Software engineers, architects and team leads have found inspiration to drive change and innovation in their team by listening to the weekly InfoQ Podcast. They have received essential information that helped them validate their software development map. We have achieved that by interviewing some of the top CTOs, engineers and technology directors from companies like Uber, Netflix and more. Over 1,200,000 downloads in the last 3 years.
Generally AI Episode 2: AI-Generated Speech and Music
In this podcast episode of Generally AI, Roland Meertens and Anthony Alford explore the world of large language models, focusing on their vulnerabilities and security measures. Additionally, they delve into the history of the transformer architecture and Google's role in its development, along with the basics of LLM inference.
Read a transcript of this interview: https://www.infoq.com/podcasts/speech-music-ai-generated/
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Weekly inspiration to drive innovation and build great teams from senior software leaders. Listen to all our podcasts and read interview transcripts:
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1/31/2024 • 43 minutes, 53 seconds
Sam Partee on Retrieval Augmented Generation (RAG)
Live from the venue of the QCon San Francisco Conference, we are talking with Sam Partee, principal engineer at Redis. In this podcast, Sam shares his insights on Redis' vector database offering, different approaches to embeddings, how to enhance large language models by adding a search component for retrieval augmented generation, and the use of hybrid search in Redis.
Read a transcript of this interview: https://bit.ly/3HzToDL
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Actionable insights on today’s critical dev priorities.
https://devsummit.infoq.com/
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The InfoQ Podcasts:
Weekly inspiration to drive innovation and build great teams from senior software leaders. Listen to all our podcasts and read interview transcripts:
- The InfoQ Podcast https://www.infoq.com/podcasts/
- Engineering Culture Podcast by InfoQ https://www.infoq.com/podcasts/#engineering_culture
- Generally AI Podcast https://www.infoq.com/generally-ai-podcast/
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1/29/2024 • 32 minutes, 15 seconds
Generally AI Episode 1: Large Language Models
In this podcast episode of Generally AI, Roland Meertens and Anthony Alford explore the world of large language models, focusing on their vulnerabilities and security measures. Additionally, they delve into the history of the transformer architecture and Google's role in its development, along with the basics of LLM inference.
Read a transcript of this interview: https://bit.ly/3HALTMV
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The InfoQ Podcasts:
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1/26/2024 • 34 minutes
Developer Upskilling and Generative AI with Hywel Carver and Suhail Patel
In this episode, Nsikan Essien talks with Hywel Carver and Suhail Patel about developer upskilling and generative AI. Together, they explore the following topics: the software engineer’s learning journey, the ways current generative AI technologies could help or hinder it, and what the role of the software engineer becomes with powerful AI technologies.
Read a transcript of this interview: https://bit.ly/42dVmTC
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https://devsummit.infoq.com/
QCon San Francisco (November 18-22, 2024)
Get practical inspiration and best practices on emerging software trends directly from senior software developers at early adopter companies.
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The InfoQ Podcasts:
Weekly inspiration to drive innovation and build great teams from senior software leaders. Listen to all our podcasts and read interview transcripts:
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1/24/2024 • 45 minutes, 6 seconds
2023 Year in Review: AI/LLMs, Tech Leadership, Platform Engineering, and Architecture + Data
In this special year-end wrap-up podcast Thomas Betts, Wes Reisz, Shane Hastie, Srini Penchikala, and Daniel Bryant reflect on technology trends in 2023 and discuss what they hope to see in 2024. Topics explored included: the use of AI and LLMs within software delivery, the changing role of technical leadership, and the increasing integration of software architecture and data engineering.
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1/15/2024 • 1 hour, 39 seconds
Shreya Rajpal on Guardrails for Large Language Models
Live from the venue of the QCon San Francisco Conference, we are talking with Shreya Rajpal, CEO and Cofounder of Guardrails AI. In this podcast, Shreya shares her insights on building guardrails for large language model (LLM) applications. Rajpal discusses how Guardrails AI assesses the reliability and safety of LLM applications, ensuring any input sent to the model is functionally correct and providing a framework for developers to create their own custom validators.
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1/8/2024 • 20 minutes, 49 seconds
InfoQ Cloud and DevOps Trends 2023
This is a repost from July 2023.
In this episode of the podcast, members of the InfoQ editorial staff will be discussing the current trends in software architecture and design, as part of the process to create our annual trends report. These reports provide InfoQ readers with a high-level overview of the topics to pay attention to, and also help the editorial team focus on innovative technologies. In addition to the report and the trends graph available on InfoQ.com, this podcast is a chance to hear our conversation and some stories our expert practitioners have observed.
Read a transcript of this interview: https://bit.ly/48FuQEH
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1/2/2024 • 42 minutes, 56 seconds
InfoQ Software Architecture & Design Trends 2023
This is a repost from March 2023.
In this episode of the podcast, members of the InfoQ editorial staff will be discussing the current trends in software architecture and design, as part of the process to create our annual trends report. These reports provide InfoQ readers with a high-level overview of the topics to pay attention to, and also help the editorial team focus on innovative technologies. In addition to the report and the trends graph available on InfoQ.com, this podcast is a chance to hear our conversation and some stories our expert practitioners have observed.
Read a transcript of this interview: https://bit.ly/3v6eOW0
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12/25/2023 • 39 minutes, 18 seconds
AsyncAPI V3 with Fran Mendez
In this episode of the podcast, Thomas Betts speaks with Fran Mendez about version 3 of AsyncAPI. The standard format for describing asynchronous APIs has evolved, and has made some breaking changes to address limitations in earlier versions.
Read a transcript of this interview: https://bit.ly/3GMLtCv
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12/18/2023 • 29 minutes, 54 seconds
Solomon Hykes Discusses Dagger, DevOps, and Docker
In this episode, Solomon Hykes, founder of Dagger and the original Docker project, sat down with Daniel Bryant to discuss the state of DevOps and how the new open source Dagger project aims to improve continuous delivery practices. Topics covered included the challenges of building applications, modernizing CI/CD tooling and practices, and building an effective community.
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12/11/2023 • 43 minutes, 30 seconds
The Software Architect's Path: Insights from Sid Anand
In this podcast Michael Stiefel spoke to Sid Anand about what it means to be a software architect, the process of becoming one, and how to be a successful architect in an organization.
Read a transcript of this interview: https://bit.ly/3R3KT8l
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12/4/2023 • 45 minutes, 50 seconds
InfoQ Java Trends Report 2023 - Discussing Insights with Mike Redlich
In this episode, Michael Redlich, lead editor of the Java topic at InfoQ, sat down with podcast co-host Daniel Bryant and discussed the recent publication of the InfoQ Java Trends Report. Topics covered included the release of Java 21, the adoption of Java virtual threads, the evolution of the Jakarta EE and Spring projects, and the development of community and ecosystems projects.
Read a transcript of this interview: https://bit.ly/3Reieyy
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11/28/2023 • 22 minutes, 44 seconds
Using ChatGPT to Search Enterprise Data with Pamela Fox
In this episode, Thomas Betts talks with Pamela Fox, a cloud advocate in Python at Microsoft. They discuss several ChatGPT sample apps that Pamela helps maintain. These include a very popular integration of ChatGPT with Azure OpenAI and Cognitive Search for querying enterprise data with a chat interface. Pamela also covers some best practices for getting started with ChatGPT apps.
Read a transcript of this interview: https://bit.ly/47wmE9r
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11/14/2023 • 33 minutes, 54 seconds
Developer-First Observability with Micha “Mies” Hernandez van Leuffen
In this episode, Thomas Betts talks with Micha “Mies” Hernandez van Leuffen about observability and incidents, and the roles of developers, SREs and other team members. One challenge is knowing what metrics to track in the first place. A developer-first approach to observability means focusing on metrics that are specific to your application.
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10/16/2023 • 26 minutes, 52 seconds
Adam Jacob Discusses DevOps, Modelling Infrastructure, and Increasing Collaboration
In this episode, Adam Jacob, CEO and co-founder at System Initiative, sat down with InfoQ podcast co-host Daniel Bryant and discussed the evolution and potential future directions of DevOps and managing infrastructure. Topics covered included the challenges remaining within the DevOps movement, how to model and manage infrastructure, and how to increase collaboration between developers and operators.
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10/2/2023 • 37 minutes, 22 seconds
Tracy Miranda on Secure Supply Chains, SBOMs, and SLSA
In this episode, Tracy Miranda, a leader in the secure software supply chain domain, sat down with InfoQ podcast co-host Daniel Bryant and discussed the current state of the industry. Topics covered included the benefits of SBOMs and SLSA, getting started with generating SBOMs, and how developers should work with leadership when evaluating their organization’s security posture.
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Oct 2-6, 2023
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9/18/2023 • 24 minutes, 20 seconds
Getting to Know Dapr with Mark Fussell and Yaron Schneider
In today's episode Thomas Betts talks to Mark Fussell and Yaron Schneider about the Distributed Applications Runtime, Dapr. In the latest InfoQ Architecture and Design Trends Report, Dapr is part of the early adopter ideas of design for portability and cloud-bound applications. Dapr provides APIs that abstract away the infrastructure details for modern applications, providing secure, best practice implementations that work across any cloud, framework, and language.
Read a transcript of this interview: https://bit.ly/3P7YSc7
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Oct 2-6, 2023
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9/11/2023 • 30 minutes, 25 seconds
AI, ML, and Data Engineering InfoQ Trends Report—September 2023
In this episode of the podcast will be discussing the current trends in the domain of AI, ML and Data Engineering as part of the process of creating our annual trends report. These reports provide InfoQ readers with a high-level overview of the topics to pay attention to and also help the editorial team focus on innovative technologies.
Read a transcript of this interview: https://bit.ly/47YpXqY
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9/6/2023 • 51 minutes, 32 seconds
Roi Ravhon on FinOps, Application Unit Economics, and Cloud Cost Optimization
In this episode, Roi Ravhon, co-founder and CEO of Finout, sat down with InfoQ podcast co-host Daniel Bryant and discussed the emergence and industry adoption of FinOps. The conversation covers topics such as the benefits of adopting FinOps, the typical journey of an organization interested in learning more about cloud costs, and a range of cultural and tooling required for a successful implementation.
Read a transcript of this interview: https://bit.ly/3sBkZ3i
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9/1/2023 • 32 minutes, 35 seconds
Building a Reliable Kafka Data Processing Pipeline With Lily Mara
In today's episode Thomas Betts talks to Lily Mara, Engineering Manager at OneSignal in San Mateo, California. She manages the infrastructure services team, which is responsible for in-house services used by other OneSignal engineering teams. They will discuss how to build a reliable Kafka data processing pipeline.
Read a transcript of this interview: https://bit.ly/3ONTM63
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8/14/2023 • 34 minutes, 28 seconds
InfoQ Cloud and DevOps Trends 2023
In this episode of the podcast, members of the InfoQ editorial staff and friends of InfoQ will be discussing the current trends in the domain of cloud and DevOps as part of the process of creating our annual trends report. These reports provide InfoQ readers with a high-level overview of the topics to pay attention to and also help the editorial team focus on innovative technologies. In addition to the report and the trends graph available on InfoQ.com, this podcast is a chance to hear our raw conversation and the stories our expert practitioners shared.
Read a transcript of this interview: https://bit.ly/3XHM6Fn
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Oct 2-6, 2023
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7/17/2023 • 42 minutes, 56 seconds
Ben Dart on 2023 Trends in Robotics at ICRA
Live from the venue of the International Conference on Robotics and Automation (ICRA), we are talking with Ben Dart about the trends in robotics. In this podcast, Ben and Roland discuss the latest robotics technology as showcased at ICRA, and discuss where this technology is on the hype cycle. They also discuss how to get started with robotics yourself.
Read a transcript of this interview: bit.ly/3XGQAMh
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7/10/2023 • 36 minutes, 51 seconds
The Evolution of Evolutionary Architecture with Rebecca Parsons
In Evolutionary Architectures, the book she co-authored, Dr. Rebecca Parsons described the principles and practices that allow architecture to evolve. In this episode of the podcast, we talk about those principles, how they’ve changed between the first and second editions of the book, and what changes we might see in the next few years.
Read a transcript of this interview: https://bit.ly/3IUg5U6
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6/5/2023 • 32 minutes
Mehrnoosh Sameki on Responsible AI
Live from the venue of the QCon London Conference, we are talking with Mehrnoosh Sameki. In this podcast, Mehrnoosh discusses the importance of responsible AI, the principles behind it, and the challenges in ensuring fairness and transparency in AI systems. She also highlights various open-source tools and approaches for developers to incorporate responsible AI practices into their machine learning models and ensure better decision-making and ethical outcomes.
Read a transcript of this interview: https://bit.ly/3BzWtAS
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5/23/2023 • 27 minutes, 1 second
From Cloud-Hosted to Cloud-Native with Rosemary Wang
Commiting to the journey of running in the cloud is quite as simple as moving your code or writing a new application on a cloud offering. Between a diverse service catalog, greater developer autonomy, rapid provisioning, surprise billing, and changing security requirements, you might find that hosting applications on the cloud does not make the most of the cloud.
In this episode of the podcast, Rosemary Wang talks about the patterns and practices that help you move from cloud-hosted to cloud-native architecture and maximize the benefit and use of the cloud. The discussion covers essential application and infrastructure considerations, as well as cost and security concerns you need to think about when approaching a cloud-native architecture.
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5/15/2023 • 30 minutes, 28 seconds
Hien Luu on ML Principles at DoorDash
Live from the venue of the QCon London Conference, we are talking with Hien Luu, head of ML Platform at DoorDash. In this podcast, Hien discusses the main principles and strategies that DoorDash uses to scale and evolve MLOps, as well as some tips for those who want to get started with MLOps.
Read a transcript of this interview: https://bit.ly/3pkOiFL
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5/8/2023 • 18 minutes, 24 seconds
Leslie Miley on AI Bias and Sustainability
Live from the venue of the QCon London Conference, we are talking with Leslie Miley, a technical advisor to the CTO at Microsoft. In this podcast, Leslie shares his insights on AI bias, sustainability, and the potential impact of AI on society. He emphasizes the importance of understanding and mitigating the harm these technologies can cause, while also discussing the responsibilities of developers, tech companies, and individuals in ensuring a more responsible and ethical approach to AI development.
Read a transcript of this interview: https://bit.ly/3LopSlT
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5/2/2023 • 33 minutes, 45 seconds
Real Time ML Pipelines Using Quix with Tomáš Neubauer
Live from the venue of the QCon London Conference we are talking with Tomáš Neubauer. He will talk about Quix Streams, an open-source Python library that simplifies real-time machine learning pipelines. In his presentation, Tomáš will discuss various architecture designs, their pros and cons, and demonstrate a real use case of detecting a cyclist crash using Quix Streams and a TensorFlow model.
Read a transcript of this interview: https://bit.ly/3L87Bck
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In this episode of the podcast, members of the InfoQ editorial staff will be discussing the current trends in software architecture and design, as part of the process to create our annual trends report. These reports provide the InfoQ readers with a high-level overview of the topics to pay attention to, and also help the editorial team focus on innovative technologies. In addition to the report and the trends graph available on InfoQ.com, this podcast is a chance to hear our conversation and some stories our expert practitioners have observed.
Read a transcript of this interview: https://bit.ly/3JHEg7O
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3/27/2023 • 39 minutes, 18 seconds
Backstage With the QCon London 2023 Programming Committee
What makes QCon software conferences stand out from other events? The top reason has to be the content, which focuses on innovator and early adopter trends, and presenters who are expert practitioners, sharing their real-world stories.
Deciding what topics to include in the conference starts with the QCon programming committee. In this episode, we're going backstage to get an understanding of how QCon London came together, and why the trends being featured are important.
Read a transcript of this interview: https://bit.ly/3mQklMx
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3/13/2023 • 25 minutes, 24 seconds
Dan Benjamin on Cloud Data Security and Data Detection and Response
In this podcast, Srini Penchikala spoke with Dan Benjamin, the CEO of Dig Security on three main topics: Cloud Data Security, Data Security Posture Management, Data Detection and Response (DDR).
Read a transcript of this interview: https://bit.ly/3KKXKe3
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2/28/2023 • 26 minutes, 44 seconds
Colin McCabe Updates on Apache Kafka KRaft Mode
Today on the InfoQ Podcast, Wes Reisz speaks with Colin McCabe about Apache Kafka’s KRaft mode. Colin is a principal engineer with Confluent working on the scalability and performance of Apache Kafka. KRaft mode is the new operating mode of Apache Kafka released with 3.3.1 and is the new target architecture for Kafka metadata (the current roadmap will completely deprecate Zookeeper in Kafka in the 4.0 release). On the podcast, Wes and Colin discuss KRaft mode and what it means for the Kafka ecosystem.
Read a transcript of this interview: https://bit.ly/3k9AtaI
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2/20/2023 • 21 minutes, 9 seconds
Expanding GraphQL Federation at Netflix with Tejas Shikhare
GraphQL can be a great choice for client to server communication, but it requires investment to maximize its potential. Netflix operates a very large, Federated GraphQL platform. Like any distributed system, this has some benefits, but also creates additional challenges. In this episode, Tejas Shikhare, explains the pros and cons of scaling GraphQL adoption.
Read a transcript of this interview: https://bit.ly/3ZxrTm6
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1/16/2023 • 30 minutes, 49 seconds
API Evolution Without Versioning with Brandon Byars
Everyone likes the idea of building something new. So much freedom. But what about making changes after you have users? In this episode, Thomas Betts talks with Brandon Byars about how you can evolve your API without versioning, a topic he spoke about at QCon San Francisco.
Read a transcript of this interview: https://bit.ly/3jONh63
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1/2/2023 • 35 minutes, 2 seconds
2022 Year in Review: ADRs, Staff Plus, Platforms, Sustainability, & Culture Design
In this special year-end wrap-up podcast Thomas Betts, Wes Reisz, Shane Hastie, Srini Penchikala, and Daniel Bryant discuss what they have seen in 2022 and muse on what they hope to see in 2023. Topics explored included: the benefits of architecture decision records (ADRs), the role of Staff Plus engineers, treating platforms as a product, the importance of sustainability and green IT, and the need to be deliberate with culture design.
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This is a re-post from April 2022.
Each year, InfoQ editors discuss what we’ve been observing across the entire software development landscape, and create several trends reports, each with its own graph of the adoption curve. This helps the editorial team focus its reporting on innovative technologies and ideas, and also provides our readers with a high-level overview of topics to keep an eye on.
There are two major components of these reports. The written report is published on InfoQ.com, and includes the trends graph and details on individual items that have been added or changed in the past year, as well a general analysis from the InfoQ editors.
The second part of the report is this episode of the InfoQ Podcast, which is a chance to listen in on part of the editors’ conversation and hear some anecdotal examples from our panel of expert practitioners.
Read a transcript of this interview: https://bit.ly/3iLjb2y
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12/12/2022 • 34 minutes, 7 seconds
The InfoQ Podcast: .NET Trends Report 2022
This is a re-post from September 2022.
In this episode of The InfoQ Podcast, we will discuss some of the .NET Trends for 2022. Today we will focus on the latest .NET developments related to User Interface and Communication. Our panelist guests for this discussion are Irina Scurtu, Microsoft MVP and International Speaker, and François Tanguay, CEO at Uno Platform.
Read a transcript of this interview: https://bit.ly/3Wdatsx
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12/11/2022 • 27 minutes, 10 seconds
Managing an API as a Product with Deepa Goyal
Not long ago, only programmers cared about APIs. Those days are behind us, and now companies need to manage their APIs as they would any other software they provide to customers. In this episode, Deepa Goyal discusses how to manage an API as a product, and how that impacts all members of the two development teams that interact with an API.
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11/28/2022 • 33 minutes, 19 seconds
The Future of Service Mesh with Jim Barton
When building a distributed system, we have to consider many aspects of the network. This has led to many tools to help software developers improve performance, optimize requests, or increase observability. Service meshes, sidecars, eBPF, layer three, layer four, layer seven, it can all be a bit overwhelming. In this podcast, Jim Barton explains some of the fundamentals of modern service meshes, and provides an overview of Istio Ambient Mesh and the benefits it will provide in the future.
Read a transcript of this interview: https://bit.ly/3UClLG6
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- Oct 2-6, 2023
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11/14/2022 • 31 minutes, 38 seconds
Susanne Kaiser on DDD, Wardley Mapping, & Team Topologies
Susanne Kaiser is a software consultant working with teams on microservice adoption. Recently, she’s brought together Domain-Driven Design, Wardley Mapping, and Team Topologies into a conversation about helping teams adopt a fast flow of change. Today on the podcast, Wes Reisz speaks with Susanne about why she feels these three approaches to dealing with software complexity are so complementary. The two then work through some of the patterns she’s seen in her consulting work and discuss how to get started, sequencing, and the effect of overall team size in applying these patterns.
Read a transcript of this interview: https://bit.ly/3z1966T
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10/31/2022 • 33 minutes, 6 seconds
Principles of Green Software Engineering with Marco Valtas
In this episode, Marco Valtas, technical lead for cleantech and sustainability at ThoughtWorks North America, discusses the Principles of Green Software Engineering. The principles help guide software decisions by considering the environmental impact. The principles are intended for everyone involved in software, and emphasize that sustainability, on its own, is a reason to justify the work.
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- August 23, 2022
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- Nov 30 - Dec 9, 2022
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10/24/2022 • 25 minutes, 54 seconds
Matt Butcher on Web Assembly as the Next Wave of Cloud Computing
Today on the InfoQ Podcast, Wes Reisz speaks with long-time open-source contributor and startup founder Matt Butcher. Matt is the CEO of Fermyon Technologies and is at the forefront of the Web Assembly (Wasm) work being done in the cloud. The two discuss Matt’s belief we’re at the start of a 3rd wave of cloud computing, the state of the Wasm ecosystem, and what Fermyon’s doing in the space. The conversation includes Spin (Fermyon’s inner loop Wasm development tooling), wasm performance/compile times, similarities to the docker ecosystem, and language support for Wasm.
Read a transcript of this interview: https://bit.ly/3MlStrZ
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10/10/2022 • 34 minutes, 18 seconds
Frederic Branczyk on Continuous Profiling Leveraging eBPF
Continuous profiling is collecting profiling data (think things like memory and CPU) all the time/throughout time in your production environment. Today on the podcast, Wes Reisz speaks with Frederic Branczyk, CEO of PolarSignals, a startup formed to enable continuous profiling leveraging eBPF. Wes and Frederic discuss the origin story of Polar Signals, eBPF (the enabling technology used by Polar Signals), Parca (the open-source system they built to collect continuous profiling data), and more, including things like FrostDB and why profiling data complements what we already have with our currenct observability stacks.
Read a transcript of this interview: https://bit.ly/3SpIcxj
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10/3/2022 • 30 minutes, 52 seconds
The InfoQ Podcast: .NET Trends Report 2022
In this episode of The InfoQ Podcast, we will discuss some of the .NET Trends for 2022. Today we will focus on the latest .NET developments related to User Interface and Communication. Our panelist guests for this discussion are Irina Scurtu, Microsoft MVP and International Speaker, and François Tanguay, CEO at Uno Platform.
Read a transcript of this interview: https://bit.ly/3BWHZvM
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9/26/2022 • 27 minutes, 10 seconds
Getting value out of an ML with Philip Howes
We are talking with Philip Howes about how to get value from your ML model as fast as possible. We will also talk about how to improve your deployed model, and what tools you can use when setting up ML projects. We conclude by discussing how stake holders should be involved, and what makes up a complete ML team.
Read a transcript of this interview: https://bit.ly/3Bwgqcv
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9/12/2022 • 27 minutes, 40 seconds
Swyx on Remote Development Environments and the End of Localhost
In this episode, Shawn Wang (swyx), head of developer experience at Airbyte, sat down with InfoQ podcast co-host Daniel Bryant and discussed the rise of remote development environments. Topics covered included, whether remote development experiences are good enough to see the death of local(host) development, what a wishlist might look like for the ultimate developer experience, and how cloud native organizations are currently developing software.
Read a transcript of this interview: https://bit.ly/3R3OEcD
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8/29/2022 • 27 minutes, 13 seconds
InfoQ AI, ML and Data Engineering Trends Report 2022
There have been a lot of innovations and developments in AI and ML space since last year. In this podcast, InfoQ’s AI, ML and Data Engineering editorial team discuss the latest trends that our readers should find interesting to learn and apply in their own organizations when these trends become mainstream technologies.
Read a transcript of this interview: https://bit.ly/3QxoZJ1
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- March 26-31, 2023
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8/1/2022 • 38 minutes, 2 seconds
Principles of Green Software Engineering with Marco Valtas
In this episode, Marco Valtas, technical lead for cleantech and sustainability at ThoughtWorks North America, discusses the Principles of Green Software Engineering. The principles help guide software decisions by considering the environmental impact. The principles are intended for everyone involved in software, and emphasize that sustainability, on its own, is a reason to justify the work.
Read a transcript of this interview: https://bit.ly/3b0hpY8
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- March 26-31, 2023
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7/25/2022 • 25 minutes, 54 seconds
Omar Sanseviero on Transformer Models and Democratizing Good ML Practices
Live from the venue of the QCon London Conference we are talking with Omar Sanseviero about Hugging Face, the limitations and biases of machine learning models, the carbon emitted when training large scale machine learning models, and democratizing good ML practices.
Read a transcript of this interview: https://bit.ly/3yTMFjc
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7/19/2022 • 33 minutes, 25 seconds
Susanne Kaiser on DDD, Wardley Mapping, & Team Topologies
Susanne Kaiser is a software consultant working with teams on microservice adoption. Recently, she’s brought together Domain-Driven Design, Wardley Mapping, and Team Topologies into a conversation about helping teams adopt a fast flow of change. Today on the podcast, Wes Reisz speaks with Susanne about why she feels these three approaches to dealing with software complexity are so complementary. The two then work through some of the patterns she’s seen in her consulting work and discuss how to get started, sequencing, and the effect of overall team size in applying these patterns.
Read a transcript of this interview: https://bit.ly/3nPmMMu
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7/11/2022 • 33 minutes, 6 seconds
Matt Klein on Envoy Gateway
When talking about edge proxy use cases, North-South is a term that is often used to talk about traffic entering a network perimeter. Envoy proxy is often used directly or as part of many other solutions when implementing these use cases. Today on the podcast, Wes Reisz speaks with Matt Klein about a recent announcement that Envoy Proxy will partner with many well-known companies in the space, including VMware, Ambassador Labs, and Tetrate to build and maintain a new member of the Envoy family – Envoy Gateway.
Read a transcript of this interview: https://bit.ly/3u17UOs
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6/27/2022 • 27 minutes, 39 seconds
Managing Tech Debt with Glenn Engstrand
In this episode, Glenn Engstrand discusses a structured approach to managing tech debt in a microservices architecture. By taking a proactive, long-term approach, all stakeholders are able to talk about, plan for, and safely reduce technical debt.
Read a transcript of this interview: https://bit.ly/3NS0ZiG
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6/13/2022 • 32 minutes, 57 seconds
Kim Lewandowski and Michael Lieberman on Securing the Software Supply Chain with SLSA
Charles Humble talks to Kim Lewandowski and Michael Lieberman about the SLSA framework. They discuss why the software supply chain is under growing attack, and explore the key ideas in SLSA.
Read a transcript of this interview: https://bit.ly/396COOm
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6/6/2022 • 27 minutes, 20 seconds
Handling High Demand Ticket On-Sales with Anderson Parra and Vitor Pellegrino
Live from the venue of the QCon London Conference we are talking with Vitor Pellegrino and Anderson Parra. They will talk about how SeatGeek is handing ticket on-sales where a large amount of users use their service in a short time, and which engineering challenges this brings.
Read a transcript of this interview: https://bit.ly/3MSIB8y
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5/30/2022 • 31 minutes, 53 seconds
Oren Eini on RavenDB, including Consistency Guarantees and C# as the Implementation Language
Wesley Reisz talks to Oren Eini about the history of RavenDB. RavenDB is a fully transactional NoSQL Document database that implements both CP and AP guarantees at different times. During the conversation, the two discuss those CP/AP distributed systems challenges, the choice of implementation language (C#), and the current plans for RavenDB 6.0, which includes a server-side sharding implementation.
Read a transcript of this interview: https://bit.ly/3LFP8C8
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5/23/2022 • 32 minutes, 52 seconds
ML Tools to Accelerate your work with Cassie Breviu
Live from the venue of the QCon London Conference we are talking with Casie Breviu. She will talk about how she got started with AI, and what machine learning tools can accelerate your work when deploying models on a wide range of devices. We will also talk about GitHub Copilot and how AI can help you be a better programmer.
Read a transcript of this interview: https://bit.ly/3wB5mHc
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5/17/2022 • 36 minutes, 13 seconds
Seven Ways to Fail at Microservices with Holly Cummins
Implementing microservices is really challenging, and there are many ways to fail. Holly Cummins has identified seven ways to fail at microservices, and on this episode of the podcast Thomas Betts asks her to describe them, and how they can be avoided.
Read a transcript of this interview: https://bit.ly/3KX9B5k
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5/10/2022 • 32 minutes, 4 seconds
Ana Medina on Chaos Engineering, Game Days, and Learning
In this podcast, Ana Medina, senior chaos engineer at Gremlin, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: how enterprise organisations are adopting chaos engineering with the requirements for guardrails and the need for “status checks” to ensure pre-experiment system health; how to run game days or IT fire drills when everyone is working remotely; and why teams should continually invest in learning from past incidents and preparing for inevitable failures within systems.
You can read the transcript here: https://bit.ly/3JSR7T0
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- June 21, 2022
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Each year, InfoQ editors discuss what we’ve been observing across the entire software development landscape, and create several trends reports, each with its own graph of the adoption curve. This helps the editorial team focus its reporting on innovative technologies and ideas, and also provides our readers with a high-level overview of topics to keep an eye on.
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4/4/2022 • 34 minutes, 5 seconds
Jaxon Repp on HarperDB NoSQL Database Platform
In the podcast, I spoke with Jaxon Repp, Head of Product at HarperDB, on their NoSQL database platform, edge persistence, and custom functions.
Jaxon has 25 years of experience architecting, designing, and developing enterprise software. He is the founder of three technology startups and has consulted with multiple Fortune 500 companies on IoT and Digital Transformation initiatives. A partially-reformed developer, he understands what it’s like to wrestle with technology instead of benefiting from it, and believes passionately that if the Jetsons never had an episode where a config file error brought down the food-o-matic, it surely should not be a problem now.
You can read the transcript here: https://bit.ly/3L9P8e3
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3/23/2022 • 26 minutes, 34 seconds
Matthew Clark on the BBC’s Migration from LAMP to the Cloud with AWS Lambda, React and CI/CD
This is a re-post from March 2021.
In this podcast Matthew Clark, Head Of Architecture for the BBC's Digital Products, sat down with InfoQ podcast co-host Charles Humble and discussed: the new architecture for the BBC’s online services; the challenges of using Lambda functions including cold start-up, function chaining, debugging and setting the memory profile; the role of DevOps and CI/CD; and the nature of a cloud transformation.
You can read the transcript here: https://bit.ly/3tfmySn
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- June 21, 2022
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3/16/2022 • 29 minutes, 34 seconds
Stefan Prodan on Flux, Flagger, and The Operator Pattern Applied to Non-Clusters Resources
In this podcast, Wesley Reisz talks to Stefan Prodan about Flux and Flagger–two tools built on top of Flux CD’s GitOps Toolkit. After discussing some of the architectural differences between Flux v1 and v2 and discussing some of the GitOps toolkit use cases, the two discuss the operator pattern on Kubernetes. They specifically spend time talking about the operator pattern, why developers may opt to build API’s on top of Kubernetes, and how the pattern can be used on non-clusters resources. The podcast wraps with a discussion on the work being down towards Flux v2’s push to GA.
You can read the transcript here: https://bit.ly/3tzQWpj
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3/7/2022 • 25 minutes, 59 seconds
Jessica Kerr on Observability and Honeycomb's Use of AWS Lambda for Retriever
In this podcast Charles Humble talks to Jessica Kerr about Honeycomb's architecture and use of Serverless, specifically AWS Lambda, as part of their custom column database system called Retriever. They also explore key differences between Retriever and Facebook’s Scuba, and how Honeycomb differs from traditional APM tools.
You can read the transcript here: https://bit.ly/3hAcaOc
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3/2/2022 • 29 minutes, 4 seconds
Clare Liguori on Automating Safe and “Hands-Off” Deployments at AWS
This is a re-post from February 2021.
In this podcast, we discuss the implementation of continuous delivery at AWS, the use of automation and deploying to multiple test environments, and the benefits of canary releasing
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2/22/2022 • 33 minutes, 7 seconds
The Architecture Advice Process with Andrew Harmel-Law
To best support continuously-delivering, autonomous teams, a software architect has to avoid being a blocker by trying to make all architectural decisions. In this episode of the podcast, Thomas Betts talks to Andrew Harmel-Law about how an advice process allows anyone to make an architectural decision, once they’ve had necessary conversations and properly documented their decision.
Read a transcript of this interview: https://bit.ly/3gNlfmo
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2/14/2022 • 37 minutes, 25 seconds
Liz Rice on Programming the Linux Kernel with eBPF, Cilium and Service Meshes
Charles Humble and Liz Rice discuss eBPF, a way of making the Linux kernel programmable. They talk about why it exists, how it works under the hood, and what you can and can’t do with it. They also talk about Cilium, an open source library for observing network connectivity between container workloads, and the new Cilium-based service mesh currently in beta.
Read a transcript of this interview: https://bit.ly/3rTPKwi
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- Feb 22, 2022
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1/31/2022 • 35 minutes, 52 seconds
Cyber Security with Maxime Lamothe-Brassard
On this episode of the InfoQ Podcast, Thomas Betts talks with Maxime Lamothe-Brassard about cybersecurity. Understanding security is very similar to understanding software architecture, with general concepts applicable to everyone, and specific needs that depend on your situation. The discussion covers roles and responsibilities, DevSecOps, and the current and future state of cloud-native security.
Read a transcript of this interview: https://bit.ly/3qXEDTy
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- Feb 22, 2022
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1/24/2022 • 27 minutes, 11 seconds
API Showdown: REST vs. GraphQL vs. gRPC – Which Should You Use?
This episode of the InfoQ podcast is the API Showdown, recorded during QCon Plus in November 2021. What is the single best API technology you should always use? Thomas Betts moderated the discussion, with the goal to understand some of the high-level features and capabilities of three popular technologies for implementing APIs. The discussion covers some of the pros and cons of GraphQL and gRPC, and why you might use them instead of a RESTful API.
Read a transcript of this interview: https://bit.ly/327JNmD
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- Feb 22, 2022
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1/17/2022 • 34 minutes, 26 seconds
Tudor Gîrba on how Moldable Development Offers a Novel Way to Reason About Systems
Charles Humble discusses Moldable Development with its creator Tudor Gîrba. They discuss Gîrba’s key insight—that developers spend more than half their time reading systems rather than writing them—and how this lead to the creation of a novel development approach, Moldable Development, and a corresponding IDE, Glamorous Toolkit, which has the potential to change both how we reason and make decisions about software systems.
Read a transcript of this interview: https://bit.ly/3Gc2Fjd
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- Feb 22, 2022
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1/10/2022 • 35 minutes, 20 seconds
AI, ML and Data Engineering InfoQ Trends Report
This is a re-post from August 2021.
Each year, the InfoQ editors discuss the current state of AI, ML and data engineering to identify the key trends that you as a software engineer, architect, or data scientist should watch. We curate our discussions into a technology adoption curve with supporting commentary to help you understand how things are evolving. We also explore what we believe you should be considering as part of your roadmap and skills development.
Read a transcript of this interview: https://bit.ly/3FOrVvu
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- Feb 22, 2022
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1/5/2022 • 58 minutes, 59 seconds
Software Architecture and Design InfoQ Trends Report 2021
This is a re-post from April 2021.
This is an overview of how the InfoQ editorial team sees the Software Architecture and Design topic evolving in 2021, with a focus on what architects are designing for today.
Read a transcript of this interview: https://bit.ly/3HfpzWN
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- Feb 22, 2022
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12/27/2021 • 54 minutes, 36 seconds
The InfoQ Podcast 2021 Year in Review: Hybrid Working, Ethics & Sustainability, and Multi-Cloud
In this special year-end wrap-up podcast Thomas Betts, Wes Reisz, Shane Hastie, Charles Humble, Srini Penchikala, and Daniel Bryant discuss what they have seen in 2021 and speculate a little on what they hope to see in 2022. Topics explored included: hybrid working, the importance of ethics and sustainability within technology, and multi-cloud architectures.
Read a transcript of this interview: https://bit.ly/32lVYfm
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- Feb 22, 2022
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12/20/2021 • 57 minutes, 43 seconds
API Lifecycles, Specifications, and Standards with Kin Lane
On this episode of the podcast, Thomas Betts talks with Kin Lane about managing your API lifecycle using standards and specifications, including OpenAPI, AsyncAPI, and JSON Schema. These specifications and the tooling based on them can help reduce communication problems, by creating documentation, generating code, and automating testing.
Read a transcript of this interview: https://bit.ly/3s6uTYo
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- Feb 22, 2022
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12/15/2021 • 33 minutes, 12 seconds
Joe, Florian and Sebastian on the Indy Autonomous Challenge
The Technical University of Munich has won the Indy Autonomous Challenge. A competition for self-racing vehicles. In this podcast Roland Meertens discussies the the event itself, what makes it challenging, and the approach the TU Munich took with Joe Speed, Florian Sauerbeck, and Sebastian Huch. We discuss the importance of simulation, the limits of hardware, and how Docker helps crossing this gap. We end the podcast by discussing the role of open source software when taking on such a challenge.
Read a transcript of this interview: https://bit.ly/3GlzbPw
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12/7/2021 • 32 minutes, 53 seconds
James Clark on How Ballerina Handles Network Interaction, Data, and Concurrency
Charles Humble discusses the design of the Ballerina programming language with its lead designer James Clark. They discuss how the goals of the language inform a number of design choices including: the type system, error handling, the concurrency model, and the language’s built in support for visualization of program flows.
Read a transcript of this interview: https://bit.ly/3xBZTQP
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- Feb 22, 2022
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11/29/2021 • 22 minutes, 36 seconds
Meenakshi Kaushik and Neelima Mukiri on Responsible AI and Machine Learning Algorithm Fairness
In the podcast, I spoke with Meenakshi Kaushik and Neelima Mukiri from Cisco team on responsible AI and machine learning bias and how to address the biases when using ML in our applications.
Meenakshi Kaushik currently works in the product management team at Cisco. She leads Kubernetes and AI/ML product offerings in the organization. Meenakshi has interest in AI/ML space and is excited about how the technology can enhance human wellbeing and productivity.
Neelima Mukiri is a principal engineer at Cisco. She is currently working in Cisco's on-premise and software service container platforms.
Read a transcript of this interview: https://bit.ly/2ZiRswO
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11/26/2021 • 32 minutes, 29 seconds
Event Driven Architectures of Scale
Wes Reisz, Matthew Clark, Gwen Shapira, and Ian Thomas discuss the evolution of event-driven architectures over the decades, the advantages that EDA offers, and thoughts for the future.
Read a transcript of this interview: https://bit.ly/2Z3b1t5
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- Feb 22, 2022
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11/19/2021 • 32 minutes, 53 seconds
Michelle Brenner Builds Netflix Workstations and Enables Artists to Create From Anywhere
Producing television shows and movies at Netflix-scale (i.e. one new movie per week instead of one or two per year) means having a way to efficiently work with many artists and content creators. Netflix Workstations were created as a cloud-based solution to provide artists with secure access to the applications and content they need to complete their work. On this episode of the podcast Thomas Betts talks with Michelle Brenner about the benefits and trade-offs of the solution that enables artists to create from anywhere.
Read a transcript of this interview: https://bit.ly/3waeORz
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- Feb 22, 2022
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11/1/2021 • 32 minutes, 36 seconds
Microsoft's Asim Hussain on Designing Software for Sustainability and the Green Software Foundation
Sustainable Software Engineering is an emerging discipline at the intersection of climate science, software, hardware, electricity markets, and data center design. In the most recent InfoQ Trends Report on architecture, the InfoQ team added designing for sustainability for the first time, suggesting that it's emerging because people are realizing that the software industry is responsible for a level of carbon usage comparable to that of the aviation industry. The question then is what can we do as individual developers and architects, if anything, and what role does the broader shift to the Cloud have? Charles Humble explores the topic with Microsoft's Asim Hussain, green cloud advocacy lead and chair of the Green Software Foundation. They discuss techniques such as demand shifting, as well as the current challenges that the Green Software Foundation is aiming to address.
Read a transcript of this interview: https://bit.ly/3jyBEx8
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- April 4-6, 2022 / London, UK
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- Nov 1-12, 2021
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- Feb 22, 2022
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10/25/2021 • 26 minutes, 19 seconds
Domain Storytelling with Stefan Hofer and Henning Schwentner
Domain storytelling is a technique for understanding a business domain by relying on people’s natural ability to learn a new language by listening to other people speaking that language. In this episode of the podcast, Stefan Hofer and Henning Schwentner cover when to use domain storytelling, what is involved in the pictographic language, and how to have productive storytelling sessions. They go into far greater detail in their new book, Domain Storytelling.
Read a transcript of this interview: https://bit.ly/3FPmlJD
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- October 19, 2021
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- November 1-12, 2021
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10/18/2021 • 23 minutes, 46 seconds
Rosaria Silipo on Codeless Deep Learning and Visual Programming
Dr. Rosaria Silipo is currently the head of data science evangelism at KNIME, spelled KNIME, the open-source data analytics platform. She is the author of 50+ technical publications, including books like “Codeless Deep Learning with KNIME,” “Practicing Data Science: A Collection of Case Studies” and “Guide to Intelligent Data Science.” She holds a doctorate degree in bioengineering and has spent more than 25 years working on data science projects for companies in a broad range of fields, including IoT, customer intelligence, financial services and cybersecurity. She also launched “Data Science Pronto!” 1-3 minute video explanations of data science concepts.
Read a transcript of this interview: https://bit.ly/3Do4BD9
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- October 19, 2021
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- November 1-12, 2021
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10/11/2021 • 26 minutes, 51 seconds
Lin Clark on the Web Assembly Component Model
The WebAssembly Component Model is a language-neutral approach to building web assembly applications in small units that can be assembled into a larger application. Using the metaphor of lego blocks, Lin Clark (a Senior Principal Software Engineer at Fastly) discusses the background, roadmap, and design goals for creating the Web Assembly Component Model. Lin is a central figure working on Web Assembly (wasm), Web Assembly System Interface (WASI), and now Web Assembly Component Model. Today on the podcast, Lin and Wes talk web assembly and the work happening around developing the component model.
Read a transcript of this interview: https://bit.ly/3a9R5Xk
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- October 19, 2021
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- November 1-12, 2021
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10/5/2021 • 30 minutes, 3 seconds
Sam Newman on Information Hiding, Ubiquitous Language, UI Decomposition and Building Microservices
In this episode of the InfoQ podcast Charles Humble talks to Sam Newman, an independent consultant focusing on microservices, cloud and CD, about the 2nd edition of Newman’s book Building Microservices, published by O’Reilly. They discuss information hiding; ideas from Domain Driven Design including aggregates, bounded contexts and ubiquitous language; UI decomposition; and team structure drawing on ideas from Team Topologies.
Read a transcript of this interview: https://bit.ly/3lXqBxx
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- October 19, 2021
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- November 1-12, 2021
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9/27/2021 • 38 minutes, 47 seconds
Tammy Bryant Butow on SRE Apprentices
In this episode, Thomas Betts speaks with Tammy Bryant Butow, principal SRE at Gremlin about training new site reliability engineers. The discussion covers a formal SRE Apprenticeship program Tammy led at DropBox, and gets into ideas about the best way to teach people new technical skills. There are benefits for the trainees, the mentors, and the company, when you put in the effort to create a formal training program.
Read a transcript of this interview: https://bit.ly/3E3Oo7t
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- September 21, 2021
- October 19, 2021
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- November 1-12, 2021
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9/13/2021 • 30 minutes, 51 seconds
Neal Ford and Mark Richards - Software Architecture: The Hard Parts
In their upcoming book, Software Architecture: The Hard Parts, Neal Ford and Mark Richards explain that every architectural decision involves trade-offs, and provide guidance on how to evaluate those trade-offs. In this episode of the InfoQ Podcast, co-host Thomas Betts spoke with Neal and Mark about the role of a software architect and the skills necessary to be successful. One of the hardest parts is recognizing that there are no right or wrong answers, or easy decisions, and this can be especially challenging for those who come from a programming background.
Read a transcript of this interview: https://bit.ly/3BQewAT
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- September 21, 2021
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- November 1-12, 2021
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9/7/2021 • 36 minutes, 54 seconds
Francesca Lazzeri on Machine Learning for Time Series Forecasting
In the podcast, Srini Penchikala spokes to Dr. Francesca Lazzeri on Machine Learning for Time Series Forecasting as the main topic which included automated machine learning and deep learning for time series data forecasting as well as other emerging trends in Machine Learning Development and Operations areas including Data Science Lifecycle.
Dr. Francesca Lazzeri currently works as Principal Cloud Advocate Manager at Microsoft. She is an experienced scientist and a machine learning practitioner with over 12 years of both academic and industry experience. She is the author of a number of publications, including technology journals, conferences, and books.
Read a transcript of this interview: https://bit.ly/38x1V8N
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- September 21, 2021
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- November 1-12, 2021
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8/30/2021 • 34 minutes, 24 seconds
Alex Matyushentsev on Argo CD, Argo Rollouts, and Continuous Delivery with Kubernetes
In this podcast Alexander Matyushentsev, principle software engineer at Intuit and core engineer on the Argo CD and Argo Rollouts projects, sat down with InfoQ podcast host Daniel Bryant and discussed the Argo projects, continuous delivery with Kubernetes, and how platform teams can help developers embrace modern release techniques and related technologies.
Read a transcript of this interview: https://bit.ly/3zyKP6o
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- September 21, 2021
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- November 1-12, 2021
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8/23/2021 • 33 minutes, 58 seconds
Lucas Cavalcanti on Using Clojure, Microservices, Hexagonal Architecture and Public Cloud at Nubank
In this episode of the InfoQ podcast Charles Humble talks to Lucas Cavalcanti, a Principal Engineer at Nubank, which is the leading FinTech in Latin America and has become the most valuable digital bank in the world. They discuss Nubank’s early architectural choices including starting with Clojure and microservices, the challenges of using public cloud for financial services in Brazil, Nubank’s desire for immutable architecture and use of Alistair Cockburn's Hexagonal Architecture, and lessons learnt as the startup scaled.
Read a transcript of this interview: https://bit.ly/3m6wXMQ
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- September 21, 2021
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- November 1-12, 2021
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8/16/2021 • 35 minutes, 58 seconds
AI, ML and Data Engineering InfoQ Trends Report - August 2021
An overview of how the InfoQ editorial team sees the AI, ML, and Data Engineering topic evolving in 2021. Topics discussed are deep learning, edge deployment of machine learning algorithms, commercial robot platforms, GPU and CUDA programming, natural language processing and GPT-3, MLOps, and AutoML.
Read a transcript of this interview: https://bit.ly/3xF0MGJ
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- August 17, 2021
- September 21, 2021
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- November 1-12, 2021
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8/9/2021 • 59 minutes, 14 seconds
What Have We Learned Over the Last Decade of Microservices?
This episode is a panel discussion from the microservices track QCon Plus, held in May 2021. Track host Nicki Watt asks "What have we learned over the last decade of microservices." The panelists included Chris Richardson, James Lewis, and Katie Gamanji. The discussion started with looking at how the meaning of "microservices architecture" has evolved over the past ten years. There were some great insights about how successfully developing, deploying, and maintaining software depends as much or more on cultural and environmental factors, than simply adopting microservices and all the tools and technology that now exist.
Read a transcript of this interview: https://bit.ly/3rOTrD7
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- August 17, 2021
- September 21, 2021
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- November 1-12, 2021
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8/4/2021 • 32 minutes, 22 seconds
Michael Perry on Immutable Architecture, CAP Theorem, and CRDTs
In this episode of the InfoQ podcast Charles Humble talks to Michael Perry about his book “The Art of Immutable Architecture”. They discuss topics including the eight fallacies of distributed computing: a set of assertions made by L Peter Deutsch and others at Sun Microsystems describing false assumptions that programmers new to distributed applications invariably make. Other topics include Pat Helland’s paper “Immutability Changes Everything”, Eric Brewer's CAP Theorem, eventual consistency, location independent identity, and CRDTs. They also discuss how the approach to building distributed systems advocated by Perry could be introduced to a real-world enterprise app that needs to integrate with mutable downstream systems.
Read a transcript of this interview: https://bit.ly/3wWMNvp
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- August 17, 2021
- September 21, 2021
- October 19, 2021
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- November 1-5, 2021
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7/26/2021 • 30 minutes, 15 seconds
Fran Méndez on AsyncAPI
On this episode of the podcast, Fran Mendez, founder of the AsyncAPI Initiative spoke with co-host Thomas Betts. AsyncAPI is a specification and growing set of tools to help developers define asynchronous APIs, and build and maintain event-driven architectures. AsyncAPI hopes to provide features and benefits to those of OpenAPI (fka Swagger) for RESTful APIs. The specification and all tooling are community-driven and fully open source.
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- July 20, 2021
- August 17, 2021
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7/19/2021 • 29 minutes, 22 seconds
Martin Mao on Observability, focusing on Alerting, Triage, & RCA
Observability is a crucial aspect of operating Microservices at scale today.
Today on the InfoQ podcast, Wes Reisz speaks with Chronosphere’s CEO Martin Mao about how he thinks about observability. Specifically, the two discuss Chronosphere’s strategy for implementing a successful observability program. Starting with alerting, Martin discusses how metrics (usually things like RED metrics or Google’s Four Golden Signals) are tools to aggregate counts and let operators know when things are moving towards an incident. In stage two of this approach, operators begin to isolate and triage what’s happening in an effort to provide a quick system restoration. Finally, Martin talks about root cause analysis (RCA) in the final stage as a way of preventing what happened from happening again. Martin uses this three stage approach (and the questions that should be asked in each of these stages) as a way of focusing on what’s important (or reducing things like Mean Time to Recovery) in a modern cloud native architecture.
Observability is the ability to understand the state of a system by observing its outputs, on today’s podcast we talk about a strategy for implementing a meaning observability program.
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- July 20, 2021
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7/13/2021 • 26 minutes, 13 seconds
Chris Richardson on Design-Time Coupling in Microservices
In this episode of the InfoQ Podcast, Thomas Betts speaks with Chris Richardson about minimizing design-time coupling in a microservice architecture. Chris begins by defining design-time coupling, and contrasts it with runtime coupling. We then discuss some of the problems that arise from design-time coupling, anti-patterns and symptoms that are warning signs of high coupling, and the trade-offs that architects need to consider in their designs.
Read a transcript of this interview: https://bit.ly/2SA4oLD
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- June 22, 2021
- July 20, 2021
- August 17, 2021
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6/21/2021 • 31 minutes, 12 seconds
John DesJardins on Continuous Intelligence and In-Memory Computing
In this podcast, John DesJardin, Chief Technology Officer at Hazelcast, met with InfoQ podcast co-host Thomas Betts to discuss the idea of continuous intelligence. This is a paradigm shift from traditional business intelligence, and relies on a corresponding move from batch-based ETL and reporting to continuous processing of streaming data. Although the languages being used, such as Python and SQL, will be familiar, developers must pay special attention to the characteristics of time-series data, especially in near-real-time scenarios. We cover the current state of the tools and technologies in use, why companies are adopting continuous intelligence to remain competitive, and we even get a bit into what the future of data processing and analysis will look like.
Read a transcript of this interview: https://bit.ly/3iDmQ0i
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- June 22, 2021
- July 20, 2021
- August 17, 2021
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6/14/2021 • 26 minutes, 45 seconds
Ron Pressler on Java Project Loom, Virtual Threads and Structured Concurrency
In this podcast Ron Pressler, technical lead for Project Loom at Oracle, sat down with InfoQ podcast co-host Charles Humble to discuss the project and its forerunner Quasar. Topics include the differences between concurrency and parallelism; what virtual threads are; current issues with JVM concurrency; the Loom developer experience; pluggable schedulers; structured concurrency; and more.
Read a transcript of this interview: https://bit.ly/34duS7G
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- June 22, 2021
- July 20, 2021
- August 17, 2021
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5/27/2021 • 33 minutes, 40 seconds
Phil Estes on Containerd, K8s Deprecation of Dockershim, Container Runtime Architecture
The container runtime is software that executes containers and manages container images. Today, when many people think about a container runtime, they're likely thinking of Docker. However, Docker is more a set of tools for building, packaging, sharing, and running a container via Docker Daemon that then makes syscalls to another tool like containerd. Containerd, in turn, makes calls to an implementation like runc that lays down the file system for the container and is the executor for the process. Today, on The InfoQ Podcast Wes Reisz talks with Phil Estes, one of the containerd maintainers, about container runtimes. The two discuss the significance (in detail) of the announcement that dockerhsim will soon be deprecated in Kubernetes, the complete container runtime stack, work the Open Container Initiative (OCI) is doing today on a third container spec around registries, and more.
Read a transcript of this interview: https://bit.ly/3uUdoZC
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- June 22, 2021
- July 20, 2021
- August 17, 2021
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- May 17-28, 2021
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5/12/2021 • 30 minutes, 49 seconds
Open Policy Agent (OPA) with the Project’s Co-Creators
The Open Policy Agent is used for policy decision-making across the stack. In the case of Kubernetes, it is often used as an admission controller to protect the API Server with dynamic rules that don’t require recompilation to introduce. Today on the InfoQ Podcast, Wes Reisz speaks with Tim Hinrichs and Torin Sandall (two of the Open Policy Agent Project creators). The three talk about the project, including things like architecture, origin, community, the policy language (Rego), and, of course, performance. The podcast is an introduction to how OPA can is used across the stack for policy decisioning.
Read a transcript of this interview: https://bit.ly/3vkqboi
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- June 22, 2021
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- August 17, 2021
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- May 17-28, 2021
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4/26/2021 • 33 minutes, 25 seconds
Software Architecture and Design InfoQ Trends Report—April 2021
An overview of how the InfoQ editorial team sees the Software Architecture and Design topic evolving in 2021, with a focus on what architects are designing for today.
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- June 22, 2021
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4/19/2021 • 55 minutes, 52 seconds
Anurag Gupta on Day 2 Operations, DevOps, and Automated Remediation
In this podcast Anurag Gupta, founder and CEO of Shoreline.io, sat down with InfoQ podcast host Daniel Bryant and discussed: the role of DevOps and site reliability engineering (SRE), day 2 operations, and the importance of building observability into applications and platforms.
Read a transcript of this interview: https://bit.ly/3mdMSHa
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- April 13, 2021
- June 22, 2021
- July 20, 2021
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- May 17-28, 2021
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4/5/2021 • 30 minutes, 50 seconds
Matthew Clark on the BBC’s Migration from LAMP to the Cloud with AWS Lambda, React and CI/CD
In this podcast Matthew Clark, Head Of Architecture for the BBC's Digital Products, sat down with InfoQ podcast co-host Charles Humble and discussed: the new architecture for the BBC’s online services; the challenges of using Lambda functions including cold start-up, function chaining, debugging and setting the memory profile; the role of DevOps and CI/CD; and the nature of a cloud transformation.
Read a transcript of this interview: https://bit.ly/3u2I8H5
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- April 13, 2021
- June 22, 2021
- July 20, 2021
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- May 17-28, 2021
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3/29/2021 • 30 minutes, 19 seconds
Ted Young on Observability and the Release of OpenTelemetry 1.0
In this podcast Ted Young, director of developer education at Lightstep, sat down with InfoQ podcast host Daniel Bryant and discussed: observability (and the three pillars), the OpenTelemetry CNCF sandbox project and the 1.0 release, and how to build an effective telemetry collection platform.
Read a transcript of this interview: https://bit.ly/3eWqJvF
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- April 13, 2021
- June 22, 2021
- July 20, 2021
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- May 17-28, 2021
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3/22/2021 • 33 minutes, 25 seconds
Michael Feathers: Looking Back at Working Effectively with Legacy Code
Several years ago, today's guest Michael Feathers published a book called Working Effectively with Legacy Code. This book introduced ways of wrangling large codebases. In the book, Feather's discussed leveraging unit tests to introduce--not only a validation of correctness but also-- documentation on a system's operation, ways to decouple/modularize monolithic code, and 24 different techniques to introduce change safely. Today on the podcast, Wes Reisz and Michael Feathers go back and review the book. The two spend some time reviewing key concepts from the book and then discuss how the techniques can be applied today. The two wrap with a discussion on what might change in a new version of the book.
Read a transcript of this interview: https://bit.ly/3qREZrL
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- March 16, 2021
- April 13, 2021
- June 22, 2021
- July 20, 2021
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- May 17-28, 2021
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3/15/2021 • 29 minutes, 57 seconds
Phil Winder on the History, Practical Application, and Ethics of Reinforcement Learning
In this episode of the InfoQ podcast Dr Phil Winder, CEO of Winder Research, sits down with InfoQ podcast co-host Charles Humble. They discuss: the history of Reinforcement Learning (RL); the application of RL in fields such as robotics and content discovery; scaling RL models and running them in production; and ethical considerations for RL.
Read a transcript of this interview: https://bit.ly/3uylAPz
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3/1/2021 • 33 minutes, 4 seconds
Clare Liguori on Automating Safe and “Hands-Off” Deployments at AWS
In this podcast Clare Liguori, Principal Software Engineer at Amazon Web Services, sat down with InfoQ podcast host Daniel Bryant and discussed: the implementation of continuous delivery at AWS, the use of automation and deploying to multiple test environments, and the benefits of canary releasing.
Read a transcript of this interview: https://bit.ly/3qwCCLy
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2/22/2021 • 34 minutes, 20 seconds
Carin Meier Using Machine Learning to Combat Major Illness, such as the Coronavirus
In this podcast, Carin Meier of Reify Health sits down with Wesley Reisz and discusses how machine learning is being used to combat major illnesses (such as the coronavirus). After a short discussion on some of the work being done today, the two shift into a discussion on the challenges of working with healthcare data and machine learning. Topics around safety, ethics, and explainability are discussed.
Read a transcript of this interview: https://bit.ly/3b6q1IB
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2/16/2021 • 28 minutes, 29 seconds
Anubhav Mishra and Nic Jackson on Platforms, Developer Workflows, and HashiCorp Waypoint
In this podcast, Anubhav Mishra and Nic Jackson from HashiCorp sat down with InfoQ podcast host Daniel Bryant. Topics discussed included: the benefits and challenges of creating application platforms in the cloud, the need for effective developer workflows, and the role of the new HashiCorp Waypoint tool and service meshes within workflows.
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2/8/2021 • 31 minutes, 44 seconds
Service Meshes and Linkerd with William Morgan
Today on the podcast, we talk about LinkerD and the larger Service Mesh space with William Morgan (CEO of Buoyant). We cover William’s thoughts around important concerns such as latency and cost (both in your cloud bill and in real human costs) of operating services, we talk a bit about the birth and evolution of LinkerD (including some of the design decisions such as Rust in the data plane and Go in the control plane building Linkerd), and, finally, we’ll talk about the importance of security with service meshes (and how it should be reasoned).
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2/1/2021 • 31 minutes, 50 seconds
Melissa Benua on Continuous Delivery, Platforms, and DevTestSecOps
In this podcast, Melissa Benua, Director of Engineering at mParticle, sat down with InfoQ podcast host Daniel Bryant and discussed: the importance of the roles of testing and security within DevOps; the benefits and challenges of building systems with teams of generalists; and how to “bake in” observability of systems from day zero.
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1/25/2021 • 20 minutes, 56 seconds
Ann Lewis Discusses the Political Tech Landscape, MoveOn’s Architecture, and Scaling Challenges
For this podcast, Ann Lewis, CTO at MoveOn, sat down with InfoQ podcast co-host Charles Humble. Topics discussed included: the political tech landscape; MoveOn’s architecture and scaling challenges; MoveOn’s open-source text banking platform Spoke; and advice when stepping into a CTO role.
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1/11/2021 • 34 minutes, 8 seconds
Kavitha Srinivasan on Federated GraphQL Adoption, Performance Considerations, and DevEx at Netflix
In this podcast, Kavitha Srinivasan, a senior software engineer at Netflix, sat down with InfoQ podcast co-host Charles Humble. Topics discussed included: how the two main Netflix business units are migrating to GraphQL; how the schema is managed; performance considerations when working with GraphQL; the role of DevEx in a large migration.
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1/4/2021 • 30 minutes, 5 seconds
Mario Platt on DevSecOps, Platforms, and Threat Modelling
In this podcast, Mario Platt, VP Head of Information Security at CloudMargin, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: the differences and similarities between DevSecOp and DevOps; the role of a platform in relation to system security; and the value of threat modelling.
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12/30/2020 • 25 minutes, 48 seconds
InfoQ Podcaster 2020 Year in Review: Challenges, Distributed Working & Looking to the Future
In this podcast, InfoQ podcast hosts, Wes Reisz, Shane Hastie, Charles Humble and Daniel Bryant, sit down for the 2020 year in review edition of the podcast. Topics discussed included: the technology industry’s response to the change in working habits; the rise of online events; the future of cloud platforms; remote working and leadership; and the need to be kind to yourself and others.
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12/21/2020 • 28 minutes, 51 seconds
Michelle Noorali on the Service Mesh Interface Spec and Open Service Mesh
In this podcast, Michelle Noorali, senior software engineer at Microsoft, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: the service mesh interface (SMI) spec, the open service mesh (OSM) project, and the future of application development on Kubernetes.
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11/30/2020 • 27 minutes, 6 seconds
Stephen Wolfram on Computer Language Design, SMP, Mathematica, and Wolfram Language
Stephen Wolfram is a British-American computer scientist, theoretical physicist, and businessman. He is also known for his work in mathematics. In 2012, he was named an inaugural fellow of the American Mathematical Society.
In this episode of the InfoQ podcast Charles Humble talks to him about Wolfram Language, its origins and the influences on its creation. In a wide-ranging discussion they also cover the ergonomics of programming languages; Wolfram|Alpha’s integration with Siri, Alexa, and the upcoming integration with Microsoft Excel; how ideas from physics, such as reference frames, may be useful for distributed systems programming; and live streaming language design discussions via Twitch.
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11/16/2020 • 50 minutes, 54 seconds
Andrew Clay Shafer on Three Economies, the Wall of Confusion, and the Origin of DevOps
Today on the InfoQ Podcast, Wes Reisz speaks with one of the people at the center of the creation of the idea of DevOps. Andrew Clay Shafer is the VP of Transformation at Red Hat where his role is about helping companies change their relationship with software in the cloud native ecosystem. In 2009, he was one of the people who first helped to shape what we know today as DevOps. On the podcast Shafer talks about the Three Economies, Wall of Confusion, and a bit about those first mentions of DevOps.
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11/3/2020 • 32 minutes, 43 seconds
Alois Reitbauer on Cloud Native Application Delivery, Keptn, and Observability
In this podcast, Alois Reitbauer, VP, Chief Technical Strategist and Head of Innovation Lab, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: microservices vs functions; the go-micro and micro frameworks; and the evolution of PaaS and how the new M3O platform fits into the landscape.
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10/28/2020 • 31 minutes, 34 seconds
KIP-500: Removing the Dependency of Zookeeper on Kafka
Today on the InfoQ Podcast, Wes Reisz talks with two of the engineers currently working on removing the dependency of ZooKeeper in Kafka. ZooKeeper is used to maintain the metadata store required to operate Kafka. While ZooKeepers removal from Kafka will simplify the operational complexity and improve some of the scalability aspects of the platform, it is a huge undertaking that represents major changes to the overall architecture. Justin Gustafson and Colin McCabe are two engineers working on change. On the podcast, the three discuss why the team made this decision, what the ramifications are, and explore what both the near and future state will be with upgrading and operating Kafka.
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10/19/2020 • 31 minutes, 39 seconds
Asim Aslam on Microservices, go-micro, and PaaS 3.0
In this podcast, Asim Aslam, founder and CEO of Micro, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: microservices vs functions; the go-micro and micro frameworks; and the evolution of PaaS and how the new M3O platform fits into the landscape.
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10/12/2020 • 24 minutes, 45 seconds
Anne Currie Discusses Cloud Providers and the Environmental Impact of Software
Charles Humble talks to Anne Currie from Container Solutions, exploring the environmental impact of technology. They look at how technology compares to other industries such as aviation and farming, how the big cloud providers compare in terms of their commitments to reducing carbon emissions, and the impact of the choices made by individual developers and software architects.
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10/5/2020 • 27 minutes, 22 seconds
Matthew Skelton and Manuel Pais on Team Topologies
In this podcast, Matthew Skelton and Manuel Pais, co-authors of the book Team Topologies, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: the role of a modern software architect, how team design impacts software architecture, creating “team APIs” in order to reduce cognitive load, and the benefits of building a “thinnest viable platform”.
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9/28/2020 • 32 minutes, 2 seconds
Pat Helland on Software Architecture and Urban Planning
Today on The InfoQ Podcast, Wes Reisz talks to Pat Helland about the relationship between software architecture and urban planning. Pat explores planning for future growth, regulations/standards, and communication practices that cities--and software architecture--had to evolve to use. He uses these comparisons to distil lessons that architects can use in building distributed systems. A key theme throughout the podcast is constraints improve system design by restraining project scope.
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9/21/2020 • 26 minutes, 39 seconds
John DesJardins on In-Memory Data Grids, Stream Processing, and App Modernization
In this podcast, John DesJardins, field CTO and VP solution architecture at Hazelcast, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: how in-memory data grids have evolved, use cases at the edge (IoT, ML inference), integration of stream processing APIs and techniques, and how data grids can be used within application modernization.
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9/14/2020 • 33 minutes, 3 seconds
Akhilesh Gupta on the Architecture of LinkedIn’s Real-time Messaging Platform
Charles Humble talks to Akhilesh Gupta, the technical lead for LinkedIn's real-time delivery infrastructure, and also LinkedIn messaging. They discuss the architecture behind LinkedIn’s real-time platform, its building blocks, the frameworks used and other technical details.
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9/7/2020 • 22 minutes, 30 seconds
Yan Cui on Serverless Orchestration & Choreography, Distributed Tracking, Cold Starts, and more
Today on the InfoQ Podcast, Yan Cui (a long time AWS Lambda user and consultant) and Wes Reisz discuss serverless architectures. The conversation starts by focusing on architectural patterns around choreography and orchestration. From there, the two move into updates on the current state of serverless cold start times, distributed tracing, and state. Today’s podcast, while not specific to AWS, does lean heavily on Yan’s expertise with AWS and AWS Lambda.
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8/31/2020 • 24 minutes, 26 seconds
Liran Haimovitch on Understandability, Complexity, and Live Debugging
In this podcast, Liran Haimovitch, CTO at Rookout, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: the concept of “understandability” and how this relates to building modern software systems, how complexity impacts a system’s understandability, and the benefits of live debugging tooling.
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8/21/2020 • 22 minutes, 52 seconds
Ana Medina on Chaos Engineering, Game Days, and Learning
In this podcast, Ana Medina, senior chaos engineer at Gremlin, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: how enterprise organisations are adopting chaos engineering with the requirements for guardrails and the need for “status checks” to ensure pre-experiment system health; how to run game days or IT fire drills when everyone is working remotely; and why teams should continually invest in learning from past incidents and preparing for inevitable failures within systems.
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8/10/2020 • 29 minutes, 41 seconds
Stefan Prodan on Progressive Delivery, Flagger, and GitOps
In this podcast, Stefan Prodan, developer experience engineer at Weaveworks and creator of the Flagger project, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: how progressive delivery extends the core ideas of continuous delivery; how the open source Flagger Kubernetes operator can be used to implement a progressive delivery strategy via canary releasing with an API gateway or service mesh; and the new “GitOps toolkit” that has evolved from the Flux continuous delivery operator.
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7/28/2020 • 38 minutes, 1 second
Rancher on Hybrid Cloud, Kubernetes at the Edge, and Open Standards
In this podcast, Shannon Williams, co-founder and president at Rancher Labs and Darren Shepherd, co-founder and CTO at Rancher Labs sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: the adoption of hybrid cloud across organisations, the evolution of Kubernetes as a key abstraction for portability and cross-cloud security, running thousands of Kubernetes clusters at the edge, and the value of open standards.
Why listen to this podcast
- Organisations are adopting hybrid cloud strategies. The use of containers to package and run applications across clouds has seen large adoption over the past five years. Containers and Kubernetes are everywhere: the datacenter, the edge, embedded systems, and other locations.
- Two enterprise use cases for Kubernetes stand out: providing standardised abstractions and APIs to increase portability across vendors and cloud platforms; and providing a framework and homogenised foundation on which to build and implement (cross cloud) security solutions.
- Open standards support interoperability and drive innovation. The CNCF is becoming the natural home for open cloud technologies. The Rancher team have donated Longhorn, their cloud-native distributed storage platform for Kubernetes that was recently announced as generally available, to the CNCF.
- With the success of lightweight Kubernetes distributions, such as Rancher’s K3s, engineers are starting to deploy standalone Kubernetes clusters “by the thousands” to edge locations. Rancher has recently released Fleet, a new open source project that is focused on managing large collections (“fleets”) of Kubernetes clusters.
- Many developers and end users of Kubernetes simply want a platform-as-a-service (PaaS)-like experience. The next 12 months will see the community focus on the simplification of the Kubernetes ecosystem.
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7/10/2020 • 31 minutes, 57 seconds
Nora Jones on Resilience Engineering, Mental Models, and Learning from Incidents
In this podcast, Nora Jones, Co-Founder and CEO at Jeli and co-author of O’Reilly’s “Chaos Engineering: System Resiliency in Practice”, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: chaos engineering and resilience engineering, planning and running effective chaos experiments, and learning from incidents.
Why listen to this podcast:
- The chaos engineering and resilience engineering fields, although inextricably linked, are often incorrectly conflated. Resilience engineering is focused on “identifying and then enhancing the positive capabilities of people in organizations that allow them to adapt effectively and safely under varying circumstances.”
- The UX of internal or engineering-focused tooling, such as chaos experimentation tooling, is extremely important. However, engineers that create these tools often overlook the value of UX, or don’t have the relevant skills in user design research to undertake this.
- We all work in socio-technical systems. It is important to take the time to understand both aspects. Developing empathy and working alongside teams that you are trying to influence is essential. It is extremely important to continually work to build correct “mental models” of a system.
- The before and after of running a chaos experiment is as important as running the experiment itself. However, the aspects of planning, creating effective hypotheses, and analysing and disseminating the results are often under-resourced.
- Incident analysis can be a catalyst to help you understand more about your system. The Learning from Incidents website, alongside books such as Sidney Dekker’s The Field Guide to Understanding Human Error and Scott Snook’s Friendly Fire, can provide excellent background information to these topics.
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7/3/2020 • 36 minutes
Rob Skillington on Metrics Collection, Uber’s M3, and OpenMetrics
In this podcast, Rob Skillington, co-founder and CTO at Chronosphere, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: metrics collection at scale, multi-dimensional metrics and high-cardinality, developer experience with platform tooling, and open standards related to observability.
Why listen to this podcast:
- Over the past ten years the requirements related to monitoring and alerting, and the approach taken to implement this, has changed considerably. Compute is now ephemeral and dynamic, services are more numerous, and engineers want to instrument more things. Scalability of a monitoring solution is vitally important.
- One of the challenges with metric data is the limited information for providing context for collected values. This can be solved by using multi-dimensional metrics. Dimensions of a metric are name-value pairs that carry additional data to describe the metric value. High dimensionality can lead to high cardinality.
- Uber’s M3 metrics collection system initially used open source components such as Cassandra and ElasticSearch for storage and indexing. As the scale of usage of M3 increased, these OSS components were gradually replaced by custom components, such as M3DB.
- Building an effective user experience for operational tooling, especially observability-foused tooling, is vitally important. Engineers will be interacting with these tools on a daily basis. They will also be relying on these tools for both alerting and being able to locate and understand what is occurring during production issues.
- Open standards are vitally important for interoperability. The OpenMetrics project is an effort to create an open standard for transmitting metrics at scale, with support for both text representation and protocol buffers.
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6/26/2020 • 33 minutes, 16 seconds
Johnny Boursiquot on Serverless Go and Site Reliability Engineering at Heroku
In this podcast, Johnny Boursiquot, Site Reliability Engineer at Heroku, sat down with InfoQ podcast co-host Daniel Bryant and discussed topics that included: why Go is a useful language for building Function-as-a-Service (FaaS) style applications; how Heroku implement the role of Site Reliability Engineer (SRE); and why the ability to teach is such a valuable skill.
Why listen to this podcast:
- Go is a useful language for building Function-as-a-Service (FaaS) style applications. The ability to build Go applications into a static binary reduces the need for dependency management, and the quick runtime and application start time is good for initiation and scaling
- The FaaS development toolchain has improved over the years. Many cloud providers now provide local runtimes, e.g. AWS SAM Local, and service simulators, e.g. LocalStack. Testing in production is facilitated by the ability to do dark launches and canary releasing at the ingress/API gateway
- Developing “serverless” applications typically does not remove the need for operational expertise on a development team. Designing systems appropriately and getting the most out of the runtime (with minimal cost) requires knowledge of the underlying infrastructure components
- The role of Site Reliability Engineering (SRE) looks different across practically every organisation. The Heroku SRE team have adapted well-established patterns and practices into their roles. They act as “diplomats”, working closely with product teams to share knowledge around operational best practices
- The ability to teach is a valuable skill, regardless of your job. Teaching people to code or to embrace important operational principles is extremely rewarding. - Engineers who teach must seek to escape the pull of their ego; by focusing on the needs of the people you are teaching, much more progress can be made.
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6/19/2020 • 41 minutes, 7 seconds
Matt Debergalis on GraphQL and Data Modelling in the Enterprise
In this podcast, Matt Debergalis, Founder and CTO at Apollo, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: the motivations for GraphQL, the Apollo Data Graph platform, data modelling in an enterprise context, and how incrementally adopting GraphQL can help with decoupling the evolution of frontend and backend systems.
Why listen to this podcast:
- The challenges of defining client-side-friendly data models, building maintainable and composable backend APIs, and moving data from the cloud to a client application contributes to making modern software development difficult and time consuming.
- GraphQL is an open-source data query and manipulation language for APIs, and a runtime for fulfilling queries with existing data. GraphQL lets application developers describe the data they need and bring that data into the screens that they are building for their users.
- The Apollo Data Graph platform is a middleware layer that provides a way of decoupling the core business APIs from the client-side consumption patterns. Apollo can implement cross-cutting concerns, such as transaction management, which mitigates the need to implement this in (potentially multiple) client-side applications.
- Apollo makes it possible to build a “data graph”: a series of graphs that are composed from an organisation’s data for use within client-side applications. A data graph is especially valuable in larger enterprises because it is here that many (money making) systems with existing APIs need to be combined to meet new business requirements.
- GraphQL can be adopted in an incremental fashion. To begin adoption just build the simplest possible graph that matches the needs of the first application, the first screen, or the first component that is required to transition over to the graph. Then let that graph evolve.
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6/13/2020 • 33 minutes, 35 seconds
Lin Sun and Neeraj Poddar on Istio, Wasm, and the Future of Service Mesh
In this podcast, Lin Sun, senior technical staff member and master inventor at IBM, and Neeraj Poddar, engineering lead and architect at Aspen Mesh, sat down with InfoQ co-host Daniel Bryant. Topics discussed included: the evolution of service mesh data planes and control planes, the new Istio 1.5 architectures, Istio WebAssembly extension support, and the future of service mesh technology.
Why listen to this podcast:
- A service mesh in one implementation approach to provide service discovery, traffic management, and cross-cutting communication concerns that engineers see when they adopt (micro)service-based.
- The data plane of most modern service mesh implementations run out-of-process as a proxy sidecar. This has evolved from library based implementations, such as Airbnb’s SmartStack or Netflix’s OSS libraries.
- The recent release of Istio 1.5 saw the deployment packaging of the control plane move from a microservice-based approach to that of a monolithic implementation, named “istiod”.
- Istio now also supports data plane extensions written in WebAssembly (Wasm). These extensions can modify requests and responses and perform out-of-band actions, such as authentication and authorization.
- Standardisations like the Service Mesh Interface (SMI) can add a lot of value, but the user requirements, common use cases, and the core abstractions of the underlying technology must be well understood.
- Multi-cluster and mesh expansion (out-of-cluster) support is continually improving in Istio and many other service mesh implementations.
5/31/2020 • 36 minutes, 43 seconds
Sam Newman: Monolith to Microservices
Today on the InfoQ Podcast, Wes Reisz talks with one of the thought leaders in Microservices, CI/CD, and Cloud -- Sam Newman. The podcast covers many of the topics, techniques, and patterns that Sam writes about in his latest book, Monolith to Microservices: Evolutionary Patterns to Transform Your Monolith. Topics covered in the podcast include understanding the problem you’re trying to solve, organizational/people changes when it comes to microservice architectures, database strategies for decomposing monolithic datastores, and why we’re seeing projects reverting from microservices to monoliths.
Why listen to this podcast:
- Fundamentally, microservices are distributed systems. Distributed systems have baggage (complexity) that comes along with them. The best way to deal with this complexity is not to address it. Try to solve the problem in other ways before choosing to take an organization to microservices.
- A common issue that large enterprises run into that might be a strong indicator for implementing microservices occurs when lots of developers are working on a given problem and they’re getting in each other’s way.
- A useful structure to follow with microservices is to make sure each service is owned by exactly one team. One team can own more than one service but having clear ownership of who owns a service helps in some of the operational challenges with microservices.
- A release train should be a stop in the journey towards continuous delivery. It’s not the destination. If you find that you can only release in a release train, you are likely building a distributed monolith.
- There are challenges of operating microservices when the end customer has to operate and manage it. These challenges are part of why we’re seeing projects move from microservices to process monoliths.
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5/25/2020 • 43 minutes, 30 seconds
Tracy Miranda on the Continuous Delivery Foundation, Interoperability, and Open Standards
In this podcast, Tracy Miranda sat down with InfoQ podcast co-host Daniel Bryant. Miranda, Director of Open Source Community at CloudBees, and board chair at the Continuous Delivery Foundation (CDF), discussed topics that included: the aims of the CDF and an outline of the current hosted projects, the need for open standards and interoperability in the CD space, and the benefits offered by progressive delivery and software supply chain management.
Why listen to this podcast:
- The Continuous Delivery Foundation (CDF) serves as the vendor-neutral home of many projects within continuous delivery space, including: Jenkins, Jenkins X, Spinnaker, Tekton, and Screwdriver.cd
- Jenkins X is a Kubernetes-native continuous delivery solution for cloud applications. This project uses a completely new architecture and code base in comparison with the original Jenkins project.
- Spinnaker is an open source, multi-cloud continuous delivery platform. The Tekton Pipelines project provides Kubernetes-style custom resources for declaring continuous integration and delivery pipelines. Spinnaker can use Tekton as its pipeline engine.
- In addition to providing a neutral home for projects within the CD space, the CDF is also aiming to help define appropriate terminology, open standards, and abstractions. This will assist with interoperability between CD components, and also promote innovation in the areas that can provide the most value.
- The CDF is also aiming to facilitate software testing, progressive delivery, and software supply chain management. Wide ranging topics such as observability and security are important will play an important role here.
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5/15/2020 • 24 minutes, 4 seconds
Marty Abbott and Tanya Cordrey on Microservices, Availability, and Managing Risk
In this podcast, Marty Abbott and Tanya Cordrey sat down with InfoQ podcast co-host Daniel Bryant. Abbott, CEO and co-founder of AKF Partners, and Cordrey, partner at AKF Partners, discussed topics that included: their learning from working together in the early days of eBay, why and how to avoid creating software systems that are composed of deep call chains of microservices, and how to build effective product teams.
Why listen to this podcast:
- First introduced in the book “The Art of Scalability”, the AKF Scale Cube is a model for segmenting software components, defining microservices, and scaling products. It also creates a common language for teams to discuss scale related options in designing solutions.
- The microservice architectural pattern is best used for implementing the “breadth” of business functionality. Engineers should avoid building deep call chains of services, as this can increase the probability of failure, and can also increase the challenges of locating and diagnosing issues. Code libraries can often be used more effectively to implement “depth” within services.
- The AKF Availability Cube is a new model to guide discussions on how to achieve high availability. This model can also be used as a mathematical tool to evaluate the theoretical “as designed” availability of existing systems.
- Building products using cross-functional teams is an effective approach. However, care should be taken not to accidentally create unnecessarily large teams, as this can add communication and coordination friction to the delivery process.
- Teams should make a conscious choice to adopt new technologies, and understand the benefits and tradeoffs with doing so. Managing risk, and in particular, technology lifespan risk, is an important part of the value engineers provide to the business.
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5/8/2020 • 36 minutes, 31 seconds
Dave Sudia on Migrating From a PaaS to a Kubernetes-Based Platform
In this podcast, Daniel Bryant sat down with Dave Sudia, senior DevOps engineer at GoSpotCheck. Topics discussed included: the benefits of PaaS; building a platform with Kubernetes as the foundation; selecting open source components and open standards in order to facilitate the evolution of a platform; and why care should be taken to prioritize the developer experience and create self-service operation of the platform.
Why listen to this podcast:
- When starting a business and searching for product-market fit, creating an application using a monolithic code base deployed onto a commercial Platform as a Service (PaaS) product is a very effective way of iterating fast and minimising operational costs.
- There may come a point where the PaaS cannot provide bespoke requirements, or it has trouble scaling, or the costs become prohibitive. At this point many teams choose to build a custom platform using cloud technologies, such as Kubernetes.
- Building a Kubernetes platform can be an effective solution, but appropriate effort needs to be put into designing, building, and maintaining the platform. The platform effectively becomes another product within the business that must be managed accordingly.
- Embracing open standards provides many benefits, especially for the long term. Implementations that are consumed through well-defined interfaces and abstraction can be more readily swapped at a later point in time. It is also generally easier to integrate components that share common interfaces.
- Attention and resources must be provided to create an effective developer experience for the platform. It is essential to prioritize self-service operations, and also to understand the core requirements of the engineers and QA specialists that will be using the platform during their daily work.
- Establishing an effective continuous delivery pipeline can enable more repeatable and scalable testing of applications, and also allows the codification of cross-functional requirements.
- The cloud native landscape has now evolved to a point where most of the frameworks and tooling required to build a platform have become viable for general purpose usage. However, some assembly may still be required, and engineers should be prepared for change, as the ecosystem moves fast.
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4/17/2020 • 30 minutes, 40 seconds
Peter Bourgon on CRDTs and State at the Edge
Today on The InfoQ Podcast, Wes Reisz talks with Peter Bourgon. Peter is a distributed system engineer working on Fastly. His area of interest is around coordination free replicated systems. The two engineers talk about the space of Conflict-Free Replicated Data Types (CRDTs) specifically in the context of edge compute. Topics covered on the podcast include Edge compute, CRDTs, CAP Theorem, and challenges around building distributed systems.
Why listen to this podcast:
- CRDTs (conflict-free replicated data types) are a class of coordination free replication systems (or systems that don’t require strategies such as leader election).
- An easy way to think of a CRDT is as an associative, commutative, and idempotent data structure plus the operations needed to use it.
The edge is an overloaded term that people tend to define based on where they sit on a spectrum between the customer and the data center. Fastly’s edge is away from the data center and but not to the telephone pole or handset.
- RAFT and Gossip are two alternative approaches to using a coordination free replication system like CRDTs.
To get the properties of a CRDT and have useful data types, you have to pay a cost in size and often bytes on the wire. These are challenges that continue to need solutions.
- Modern Distributed systems and data structures like CRDTs require you to start thinking about state in the system itself. It’s not unusual for a system today to give you multiple results back that the system will have to handle or merge.
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4/3/2020 • 37 minutes, 1 second
Joe Duffy on Infrastructure as Code, Pulumi, and Multi-Cloud
In this podcast, Daniel Bryant sat down with Joe Duffy, founder and CEO at Pulumi, and discussed several infrastructure-themed topics: the evolution of infrastructure as code (IaC), the way in which the open source Pulumi framework allows engineers to write IaC using general purpose programming languages such as JavaScript and Go, and the future of multi-cloud environments.
Why listen to this podcast:
● Infrastructure as Code (IaC) enables engineers to programmatically define the configuration and provisioning of computing infrastructure, on-premises hardware, and cloud services.
● Traditional IaC tools were often imperative, requiring engineers to define and enumerate the necessary steps and SDK calls in order to configure the underlying infrastructure.
● Modern IaC tools like HashiCorp’s Terraform, AWS CloudFormation and other related cloud vendor tooling enable engineers to write declarative code to define a required state of the infrastructure. The tools parse the declarative configuration and take appropriate action to enact the specified state, for example, calling SDKs and APIs, verifying results, iterating etc.
● Pulumi is an open source framework that enables engineers to define IaC using general purpose programming languages, such as Node, Python, .NET Core, and Go.
● Pulumi allows imperative specification of IaC. Engineers can use their favourite language-specific features, idioms, and patterns. The use of language modules, packages, and libraries can also enable code reuse.
● Under the hood, Pulumi transforms code written in the supported languages to a declarative specification model. This model is then used to enact the required infrastructure state.
● Frameworks like Pulumi enable engineers to deploy and configure infrastructure across multiple cloud vendors and services (including Kubernetes clusters).
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3/27/2020 • 27 minutes, 58 seconds
Dylan Schiemann on the Evolution of Dojo, Web Components and Trends in the Web Development Landscape
In this podcast Charles Humble spoke to Dylan Schiemann, co-creator of Dojo and InfoQ’s JavaScript and Web Development lead editor, about the history and current state of Dojo, and key emerging trends in the JavaScript landscape today. Key topics include Dojo’s adoption of Typescript, web components, and client-side libraries such as Svelte and Stencil.
Why listen to this podcast:
- Modern Dojo (2.0 and upwards) is focussed on being a very small, opinionated reactive framework, but with a lot of the components you need to build a modern JavaScript application built in.
- The framework tries to align closely to standards, for example using Web Components extensively for UI components, alongside ES modules and promises. The use of standards, as well as the convergence towards the reactive programming model for web UI, has improved interoperability, though there are some limitations such as the lack of an easy way to share resources across web components.
- Dojo was one of the first frameworks to make the decision to switch to Typescript, though it took some time to make that transition. The switch was mainly motivated by TypeScript’s support for interfaces, but it wasn’t until Typescript 2.6 they felt able to ship Dojo 2.
- On the client side we’re paying close attention to Svelte and Stencil as two particularly interesting client-side frameworks.
- We’ve moved Web Components from early adopter to early majority on the trend report, based on the fact that all browsers accept IE now natively support it, but also large companies such as Apple, Nike and ESPN are deploying web components and their sites. Apple’s iTunes implementation, for example, now uses web components.
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3/20/2020 • 32 minutes, 35 seconds
Gareth Rushgrove on Kubernetes as a Platform, Applications, and Security
In this podcast, Daniel Bryant sat down with Gareth Rushgrove, Director of Product Management at Snyk. Topics covered included Kubernetes as a platform, application abstractions, continuous delivery, and implementing good security practices in the cloud native space.
Why listen to this podcast:
- The value provided by Kubernetes depends on an organisation’s context. Kubernetes acts as both a series of lower-level building blocks for a platform, and also as a very powerful API for deploying and operating container-based applications.
- Kubernetes provides several useful abstractions for engineers. For example, Pods, Deployments, and Services. However, Kubernetes doesn’t have an “application”-focused abstraction. Tools such as Helm and specifications like the Cloud Native Application Bundle (CNAB) are driving innovation in this space.
- There is a large amount of open source Kubernetes tooling. This has been created by a range of vendors, groups, and individuals. Encouraging this diverse mix of participation is beneficial for the long-term health of the ecosystem.
- The Cloud Native Computing Foundation (CNCF) provides a space for people to collaborate regardless of their current organisational affiliations.
- Defining appropriate standards within the cloud native space is useful for enabling interoperability and providing common foundations for others to innovate on top of.
- Security challenges within IT are socio-technical. Security teams working with cloud native technologies will benefit from continual learning, developing new skills, and researching new tools. For example, the defaults of Kubernetes aren’t necessarily secure, but this can be readily addressed with appropriate configuration.
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3/13/2020 • 30 minutes, 58 seconds
Luca Mezzalira on Micro Frontends at DAZN
- A Micro frontends is an approach to developing frontends that attempts to take some of the same benefits from Microservices and apply them to frontend development.
- Microfront ends can be developed with different technologies and ownership of components on a single view. However, DAZN took a vertical approach to build them. Each Micro frontend is loaded into an app shell that offers an API for crosscutting concerns. Only one Micro frontend is loaded at a time into the app shell.
- The ‘Inverse Conway Maneuver’ recommends evolving your team and organizational structure to create the architecture you want.
- DAZN derisks deployments by using canaries implemented with Lambda at the Edge on Cloudfront. For code deployments, each of the Micro frontends can be introduced with a limited scope and then expanded once proven stable.
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3/9/2020 • 34 minutes, 43 seconds
Zhamak Dehghani on Data Mesh, Domain-Oriented Data, and Building Data Platforms
In this podcast, Daniel Bryant sat down with Zhamak Dehghani, principal consultant, member of technical advisory board, and portfolio director at ThoughtWorks. Topics discussed included: the motivations for becoming a data-driven organization; the challenges of adapting legacy data platforms and ETL jobs; and how to design and build the next generation of data platforms using ideas from domain-driven design and product thinking, and modern platform principles such as self-service workflows.
Why listen to this podcast:
- Becoming a data-driven organization remains one of the top strategic goals of many organizations. Being able to rapidly run experiments and efficiently analyse the resulting data can provide a competitive advantage.
- There are several “architecture failure modes” within existing enterprise data platforms. They are centralized and monolithic. The composition of data pipelines are often highly-coupled, meaning that a change to the data format will require a cascade of changes throughout the pipeline. And finally, the ownership of data platforms is often siloed and hyper-specialized.
- The next generation of enterprise data platform architecture requires a paradigm shift towards ubiquitous data with a distributed data mesh.
Instead of flowing the data from domains into a centrally owned data lake or platform, domains need to host and serve their domain datasets in an easily consumable way.
- Domain data teams must apply product thinking to the datasets that they provide; considering their data assets as their products, and the rest of the organization's data scientists, ML and data engineers as their customers.
The key to building the data infrastructure as a platform is (a) to not include any domain specific concepts or business logic, keeping it domain agnostic, and (b) make sure the platform hides all the underlying complexity and provides the data infrastructure components in a self-service manner.
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3/2/2020 • 33 minutes, 46 seconds
Brittany Postnikoff on Security, Privacy, and Social Engineering with Robots
In this podcast, Daniel Bryant sat down with Brittany Postnikoff, a computer systems analyst specialising on the topics of robotics, embedded systems, and human-robot interaction. Topics discussed included: the rise of robotics and human-robot interaction within modern life, the security and privacy risks of robots used within this context, and the potential for robots to be used to socially engineer people.
Why listen to this podcast:
- Physical robots are becoming increasingly common in everyday life, for example, offering directions in airports, cleaning the floor in peoples’ homes, and acting as toys for children.
- People often imbue these robots with human qualities, and they trust the authority granted to a robot.
- Social engineering can involve the psychological manipulation of people into performing actions or divulging confidential information. This can be stereotyped by the traditional “con”.
- As people are interacting with robots in a more human-like way, this can mean that robots can be used for social engineering.
- A key takeaway for creators of robots and the associated software is the need to develop a deeper awareness of security and privacy issues.
- Software included within robots should be patched to the latest version, and any data that is being stored or transmitted should be encrypted.
- Creators should also take care when thinking about the human-robot UX, and explore the potential for unintended consequences if the robot is co-opted into doing bad things.
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2/21/2020 • 22 minutes, 36 seconds
Anurag Goel on Cloud Native Platforms, Developer Experience, and Scaling Kubernetes
In this podcast, Daniel Bryant sat down with Anurag Goel, Founder and CEO of Render. Topics covered included: the evolution of cloud platforms; simplifying developer experience; running large-scale workloads on Kubernetes; and the future of tooling and platforms within the cloud native computing space.
Why listen to this podcast:
- Render is aiming to be the next generation of cloud provider. Developers deploy and manage applications via a Platform-as-a-Service (PaaS) -like experience using custom simplified YAML configuration.
- Render is built on top of Kubernetes, but the internals and configuration of this orchestration framework is not exposed to end user developers.
- Many large scale usages of traditional cloud vendor platforms require the formation of specialised in-house “DevOps” teams. The provision of virtualisation and API-driven operation via the cloud providers was revolutionary, but it didn’t fundamentally change the existing platform paradigm.
- Arguably platform usability may have taken a step back with the arrival of public cloud vendor platforms. For example, developers may just want to write code, and not have to write complicated deployment descriptors. Operations team may want to focus on supporting engineers and advising on performance and scale, rather maintaining cloud provisioning scripts.
- The Render team are planning to run all future workloads of self-managed Kubernetes, rather than use a hosted offering, due to them experiencing implementation bugs when running their clusters at medium-to-large scale.
- The Cloud Native Computing Foundation (CNCF) is encouraging large amounts of innovation within the cloud platform space. However, due to the Cambrian explosion of the Cloud Native Landscape over the past several years, there must surely be consolidation of tools, platforms, and vendors in the near future.
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2/7/2020 • 27 minutes, 7 seconds
Greg Law on Debugging, Record & Replay of Data, and Hyper-Observability
In this podcast, Daniel Bryant sat down with Greg Law, CTO at Undo. Topics discussed included: the challenges with debugging modern software systems, the need for “hyper-observability” and the benefit of being able to record and replay exact application execution; and the challenges with implementing the capture of nondeterministic system data in Undo’s LiveRecorder product for JVM-based languages that are Just-In-Time (JIT) compiled.
Why listen to this podcast:
- Understanding modern software systems can be very challenging, especially when the system is not doing what is expected. When debugging an issue, being able to observe a system and look at logging output is valuable, but it doesn’t always provide all of the information a developer needs. Instead we may need “hyper observability”; the ability to “zoom into” bugs and replay an exact execution.
- Being able to record all nondeterministic stimuli to an application -- such as user input, network traffic, interprocess signals, and threading operations -- allows for the replay of an exact execution of an application for debugging purposes. Execution can be paused, rewound, and replayed, and additional logging data can be added ad hoc.
- Undo’s LiveRecorder allows for the capture of this nondeterministic data, and this can be exported and shared among development teams. The UndoDB debugger, which is based on the GNU Project Debugger, supports the loading of this data and the execution and debugging in forwards and reverse execution of the application. There is also support for other debuggers, such as that included within IntelliJ IDEA.
- Advanced techniques like multi-process correlation reveal the order in which processes and threads alter data structures in shared memory, and thread fuzzing randomizes thread execution to reveal race conditions and other multi-threading defects.
- The challenges of using this type of technology when debugging (micro)service-based application lies within the user experience i.e. how should the multiple process debugging experience be presented to a developer?
Live Recorder currently supports C/C++, Go, Rust, Ada applications on Linux x86 and x86_64, with Java support available in alpha. Supporting the capture and replay of data associated with JVM language execution, which contain extra abstractions and are often Just-In-Time (JIT) compiled, presented extra challenges.
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1/31/2020 • 30 minutes, 46 seconds
Idit Levine Discussing Gloo, Service Mesh Interface, and Web Assembly Hub
Today on The InfoQ Podcast, Wes Reisz speaks with CEO and founder of Solo Idit Levine. The two discuss the Three Pillars of Solo around Gloo, their API gateway, interoperability of service meshes (including the work on Service Mesh Interface), and on extending Envoy with Web Assembly (and the recently announced Web Assembly Hub).
Why listen to this podcast:
- Gloo is a Kubernetes-native ingress controller and API gateway. It’s built on top of Envoy and at its core is open source.
- The Service Mesh Interface (SMI) is a specification for service meshes that runs on Kubernetes. It defines a common standard that can be implemented by a variety of providers. The idea of SMI is it’s an abstraction on top of service meshes, so that you can use one language to configure them all.
- Autopilot is an open-source Kubernetes operator that allows developers to extend a service mesh control plane.
- Lua has been commonly used to extend the service mesh data plane. Led by Google and the Envoy community, web assembly is becoming the preferred way of extending the data plane. Web assembly allows you to write Envoy extensions in any language while still being sandboxed and performant.
- WebAssembly Hub is a service for building, deploying, sharing, and discovering Wasm extensions for Envoy.
- Wasme is a docker like an open-source commandline tool from Solo to simplify the building, pushing, pulling, and deploying Envoy Web Assembly Filters.
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1/24/2020 • 38 minutes, 38 seconds
Gunnar Morling on Change Data Capture and Debezium
Today, on The InfoQ Podcast, Wes Reisz talks with Gunnar Morling. Gunnar is a software engineer at RedHat and leads the Debezium project. Debezium is an open-source distributed platform for change data capture (CDC). On the show, the two discuss the project and many of its use cases. Additionally, topics covered on the podcast include bootstrapping, configuration, challenges, debugging, and operational modes. The show wraps with long term strategic goals for the project.
Why listen to this podcast:
- CDC is a set of software design patterns used to react to changing data in a data store. Used for things like internal changelogs, integrations, replication, and event streaming, CDC can be implemented leveraging queries or against the DB transaction log. Debezium leverages the transaction log to implement CDC and is extremely performant.
- Debezium has mature source and sink connectors for MySQL, SQL Server, and MongoDB. In addition, there are Incumbating connectors for Cassandra, Oracle, and DB2. Community sink connectors have been created for ElasticSearch.
- In a standard deployment, Debezium leverages a Kafka cluster by deploying connectors into Kafka Connect. The connectors establish a connection to the source database and then write changes to a Kafka topic.
- Debezium can be run in embedded mode. Embedded mode imports Java library into your own project and leverages callbacks for change events. The library approach allows Debezium implementations against other tools like AWS Kinesis or Azure's Event Hub. Going forward, there are plans to make a ready-made Debezium runtime.
- Out of the box, Debezium has a one-to-one mapping between tables and Kafka topic queues. The default approach exposes the internal table structure to the outside. One approach to address exposing DB internals is to leverage the Outbox Pattern. The Outbox Pattern uses a separate outbox table as a source. Inserts into your normal business logic tables also make writes to the outbox. Change events are then published to Kafka from the outbox source table.
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1/17/2020 • 29 minutes, 15 seconds
Kelsey Hightower on Extending Kubernetes, Event-Driven Architecture, and Learning
In this podcast, Daniel Bryant sat down with Kelsey Hightower, Staff Developer Advocate at Google. Topics covered included: the extensibility of Kubernetes, and why it has become the platform that other platforms are being built on top of; creating event-driven architectures and deploying these onto Function-as-a-Service (FaaS) platforms like the Kubernetes-based Knative and Google Cloud Run; and the benefits of learning, sharing knowledge, and building communities.
Why listen to this podcast:
- Kubernetes is a platform for building platforms. It may not be as opinionated as traditional Platform-as-a-Service (PaaS) offerings, but it has become popular due to its extensibility. There are PaaS-like solutions built on top of Kubernetes, such as OpenShift, Knative, and Cloud Run.
- The creation of common interfaces within Kubernetes -- such as Custom Resource Definitions (CRDs), Container Networking Interface (CNI), and Container Runtime Interface (CRI) -- enabled the adoption of the platform by vendors and the open source community without everyone needing to agree on exactly how to implement extensions.
- Although not every workload can be effectively implemented using an event-driven architecture, for those that can the Kubernetes-based Function-as-a-Service (FaaS) platforms like Knative and Cloud Run can handle a lot of the operational management tasks for developers.
- Engineers may be able to get ~90% of the “service mesh” traffic management functionality they need from using a simple proxy.
However, the separation of the control and data planes within modern service meshes, in combination with the rise in popularity of the sidecar deployment model, has provided many benefits within Kubernetes.
- A lot of learning within software development and information technology is transferable. If you spend time going deep in a technology when you begin your career, much of what you learn will be useful when you come to learn the next technology.
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1/10/2020 • 26 minutes, 19 seconds
Katie Gamanji on Condé Nast’s Kubernetes Platform, Self-Service, and the Federation and Cluster APIs
In this podcast, Daniel Bryant sat down with Katie Gamanji, Cloud Platform Engineer at Condé Nast International. Topics covered included: exploring the architecture of the Condé Nast Kubernetes-based platform; the importance of enabling self-service deployment for developers; and how the Kubernetes’ Federation API and Cluster API may enable more opportunities for platform automation.
- Founded in the early 1900s, Condé Nast is a global media company that has recently migrated their application deployment platforms from individually-curated geographically-based platforms, to a standardised distributed platform based on Kubernetes and AWS.
- The Condé Nast engineering team create and manage their own Kubernetes clusters, currently using CoreOS’s/Red Hat’s Tectonic tool.
Self-service deployment of applications is managed via Helm Charts. - The platform team works closely with their “customer” developer teams in order to ensure their requirements are being met.
- The Kubernetes Federation API makes it easy to orchestrate the deployment of applications to multiple clusters. This works well for cookie-cutter style deployments that only require small configuration differences, such as scaling the number of running applications based on geographic traffic patterns.
- The Cluster API is a Kubernetes project to bring declarative APIs to cluster creation, configuration, and management. This enables more effective automation for cluster lifecycle management, and may provide more opportunities for multi-cloud Kubernetes use.
- The Condé Nast platform Kubernetes Ingress is handled by Traefik, due to the good Helm support and cloud integration (for example, AWS Route 53 and IAM rule synchronization). The platform team is exploring the use of service mesh for 2020.
- Abstractions, interfaces, and security will be interesting focal points for improvement in the Kubernetes ecosystem in 2020.
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1/3/2020 • 31 minutes, 16 seconds
Joseph Jacks on Commercial Open Source Software, RISC-V, and Disrupting the Application Layer
In this podcast, Daniel Bryant spoke to Joseph Jacks, Founder of OSS Capital and the Open Core Summit, and discussed topics including the open source and open core models, innovations within open source hardware and the RISC-V instruction set architecture, and current opportunities for disruption using commercial open source software.
Why listen to this podcast:
- Recently, open source software and the open core business model have driven a lot of innovation and created a lot of value, particularly within the cloud “as-a-service” space.
- There has been some disagreement between the open source and commercially-focused communities, for example, in relation to the licencing models and how value is captured.
- The Open Core Summit (OCS) is a new conference focusing on the intersection of commercialisation and open source software that aims to facilitate discussion in this space.
- Organisations building around open source software can potentially look at large cloud vendors as partners. Public clouds can provide effective distribution, and typically focus on offering breadth of services rather than the depth of expertise that can be provided by a specialist company.
- RISC-V is an open-source hardware instruction set architecture (ISA) based on the well-established reduced instruction set computer (RISC) principles. Leveraging RISC-V can reduce the time and cost of customising chip designs.
- A lot of recent open source innovation has focused on the infrastructure layer within computing systems. This means that the application layer is now potentially ripe for disruption via commercial open source software.
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12/27/2019 • 26 minutes, 28 seconds
The InfoQ Podcast Hosts Take a Look Back at 2019, Discussing Teal, Edge, Quantum Computing, and more
In this special year-end wrap-up podcast Wes Reisz, Shane Hastie, Daniel Bryant, and Charles Humble discuss what we’ve seen in 2019 and speculate a little on what we hope to see in 2020. Topics include business agility and Teal, what it means to be an ethical engineer, bringing your whole self to work, highlights from QCon and InfoQ during 2019, the rise of Python, and progress in quantum computing.
Why listen to this podcast:
* Business agility is one of the major themes that the InfoQ team has seen emerge this year, with stronger emphasis on outcomes over outputs. We’ve also seen a growing interest in ethics and the ethical implications of the work we all do.
* On the programming languages front the rise of Python continues, driven largely by its popularity in data science.
* As Kubernetes cements its dominant position we’re hoping to see a simplification of the workflows associated with it, as well as in areas like observability.
* There have been several big announcements in quantum computing in the past year, and this is an area we continue to watch with interest.
* Another key trend for next year is edge computing. The edge of the cloud infrastructure has an amazing amount of available compute resource, as does the device edge.
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12/16/2019 • 33 minutes, 27 seconds
Josh Wills on Building Resilient Data Engineering and Machine Learning Products at Slack
Josh Wills, a software engineer working on data engineering problems at Slack, discusses the Slack data architecture and how they build and observe their pipelines. Josh, along with color commentary such as the move from IC to manager (and back), discusses recommendations, tips, tools, and lessons Slack engineering teams discovered while building products like Slack Search. The podcast covers machine learning, observability, data engineering, and general practices for building highly resilient software.
Why listen to this podcast:
- Slack has a philosophy of building only what they need. They have a don’t reinvent the wheel mindset.
- Slack was originally a PHP monolith. Today, it is largely Hack-lang, HHVM, and several Java and Go binarys. On the data side, application logs are in Thrift (there is a plan to migrate to protobuf). Events are processed through a Kafka cluster that handles 100,000s of events per second. Everything is kept in S3 with a large Hive metastore. EMR is spun up on demand. Presto, Airflow, Slack, Snowflake (business analytics), Quiver (key value store) are all used.
- ML worked best for Slack when it was used to help people answer questions. Things like Learn to Rank (LTR) become the most effective use of ML for Slack.
- You can get pretty far with rules. Use machine learning when that’s all that’s left.
- When you start applying observability to your data pipeline, a key lesson for Slack was to really focus on structured data, tracing, high cardinality events. This let them really use the tools they were already familiar with (ELK, Prometheus, Grafana) and go deep into understanding what’s happening in the systems.
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12/9/2019 • 30 minutes, 32 seconds
Bryan Liles on Making Kubernetes Easier for Developers, the CNCF, and “Serverless”
In this podcast, Daniel Bryant sat down with Bryan Liles, senior staff engineer at VMware. Topics covered included: the challenges with deploying applications into Kubernetes, using the open source Octant tool to increase a user’s understanding of Kubernetes clusters, and how “serverless” technologies may influence the future approaches to building software.
Why listen to this podcast:
- Octant is a highly extensible platform for developers to better understand the complexity of Kubernetes clusters. Octant runs locally, using the local Kubernetes credentials. It currently displays information about a Kubernetes cluster and related applications as a web page. Soon this tool and resulting display will be provided as a standalone application.
- The goal of Octant is to enable users to discover what they need to discover. The tool aims to provide context relevant to where a user is and what they are trying to achieve. The Octant plugin system allows integration with other tooling, such as logging and metrics frameworks. This aims to facilitate quick problem detection and resolution.
- Cloud native platforms like Kubernetes are complicated, as there are lots of moving parts. The most important challenge to be tackled to increase the adoption of platforms like Kubernetes is “how do we move code from our IDEs to wherever it needs to run with the least amount of friction?”. Testing needs to be implicit, as does security verification, and the acts of deployment. Kubernetes needs its “Ruby on Rails” moment.
- Creating “serverless” systems is an interesting approach, but we may currently be using this technology in a non-optimal way. For example, creating web applications using this technology enables scalability, but can lead to the creation of difficult to understand systems that also require a lot of boilerplate configuration. Arguably, a more interesting use case is implementing large-scale batch processing using simple event-driven models.
- The Cloud Native Computing Foundation (CNCF) has created a series of communities of practice called Special Interest Groups (SIGs), such as SIG App Delivery. This allows folks with similar interests to work together as a community, focusing on solving a specific set of well-scoped problems. There are many ways to get involved, from discussions, to coding and creating documentation.
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11/15/2019 • 29 minutes, 38 seconds
Victor Dibia on TensorFlow.js and Building Machine Learning Models with JavaScript
Victor Dibia is a Research Engineer with Cloudera’s Fast Forward Labs. On today’s podcast, Wes and Victor talk about the realities of building machine learning in the browser. The two discuss the capabilities, limitations, process, and realities around using TensorFlow.js. The two wrap discussing techniques like Model distillation that may enable machine learning models to be deployed in smaller footprints like serverless.
- While there are limitations in running machine learning processes in a resource constrained environment like the browser, there are tools like TensorFlow.js that make it worthwhile. One powerful use case is the ability to protect the privacy of a user base while still making recommendations.
TensorFlow.js takes advantage of the WebGL library for its more computational intense operations.
- TensorFlow.js enables workflows for training and scoring models (doing inference) purely online, by importing a model built offline with more tradition Python tools, and a hybrid approach that builds offline and finetunes online.
To build an offline model, you can build a model with TensorFlow Python (perhaps using a GPU cluster). The model can be exported into the TensorFlow SaveModel Format (or the Keras Model Format) and then converted with TensorFlow.js into the TensorFlow Web Model Format. At that point, the can be directly imported into your JavaScript.
- TensorFlow Hub is a library for the publication, discovery, and consumption of reusable parts of machine learning models and was made available by the Google AI team. It can give developers a quick jumpstart into using trained models.
- Model compression promises to make models small enough to run in places we couldn’t run models before. Model distillation is a process where a smaller model is trained to replicate the behavior of a larger one. In one case, BERT (a library almost 500MB in size) was distilled to about 7MB (almost 60x compression).
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11/8/2019 • 28 minutes
Michelle Krejci on Moving to Microservices: Visualising Technical Debt, Kubernetes, and GraphQL
In this podcast, Daniel Bryant spoke to Michelle Krejci, service engineer lead at Pantheon, about the Drupal and Wordpress webops-based company’s move to a microservices architecture. Michelle is a well-known conference speaker in the space of technical leadership and continuous integration, and she shared her lessons learned over the past four years of the migration.
Why listen to this podcast:
- The backend for the Pantheon webops platform began as a Python-based monolith with a Cassandra data store. This architecture choice initially enabled rapid feature development as the company searched for product/market fit. However, as the company found success and began scaling their engineering teams, the ability to add new functionality rapidly to the monolith became challenging.
- Conceptual debt and technical debt greatly impact the ability to add new features to an application. Moving to microservices does not eliminate either of these forms of debt, but use of this architectural pattern can make it easier to identify and manage the debt, for example by creating well-defined APIs and boundaries between modules.
- Technical debt -- and the associated engineering toil -- is real debt, with a dollar value, and should be tracked and made visible to everyone.
Establishing “quick wins” during the early stages of the migration towards microservices was essential. Building new business-focused services using asynchronous “fire and forget” event-driven integrations with the monolith helped greatly with this goal.
- Using containers and Kubernetes provided the foundations for rapidly deploying, releasing, and rolling back new versions of a service. Running multiple Kubernetes namespaces also allowed engineers to clone the production namespace and environment (without data) and perform development and testing within an individually owned sandboxed namespace.
- Using the Apollo GraphQL platform allowed schema-first development. Frontend and backend teams collaborated on creating a GraphQL schema, and then individually built their respective services using this as a contract. Using GraphQL also allowed easy mocking during development. Creating backward compatible schema allowed the deployment and release of functionality to be decoupled.
11/1/2019 • 34 minutes, 5 seconds
Ryan Kitchens on Learning from Incidents at Netflix, the Role of SRE, and Sociotechnical Systems
In today’s podcast we sit down with Ryan Kitchens, a senior site reliability engineer and member of the CORE team at Netflix. This team is responsible for the entire lifecycle of incident management at Netflix, from incident response to memorialising an issue.
Why listen to this podcast:
- Top level metrics can be used as a proxy for user experience, and can be used to determine that issue should be alerted on an investigated. For example, at Netflix if the customer playback initiation “streams per second” metric declines rapidly, this may be an indication that something has broken.
- Focusing on how things go right can provide valuable insight into the resilience within your system e.g. what are people doing everyday that helps us overcome incidents. Finding sources of resilience is somewhat “the story of the incident you didn’t have”.
- When conducting an incident postmortem, simply reconstructing an incident is often not sufficient to determine what needs to be fixed; there is no root cause with complex socio-technical systems as found at Netflix and most modern web-based organisations. Instead, teams must dig a little deeper, and look for what went well, what contributed to the problem, and where are the recurring patterns.
- Resilience engineering is a multidisciplinary field that was established in the early 2000s, and the associated community that has emerged is both academic and deeply practical. Although much resilience engineering focuses on domains such as aviation, surgery and military agencies, there is much overlap with the domain of software engineering.
- Make sure that support staff within an organisation have a feedback loop into the product team, as these people providing support often know where all of the hidden problems are, the nuances of the systems, and the workarounds.
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10/4/2019 • 28 minutes, 54 seconds
Oliver Gould on the Three Pillars of Service Mesh, SMI, and Making Technology Bets
In this podcast we sit down with Oliver Gould, co-founder and CTO of Buoyant. Oliver has a strong background in networking, architecture and observability, and worked on solving associated technical challenges at both Yahoo! and Twitter. Oliver is a regular presenter at cloud and infrastructure conferences, and alongside his co-founder William Morgan, you can often find them in the hallway track, waxing lyrical about service mesh -- a term they practically coined -- and trying to bring others along on the journey.
Service mesh technology is still young, and the ecosystem is still very much a work in progress, but there have been several recent interesting developments within this space. One of these was the announcement of the service mesh interface (SMI) at the recent KubeCon EU in Barcelona. The SMI spec seeks to unlock service mesh integrators and implementers, as this can provide an abstraction that removes the need to bet on any single service mesh implementation. This can be good for both tool makers and enterprise early adopters. Many organisations like Microsoft and HashiCorp are involved with working alongside the community to help define the SMI, including Buoyant.
In this podcast we summarise the evolution of the service mesh concept, with a focus on the three pillars: visibility, security, and reliability. We explore the new traffic “tap” feature within Linkerd that allows near real time in-situ querying of metrics, and discuss how to implement network security by leveraging the primitives like Service Account provided by Kubernetes. We also discuss how reliability features, such as retries, time outs, and circuit-breakers are becoming table stakes for infrastructure platforms.
We also cover the evolution of the service mesh interface, explore how service meses may impact development and platforms in the future, and briefly discuss some of the benefits offered by the Rust language in relation to building a data plane for Linkerd. We conclude the podcast with a discussion of the importance of community building.
Why listen to this podcast:
- A well-implemented service mesh can make a distributed software system more observable. Linkerd 2.0 supports both the emitting of mesh telemetry for offline analysis, and also the ability to “tap” communications and make queries dynamically against the data. The Linkerd UI currently makes use the tap functionality.
- Linkerd aims to make the implementation of secure service-to-service communication easy, and it does this by leveraging existing Kubernetes primitives. For example, Service Accounts are used to bootstrap the notion of identity, which in turn is used as a basis for Linkerd’s mTLS implementation.
- Offering reliability is “table stakes” for any service mesh. A service mesh should make it easy for platform owners to offer fundamental service-to-service communication reliability to application owners.
- The future of software development platforms may move (back) to more PaaS-like offerings. Kubernetes-based function as a service (FaaS) frameworks like OpenFaaS and Knative are providing interesting features in this space. A service mesh may provide some of the glue for this type of platform.
- Working on the service mesh interface (SMI) specification allowed the Buoyant team to sit down with other community members like HashiCorp and Microsoft, and share ideas and identify commonality between existing service mesh implementations.
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9/20/2019 • 25 minutes, 8 seconds
Event Sourcing: Bernd Rücker on Architecting for Scale
Today on the podcast, Bernd Rucker of Camunda talks about event sourcing. In particular, Wes and Bernd discuss thoughts around scalability, events, commands, consensus, and the orchestration engines Camunda implemented. This podcast is a primer on considerations between an RDBMS and event-driven systems.
Why listen to this podcast:
- An event-driven system is a more modern approach to building highly scalable systems.
- An RDBMS system can limit throughput in scalability. Camunda was able to achieve higher levels of scale by implementing an event-driven system.
- Command and events are often confused. Commands are actions that request something to happen. Events describe something that happened. Confusing the two causes confusion in application development of event-driven systems.
9/13/2019 • 25 minutes, 7 seconds
Pat Kua on Technical Leadership, Cultivating Culture, and Career Growth
In this podcast we discuss a holistic approach to technical leadership, and Pat provides guidance on everything from defining target operating models, cultivating culture, and supporting people in developing the career they would like. There are a bunch of great stories, several book recommendations, and additional resources to follow up on.
* Cultivating organisational culture is much like gardening: you can’t force things, but you can set the right conditions for growth. The most effective strategy is to communicate the vision and goals, lead the people, and manage the systems and organisational structure.
* N26, a challenger bank based in Berlin has experienced hypergrowth over the past two years. Both the number of customers and the amount of employees have increased over threefold. This provides lots of opportunities for ownership of product and projects, and it creates unique leadership challenges.
* A target operating model (TOM) is a blueprint of a firm's business vision that aligns operating capacities and strategic objectives and provides an overview of the core business capabilities, internal factors, and external drivers, strategic and operational levers. This should be shared widely within an organisation
* Pat has curated a “trident operating” model for employee growth. In addition to the class individual contributor (IC) and management tracks, he believes that a third “technical leadership” track provides many benefits.
* People can switch between these tracks as their personal goals change. However, this switch can be challenging, and an organisation must support any transition with effective training.
* Pat recommends the following books for engineers looking to make the transition to leadership: The Manager’s Path, by Camille Fournier; Resilient Management, by Lara Hogan; Elegant Puzzle, by Will Larson; and Leading Snowflakes by Oren Ellenbogen. Pat has also written his own book, Talking with Tech Leads.
* It is valuable to define organisation values upfront. However, these can differ from actual culture, which more about what behaviours you allow, encourage, and stop.
* Much like the values provided by Netflix’s Freedom and Responsibility model, Pat argues that balancing autonomy and alignment within an organisation is vital for success. Managers can help their team by clearly defining boundaries for autonomy and responsibility.
* Developing the skills to influence people is very valuable for leaders. Influence is based on trust, and this must be constantly cultivated. Trust is much like a bank account, if you don’t regular deposit actions to build trust, you may find yourself going overdrawn when making a deposit. This can lead to bad will and defensive strategies being employed.
9/6/2019 • 26 minutes, 34 seconds
Thomas Graf on Cilium, the 1.6 Release, eBPF Security, & the Road Ahead
Cilium is open source software for transparently securing the network connectivity between application services deployed using Linux container management platforms like Docker and Kubernetes. It is a CNI plugin that offers layer 7 features typically seen with a service mesh. On this week’s podcast, Thomas Graf (one of the maintainers of Cilium and co-founder of Isovalent) discusses the recent 1.6 release, some of the security questions/concerns around eBPF, and the future roadmap for the project.
Why listen to this podcast:
* Cilium brings eBPF to the Cloud Native World. It works across both layer 4 and a layer 7. While it started as a pure eBPF plugin, they discovered that just caring about ports was not enough from a security perspective.
* Cilium went 1.0 about a year and a half ago. 1.6 is the most featured-packed release of Cilium yet. Today, it has around 100 contributors.
* While Cilium can make it much easier to manage IPTables, Cilium overlaps with a service mesh in that it can do things like understand application protocols, HTTP routes, or even restrict access to specific tables in data stores.
* Cilium provides both in kernel and sidecar deployments. For sidecar deployments, it can work with Envoy to switch between kernel space and userspace code. The focus is on flexibility, performance, and low overhead.
* BPF (Berkeley Packet Filter) was initial designed to do filtering on data links. eBPF has the same roots but it’s now used for system call filtering, tracing, sandbox, etc. It’s grown to be a general-purpose programming language to extend the Linux kernel.
* Cilium has a multi-cluster feature built-in. The 1.6 release can run in a kube-proxy free configuration. It allows fine-grain network policies to run across multiple clusters without the use of IPTables.
* Cilium offers on-the-wire encryption using in-kernel encryption technology that enables mTLS across all traffic in your service fleet. The encryption is completely transparent to the application.
* eBPF has been used in all production environments at Facebook since May 2017. It’s been used at places like Netflix, Google, and Reddit. There are a lot of companies who have an interest in eBPF being secure and production-ready, so there’s a lot of attention focused on fixing and resolving and security issues that arise.
* 1.6 also released KVstore-free operation, socket-based load balancing, CNI chaining, Native AWS ENI mode, enhancements to transparent encryption, and more.
* The plans for 1.17 is to keep raising up the stack into the socket level (to offer things like load balancing and transparent encryption at scale) and likely offering deeper security features such as process-aware security policies for internal pod traffic.
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9/2/2019 • 27 minutes, 5 seconds
Yuri Shkuro on Tracing Distributed Systems Using Jaeger
The three pillars of observability are logs, metrics, and tracing. Most teams are able to handle logs and metrics, while proper tracing can still be a challenge. On this podcast, we talk with Yuri Shkuro, the creator of Jaeger, author of the book Mastering Distributed Tracing, and a software engineer at Uber, about how the Jaeger tracing backend implements the OpenTracing API to handle distributed tracing.
Why listen to the podcast:
- Jaeger is an open-source tracing backend, developed at Uber. It also has a collection of libraries that implement the OpenTracing API.
- At a high level, Jaeger is very similar to Zipkin, but Jaeger has features not available in Zipkin, including adaptive sampling and advanced visualization tools in the UI.
- Tracing is less expensive than logging because data is sampled. It also gives you a complete view of the system. You can see a macro view of the transaction, and how it interacted with dozens of microservices, while still being able to drill down into the details of one service.
- If you have only a handful of services, you can probably get away with logging and metrics, but once the complexity increases to dozens, hundreds, or thousands of microservices, you must have tracing.
- Tracing does not work with a black box approach to the application. You can't simply use a service mesh then add a tracing framework. You need correlation between a single request and all the subsequent requests that it generates. A service mesh still relies on the underlying components handling that correlation.
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8/28/2019 • 32 minutes, 14 seconds
Louise Poubel on the Robotic Operating System
ROS is the Robotic Operating System. It’s been used by thousands of developers to prototype and create a robotic application. ROS can be found on robotics in warehouses, self-driving car companies, and on the International Space Station. Louise Poubel is an engineer working with Open Robotics. Today on the podcast, she talks about what it takes to develop software that moves in physical space, including the Sense, Think, Act Cycle, the developer experience, and architecture of ROS.
Why listen to this podcast:
- Writing code for robot development, you use the Sense, Think, Act Cycle.
- ROS is an SDK for robotics. It provides a communication layer that enables data to flow between nodes that handle sensors, logic, and actuation.
- ROS has two versions and has been around for twelve years. ROS 1 was entirely implemented in C. ROS 2 offers is a common C layer with implementations in many different languages, including Java, JavaScript, and Rust.
- Released on a six-month cadence, Dashing was the latest release (May 2019). Previous releases were supported for one year, Dashing is the first LTS and will be supported for two years.
- ROS 2 builds on top of the standard Data Distribution Service (DDS) that you find in mission-critical systems like nuclear power and airplanes.
- Simulation is an important step in robotics. It allows you to prototype a system before deploying to a physical system.
- Rviz is a three-dimensional visualizer used to visualize robots, the environments they work in, and sensor data. It is a highly configurable tool, with many different types of visualizations and plugins. It allows you to put together all your data in one place and see it.
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8/19/2019 • 28 minutes, 41 seconds
Matt Klein on Envoy Mobile, Platform Complexity, and a Universal Data Plane API for Proxies
In this podcast we sit down with Matt Klein, software plumber at Lyft and creator of Envoy, and discuss topics including the continued evolution of the popular proxy, the strength of the open source Envoy community, and the value of creating and implementing standards throughout the technology stack. We also explore the larger topic of cloud natives platforms, and discuss the tradeoffs between using a simple and opinionated platform against something that is bespoke and more configurable, but also more complex. Related to this, Matt shares his thoughts on when and how to make the decision within an organisation to embrace technology like container orchestration and service meshes.
Finally, we explore the creation of the new Envoy Mobile project. The goal of this project is to expand the capabilities provided by Envoy all the way out to mobile devices powered by Android and iOS. For example, most current user-focused traffic shifting that is conducted at the edge is implemented with coarse-grained approaches via by BGP and DNS, and using something like Envoy within mobile app networking stacks should allow finer-grained control.
Why listen to this podcast:
- The Envoy Proxy community has grown from strength-to-strength over the last year, from the inaugural EnvoyCon that ran alongside KubeCon NA 2018, to the increasing number of code contributions from engineers working across the industry
- Attempting to create a community-driven “universal proxy data plane” with clearly defined APIs, like Envoy’s XDS API, has allowed vendors to collaborate on a shared abstraction while still allowing room for “differentiated success” to be built on top of this standard
Google’s gRPC framework is adopting the Envoy XDS APIs, as this will allow both Envoy and gRPC instances to be operated via a single control plane, for example, Google Cloud Platform’s Traffic Director service.
- There is a tendency within the software development industry to fetishise architectures that are designed and implemented by the unicorn tech companies, but not every organisation operates at this scale.
- However, there has also been industry pushback against the complexity that modern platform components like container orchestration and service meshes can introduce to a technology stack. - Using a platform within these components provides the best return on investment when an organisation’s software architecture and development teams have reached a certain size.
- Function-as-a-Service (Faas)-type platforms will most likely be how engineers will interact with software in the future. Business-focused developers often do not want to interact with the platform plumbing
Envoy Mobile is building on prior art, and aims to expand the capabilities provided by Envoy all the way out to mobile devices using Android and iOS. Most current end user traffic shifting is implemented with coarse-grained approaches via BGP and DNS, and using something like Envoy instead will allow finer-grained control.
- Using Envoy Mobile in combination with Protocol Buffers 3, which supports annotations on APIs, can facilitate working with APIs offline, configuring caching, and handling poor networking conditions. One of the motivations for this work is that small increases in application response times can lead to better business outcomes.
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8/9/2019 • 41 minutes, 24 seconds
Armon Dadgar on HashiCorp Research, the Evolution of Infrastructure Tooling, and Standardisation
On this podcast, we’re talking to Armon Dadgar, co-founder and CTO of HashiCorp. Alongside Mitchell Hashimoto, Armon founded HashiCorp over six years ago, and the company has gone from strength to strength, with their open source infrastructure product suite now consisting of Consul, Nomad, Vault and Terraform.
We discuss the formation of the HashiCorp research division, and explore some of the computer science research underpinning Consul and Nomad. We also cover the challenges of supporting teams when they are looking to embrace new modes of working with dynamic infrastructure, and Armon introduces the new learn.hashicorp.com educational website and accompanying community and support forums.
Why listen to this podcast:
- There is a lot of fundamental computer science research that underpins the HashiCorp infrastructure workflow and configuration tooling. This helps to ensure that these mission-critical tools perform as expected, and enables sound reasoning about scaling these technologies.
- The HashiCorp founders recognised the value of creating an industrial research-focused department within the company even when there were only 30 staff.
- The Consul service mesh and distributed key value store leverages consensus and gossip algorithms from computer science research, Raft and SWIM, respectively. The HashiCorp team contributed a novel research-based improvement to SWIM -- Lifeguard: SWIM-ing with Situational Awareness -- that was presented at the DSN academic conference
- Initially HashiCorp produced a new tool every 6-12 months, focusing on filling gaps within the infrastructure workflow tooling market. Now the focus is on refining the operator/user experience of the existing tools, creating more integrations with other platforms and tooling, and facilitating engineering teams adopting these tools, via the creation of educational resources and community forums.
- Standardisation within computing technology can offer many benefits, especially where interoperability is required or technology switching costs are high. Care must be taken to ensure the correct interfaces are created, and that the time is right to create appropriate abstractions.
- The HashiCorp team are focusing on "marching up the stack", with the goal that a lot of the underlying "plumbing" should be hidden from, or easily configurable by, application developers. This will allow developers to focus on adding value related to their business or organisation, rather than getting stuck with managing infrastructure.
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8/2/2019 • 22 minutes, 35 seconds
Kingsley Davies and Cat Swetel at QCon London about Ethics and Requisite Variety
In this episode recorded at QCon London 2019 Shane Hastie, Lead Editor for Culture & Methods, first spoke to Kingsley Davies about ethics and then with Cat Swetel about requisite variety and being mindful of the impact our decisions have for the future.
Why listen to this podcast:
• The need to explore the application of technology for good
• The need for ethical standards in the technology industry
• Data is the new oil and it is frequently used in ways that are not in the best interest of society
• Other engineering professions have codes of conduct and ethical frameworks that are mandated as part of the education process, software engineering currently has very little
• Ashby’s law of requisite variety – the more options that are available to a system, the more resilient the system is applies to all aspects of our socio-technical systems
• We exist in the realm of ethics – we can’t just go to work and do what you’re told. Everything we do is a choice and our choices have a huge impact on the future
7/29/2019 • 31 minutes, 40 seconds
Thomas Wuerthinger on GraalVM and Optimizing Java With Ahead-of-Time Compilation
The promise of Java has always been, “write once, run anywhere.” This was enabled through just-in-time compilation, which allowed developers to target a platform at compilation. But, this flexibility has given rise to comments like, “Java is slow.” What if you could compile Java to Native Code? On this podcast, we’re talking to Thomas Wuerthinger, a senior research director at Oracle Labs. Leading programming language implementation teams for Java, JavaScript, Ruby, and R. He is the architect of the Graal compiler and the Truffle self-optimizing runtime.
Why listen to the podcast:
- The GraalVM project was initially just a replacement for the JVM C2 just-in-time compiler, but has evolved to include support for multiple languages, as well as an ahead-of-time compiling mode.
- Support for multiple languages can provide better performance for some languages, as well as making direct calls without inter-process communication.
- With GraalVM’s AOT compilation, you can statically link system libraries, which allows you to run a static binary on a bare-metal Docker image, without even a Linux distribution.
- The major benefits of AOT are minimized startup time, memory footprint, and packaging size. This can come with a trade-off in reduced maximum throughput and higher latency.
- The GraalVM roadmap includes supporting additional platforms, such as Windows and mobile, as well as performance improvements for both the JIT and AOT compilers.
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7/19/2019 • 25 minutes, 42 seconds
Johnny Xmas on Web Security & the Anatomy of a Hack
On this podcast, Wes talks to John Xmas. Johnny works for Kasada, a company that offers a security platform to help ensure only your users are logging into your web applications. Johnny is a well-known figure in the security space. The two discuss common attack vectors, the OWASP Top 10, and then walk through what hackers commonly do attempting to compromise a system. The show is full of advice on protecting your systems including topics around Defense in Depth, Time-Based Security, two-factor authentication, logging/alerting, security layers, and much more.
Why listen to this podcast:
- While there are sophisticated web attacks out there that use things like PhantomJS or Headless Chome, the vast majority of the web application attacks are the same unsophisticated scripted attacks that you always hear about. These are simple scripts using tools like curl and BurpSuite with Python or JavaScript. These simple scripts are still incredibly effective.
- OWASP Top 10 really hasn’t changed all that much in the last ten years. For example, despite being the number one approach used to educate defensive engineers on how to protect their apps, SQLI (SQL Injection) is still the most common attack. We continue to repeat the same mistakes that have exposed systems for a decade now.
- Phishing is by and far the quickest way to compromise a system. Defensive in Depth, security boundaries, limiting local admin rights are all things that corporations can implement to minimize the blast radius.
- Attackers have hundreds of gigs of actual username/password combinations that have been exposed from all the breaches over the past few years. These are often a first step when attempting to compromise a system. It’s more often likely that they will figure out a valid email pattern for a company and then feed actual names into that pattern to go after the username. From there, brute force attacks with those usernames against libraries of passwords is a common approach.
- A common approach is to go after an email login. While the email can be a treasure trove of information, it’s more about using those credentials in other places. It’s pretty common, for example, to use those credentials to get into a network with a VPN.
- Captcha/reCaptcha is not very effective and preventing these brute force attacks. There are a large number of bypasses and even Mechanical Turk companies that are available to bypass these tools. What can be effective is Time Based Security because it slows the attackers down. If you can slow them down, you can make the attack say long to succeed that they’ll go somewhere else.
- Once inside the network, most companies often have little security on internal systems. Multi-factor authentication, not just on the front door, but on internal systems is a huge step in the right direction. Monitoring not only for failed login attempts but, in some situations, valid login attempts (such as when a domain admin logs into a domain controller) should absolutely be used.
- When it comes to application security between services within a network, the best advice is to make sure developers really understand what is trying to be accomplished by something like JWT (JSON Web Tokens). Often its the lack of understanding of what they’re actually doing that leads to system vulnerabilities.
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6/17/2019 • 31 minutes, 55 seconds
Mike Milinkovich, Director of the Eclipse Foundation, Discusses the Journey to Jakarta EE 8
Today on the podcast, Wes talks with Mike Milinkovich, Executive Director of the Eclipse Foundation. The Eclipse Foundation was chosen to govern the evolution of Oracle’s Java EE to Jakarta EE. The two discuss the project, the recent news about issues with the javax namespace, the challenges around bundling a Java Runtime with Eclipse, and the path forward for Jakarta EE 9 and beyond.
Why listen to this podcast:
- Java EE, unlikely Java SE, has always been a multi-vendor ecosystem. It made sense for everyone for Oracle to invite their partners to be involved in the governance of the specification for Java EE for it to continue moving forward. This is the reason for moving Java EE into the Eclipse Foundation as Jakarta EE.
- The current plan is for the Eclipse Foundation to get a copyright license to evolve the text of the specification and not a license to the trademarks of Java EE itself.
- The javax namespace must remain as is. For it to be evolved, a different namespace must be used.
The javax namespace is a trademark of Oracle. Because of this, there are quality controls that Oracle required for its evolution. Ultimately because of those controls, the Eclipse Foundation felt it was better to branch javax into a different namespace and evolve it separately solely under Jakarta EE governance.
- Jakarta EE 8 is targeted to be released around Oracle Code ONE. Jakarta EE 8 will be exactly the same as Java EE 8. * The only difference is it will be licensed from Jakarta, not Oracle and only requires membership in the Working Group.
- Beyond EE 8, the release cycle, the plan for moving the javax namespace (and keeping compatibility with both the old javax namespace and the new namespace), and new specifications for inclusion into Jakarta EE are still active areas of discussion.
- Unrelated to the discussion of Jakarta EE (but discussed in the same board meeting), an attempt to bundle OpenJ9 with the Eclipse IDE failed because of licensing restrictions around a certified Java Runtime. OpenJ9 is certified when acquired through an IBM channel, but not when downloaded directly for us.
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6/3/2019 • 26 minutes, 55 seconds
Piero Molino on Ludwig, a Code-Free Deep Learning Toolbox
Ludwig is a code-free deep learning toolbox originally created and open sourced by UberAI. Today, on the podcast the creator of Ludwig Piero Molino and Wes Reisz discuss the project. The two talk about how the project works, its strengths, it’s roadmap, and how it’s being used by companies inside (and outside) of Uber. They wrap by discussing path ahead for Ludwig and how you can get involved with the project.
Why listen to this podcast:
• Uber AI is the research and platform team for everything AI at the company with the exception of self-driving cars. Self-driving cars are left to Uber ATG.
• Ludwig allows you to specify a Tensorflow model in a declarative format that focuses on your inputs and outputs. Ludwig then builds a model that can deal with those types of inputs and outputs without a developer explicitly specifying how that is done.
• Because of Ludwig’s datatype abstraction for inputs and outputs, there is a huge range of applications that can be created. For example, an input could be text and output could be a category. In this case, Ludwig will create a text classifier. An image and text input (such as a question: “Is there a dog in this image”) would output a question answering system. There are many combinations that are possible with Ludwig.
• Uber is using Ludwig for text classification for customer support.
• Datatypes can be extended easily with Ludwig for custom use cases.
• Ludwig would love to have people contribute to the project. There are simple feature requests that are just not prioritized with the current contributor workload. It’s a great place to get involved with machine learning and gain experience with the project.
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From time to time InfoQ publishes trend reports on the key topics we’re following, including a recent one on DevOps and Cloud. So if you are curious about how we see that state of adoption for topics like Kubernetes, Chaos Engineering, or AIOps point a browser to http://infoq.link/devops-trends-2019.
5/24/2019 • 29 minutes, 19 seconds
Ben Sigelman, Co-Creator of Dapper & OpenTracing API, on Observability
Ben Sigelman is the CEO of Lightstep and the author of the Dapper paper that spawned distributed tracing discussions in the software industry. On the podcast today, Ben discusses with Wes observability, and his thoughts on logging, metrics, and tracing. The two discuss detection and refinement as the real problem when it comes to diagnosing and troubleshooting incidents with data. The podcast is full of useful tips on building and implementing an effective observability strategy.
Why listen to this podcast:
- If you’re getting woke up for an alert, it should actually be an emergency. When that happens, things to think about include: when did this happen, how quickly is it changing, how did it change, and what things in my entire system are correlated with that change.
- A reality that seems to be happening in our industry is that we’re coupling the move to microservices with a move to allowing teams to fully self-determine technology stacks. This is dangerous because we’re not at the stage where all languages/tools/frameworks are equivalent.
- While a service mesh offers a great potential for integrations at layer 7 many people have unrealistic expectations on how much observability will be enabled by a service mesh. The service mesh does a great job of showing you the communication between the services, but often the details get lost in the work that’s being done inside the service. Service owners need to still do much more work to instrument applications.
- Too many people focus on the 3 Pillars of Observability. While logs, metrics, and tracing are important, observability strategy ought to be more focused on the core workflows and needs around detection and refinement.
- Logging about individual transactions is better done with tracing. It’s unaffordable at scale to do otherwise.
- Just like logging, metrics about individual transactions are less valuable. Application level metrics such as how long a queue is are metrics that are truly useful.
- The problem with metrics are the only tools you have in a metrics system to explain the variations that you’re seeing is grouping by tags. The tags you want to group by have high cardinality, so you can’t group them. You end up in a catch 22.
- Tracing is about taking traces and doing something useful with them. If you look at hundreds or thousands of tracing, you can answer really important questions about what’s changing in terms of workloads and dependencies about a system with evidence.
- When it comes to serverless, tracing is more important than ever because everything is so ephemeral. Node is one of the most popular serverless languages/frameworks and, unfortunately, also one of the hardest of all to trace.
- The most important thing is to make sure that you choose something portable for the actual instrumentation piece of a distributed tracing system. You don’t want to go back and rip out the instrumentation because you want to switch vendors. This is becoming conventional wisdom.
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5/5/2019 • 42 minutes, 18 seconds
Ashley Williams on Web Assembly, Wasi, & the Application Edge*
- Web Assembly (wasm) is a set of instructions or a low-level byte code that is a target for higher level languages. It was added to the browser because it was a portion of the web platform that many felt was just missing.
- Wasm is still a young technology. It performs really well for computationally intensive applications and also offers performance consistency (because it lacks a garbage collector).
- Bootstrapping an application using the Rust toolchain looks like: pull down a template, export a function using an attribute (defines that you want to access this function from JavaScript), and run a tool called wasm-pack (compiles it into Web Assembly and then runs a tool called wasm-bindgen that generated Rust types for Wasm). Then you can talk to that binary as if it was written in JavaScript in your code.
- Cloudflare workers allow JavaScript that you might have written for a server to be written and distributed at the application edge (or close to the end user). It uses a similar model as serverless architecture platforms.
- Interesting use cases such as A/B testing, DDoS prevention, server-side rendering, or traffic shaping can be done at the edge.
- Wasm is an approach to bringing full application experiences to the edge.
- Wasi (Web Assembly System Interface) is a standardized interface for running Web Assembly for places that are outside of the web. Fastly recently released a pure Web Assembly runtime for their edge that is built on top of Wasi called Lucet (allows access to lower level things at the edge like sockets and UDP).
- Zoom has a web client written in Web Assembly.
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4/26/2019 • 40 minutes, 40 seconds
Bryan Cantrill on Rust and Why He Feels It’s The Biggest Change In Systems Development in His Career
Bryan Cantrill is the CTO of Joyent and well known for the development of DTrace at Sun Microsystems. Today on the podcast, Bryan discusses with Wes Reisz a bit about the origins of DTrace and then spends the rest of the time discussing why he feels Rust is the “biggest development in systems development in his career.” The podcast wraps with a bit about why Bryan feels we should be rewriting parts of the operating system in Rust.
Why listen to the podcast:
• DTrace came down to a desire to use Dynamic Program Text Modification to instrument running systems (much like debuggers do) and has its origins to when Bryan was an undergraduate.
• When a programming language delivers something to you, it takes it from you in the runtime. The classic example of this is garbage collection. The programming language gives you the ability to use memory dynamically without thinking of how the memory is stored in the system, but then it’s going to exact a runtime cost.
• One of the issues with C is that it just doesn’t compose well. You can’t just necessarily pull a library off the Internet and use it well. Everyone’s C is laden with some many idiosyncrasies on how it’s used and the contract on how memory is used.
• Ownership is statically tracking who owns the structure. It’s ownership and the absence of GC that allows you to address the composability issues found in C.
• It’s really easy in C to have integer overflow which leads to memory safety issues that can be exploited by an attacker. Rust makes this pretty much impossible because it’s very good at how it determines how you use signed vs unsigned types.
• You don’t want people solving the same problems over and over again. You want composability. You want abstractions. What you don’t want is where you’ve removed so much developer friction that you develop code that is riddled with problems. For example, it slows a developer down to force them to run a linter, but it results in better artifacts. Rust effective builds a lot of that linter checking into the memory management/type checking system.
• While there’s some learning curve to Rust. It’s not that bad if you realize there are several core concepts you need to understand to understand Rust. Rust is one of those languages that you really need to learn in a structured way. Sit down with a book and learn it.
• Rust struggles when you have objects that are multiply owned (such as a Doubly Linked List). It’s because it doesn’t know who owns what. While Rust supports unsafe operations, you should resist the temptation to develop with a lot of unsafe operations if you want the benefits of what Rust offers developers.
• Firmware is a great spot for growing Rust development in a process of replacing bits of what we think of as the operating system.
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4/12/2019 • 38 minutes, 41 seconds
Oracle Labs’ Duncan Macgregor on Graal, TruffleRuby, & Project Loom
Duncan Macgregor speaks with Wes Reisz about the work being done on the experimental Graal Compiler. He talks about the use cases and where the new JIT compiler excels really well (compared to C2). In addition, Duncan talks about the relationship of Graal to Truffle. The two then discuss a language Duncan works on at OracleLabs (TruffleRuby) that is being implemented on the stack. Finally, the podcast wraps with a discussion of Project Loom and its relationship to TruffleRuby and Graal.
Why listen to this podcast:
- Graal is a replacement for the JVM’s C2 JIT compiler. It was tracked with JEP 295 (Ahead-of-Time Compilation) and included in Java 9. As of Java 10, Graal is experimental for the Linux x64 platform.
- Graal is written in Java and excels at implementing code that takes a functional approach to solving problems (such as Scala). It can also offer improvements / optimizations for other languages (including other non-traditional JVM languages such as C and Ruby).
- Truffle is a language implementation framework used my Graal. The idea is rather than having to write a compiler for your language, you can write an interpreter. This gives you the ability to write specializations at a higher level of abstraction that yields performance and better understanding.
- Truffle’s architecture and design allows things like allowing unrelated languages to do interop, garbage collection, and types.
- TruffleRuby and JRuby started off with a lot of shared code. They’ve branched and JRuby today focuses on integration with other Java classes. It compiles to bytecode and then relies on the C2 JIT to run on the JVM. TruffleRuby doesn’t try to compile to Java classes and only uses the Truffle framework to compile the things it needs. TruffleRuby is able to use most of native Ruby.
- Project Loom is a project that aims to add one shot delimited continuations to the JVM. It leverages fibers (a much lighter concurrency primitive than threads) and can literally run millions of them.
4/5/2019 • 29 minutes, 41 seconds
Rod Johnson Chats about the Spring Framework Early Days, Languages Post-Java, & Rethinking CI/CD
Today on The InfoQ Podcast, Wes talks with Rod Johnson. Rod is famously responsible for the creation of the Spring Framework. The two talk about the early years of the framework and provides some of the history of its creation. After discussing Spring, Wes and Rod discuss languages he’s been involved with since Java (these include Scala and TypeScript). He talks a bit about what he liked (and didn’t like) about each. Finally, the two wrap by discussing Atomist and how they’re trying to change the idea of software delivery from a statically defined pipeline (located in individual repositories) to an event hub that drives a series of actions for software delivery. He describes this as creating an API for your software.
Why listen to this podcast:
- The initial origins of the Spring Framework really came about through a process of trying to write a really great book about J2EE in 2002. It was through that process that Rod Johnson found he felt there was a better way and ultimately lead to the creation of the Spring Framework.
- What started as examples and references, became the Spring Framework. By 2005 there were about 2 million downloads of the Spring Framework.
After leaving VMWare in 2013, Rod spent several years working with Scala. One of the elegant features that really attracted Rod to Scala was how everything is an expression. One of the things he didn’t like was an affinity to overly complex approaches to problem solving.
- Today at Atomist, Rod does a lot of work in Node. He really enjoys the robust extra layer of typing over a dynamic language and the ability to escape to JavaScript if needed (similar to escaping types with reflection in Java found in the internals of the Spring Framework).
- Atomist, the company he founded after leaving VMWare, is rethinking CI/CD from a static pipeline defined in every repository to an event-driven system that defines how to respond to specific events (such as a push from Git). For example, all pushes with Spring Boot can be configured to be scanned with SonarQube or because a push has kubespec it might get deployed to a K8 cluster. He describes this as creating an API for your software.
- One of the reasons Atomist integrates so tightly with Slack (and other similar messaging platforms) is because it allows developers to shape their own relevant messages. By joining (or leaving channels), people are able to subscribe to only the information they actually want. Meeting developers inside Slack is an important interface for Atomist.
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3/23/2019 • 34 minutes, 18 seconds
Katharine Jarmul and Ethical Machine Learning
Today on The InfoQ Podcast, Wes talks with Katharine Jarmul about privacy and fairness in machine learning algorithms. Katharine discusses what’s meant by Ethical Machine Learning and some things to consider when working towards achieving fairness. Katharine is the Co-Founder at KIProtect a machine learning security and privacy firm based in Germany and is one of the three keynotes at QCon.ai.
Why listen to this podcast:
- Ethical machine learning is about practices and strategies for creating more ethical machine learning models. There are many highly publicized/documented examples of machine learning gone awry that show the importance of the need to address ethical machine learning.
- Some of the first steps to prevent bias in machine learning is awareness. You should take time to identify your team goals and establish fairness criteria that should be revisited over time. This fairness criteria then can be used to establish the minimum fairness criteria allowed in production.
- Laws like GDPR in the EU and HIPAA in the US provide privacy and security to users and have legal implications if not followed.
- Adversarial examples (like the DolphinAttack that used subsonic sounds to activate voice assistants) can be used to fool a machine learning model into hearing or seeing something that’s not there. More and more machine learning models are becoming an attack vector for bad actors.
- Machine learning is always an iterative process.
- Zero-Knowledge Computing (or Federated Learning) is an example of machine learning at the edge and is designed to respect the privacy of an individual’s information.
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3/16/2019 • 32 minutes, 29 seconds
Grady Booch on Today’s Artificial Intelligence Reality and What it Means for Developers
Today on The InfoQ Podcast, Wes Reisz speaks with Grady Booch. Grady is well known as the co-creator of UML, an original member of the design patterns movement, and now work he’s doing around Artificial Intelligence. On the podcast today, the two discuss what today’s reality is for AI. Grady answers questions like what does an AI mean to the practice of writing software and around how he seems it impact delivering software. In addition, Grady talks about AI surges (and winters) of over the years, the importance of ethics in software, and host of other related questions.
Why listen to this podcast:
- There have been prior ages of AI that has lead to immediate winters of where reality set in. It stands to reason, there will be a version of an AI winter that follows today’s excitement around deep learning.
- AIs are beginning to look at the code for testing edge cases in software and do things such as looking over your shoulder and identifying patterns in the code that you write.
- AIs will remove tedium for software developers; however, software developer is (and will remain) a labor-intensive activity for decades to come.nAI is another bag of tools in a larger systems activity.
- Much of the AI developers are young white men from the United States. That has a number of inherent biases in this fact. There are several organizations that are focused on combating some of these biases and bringing ethical learning into the field. This is important for us to be aware of and encourage.
- The traditional techniques of systems engineering we know for building non-AI systems will still apply. AI’s are pieces of larger systems. That might be really interesting parts, but it’s just a part of a larger system that requires a lot of non-AI engineering use cases.
- Early machine learning systems were mostly learn and forget systems. You teach them, you deploy them, and you walk away. Today, we do continuous learning and we need to integrate these new models into the delivery pipeline.
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2/22/2019 • 32 minutes, 32 seconds
Joe Beda on Kubernetes & the CNCF
Today on The InfoQ Podcast, Wes talks with Joe Beda. Joe is one of the co-creators of Kubernetes. What started in the fall of 2013 with Craig McLuckie, Joe Beda, and Brendan Burns working on cloud infrastructure has become the default orchestrator for cloud native architectures. Today on the show, the two discuss the recent purchase of Heptio by VMWare, the Kubernetes Privilege Escalation Flaw (and the response to it), Kubernetes Enhancement Proposals, the CNCF/organization of Kubernetes, and some of the future hopes for the platform.
Why listen to this podcast:
- Heptio, the company Joe and Craig McLuckie co-founded, viewed themselves as not a Kubernetes company, but more of a cloud native company. Joining VMWare allowed the company to continue a mission of helping people decouple “moving to cloud/taking advantage of cloud” patterns (regardless of where you’re running).
- Re:Invent 2017 when EKS was announced was a watershed moment for Kubernetes. It marked a time where enough customers were asking for Kubernetes that the major cloud providers started to offer first-class support.
- Kubernetes 1.13 included a patch for the Kubernetes Privilege Escalation Flaw Patch. While the flaw was a bad thing, it demonstrated product maturity in the way the community-based security response.
- Kubernetes has an idea of committees, sigs, and working groups. Security is one of the committees. There were a small group of people who coordinated the security response. From there, trusted sets of vendors validated and test patches. Most of the response is based on how many other open source projects handle security response.
- Over the last couple of releases, Kubernetes has introduced a Sig Architecture special interest group. It’s an overarching review for changes that sweep across Kubernetes. As part of Sig Architecture, the Kubernetes community has introduced Kubernetes Enhancement Proposal process (or KEPs). It’s a way for people to propose architectural changes to Kubernetes.
- The goal of the CNCF is to curate and provide support to a set of projects (of which Kubernetes is one). The TOC (Technical Oversight Committee) decides which projects are going to be part of the CNCF and how those projects are supported.
- Kubernetes was always viewed by the creators as something to be build on. It was never really viewed as the end goal.
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2/12/2019 • 30 minutes, 12 seconds
Megan Cartwright on Building a Machine Learning MVP at an Early Stage Startup
Today on the InfoQ Podcast, Wes speaks with ThirdLove’s Megan Cartwright. Megan is the Director of Data Science for the personalized bra company. In the podcast, Megan first discusses why their customers need a more personal experience and how their using technology to help. She focuses quite a bit of time in the podcast discussing how the team got to an early MVP and then how they did the same for getting to an early machine learning MVP for product recommendations. In this later part, she discusses decisions they made on what data to use, how to get the solution into production quickly, how to update/train new models, and where they needed help. It’s a real early stage startup story of a lean team leveraging machine learning to get to a practical recommendations solution in a very short timeframe.
Why listen to this podcast:
- The experience for women selecting bras is poor experience characterized by awkward fitting experiences and an often uncomfortable product that may not even fit correctly. ThirdLove is a company built to serve this market.
- ThirdLove took a lean approach to develop their architecture. It’s built with the Parse backend. The leveraged Shopify to build the site. The company’s first recommender system used a rules engine embedded into the front end. After that, they moved to a machine learning MVP with a Python recommender service that used a Random Forest algorithm in SciKit-Learn.
- Despite having the data for 10 million surveys, the first algorithms only need about 100K records to be trained. The takeaway is you don’t have to have huge amounts of data to get started with machine learning.
- To initially deploy their ML solution, ThirdLove first shadowed all traffic through the algorithm and then compared it to what was being output by the rules engine. Using this along with information on the full customer order lifecycle, they validated the ML solution worked correctly and outperformed the rules engine.
- ThirdLove’s machine learning story shows that you move towards a machine learning solution quickly by leveraging your own network and using tools that may already familiar to your team.
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1/28/2019 • 32 minutes, 14 seconds
Lynn Langit on 25% Time and Cloud Adoption within Genomic Research Organizations
Lynn Langit is a consulting cloud architect who holds recognitions from all three major cloud vendors on her contributions to their respective communities. On today’s podcast, Wes talks with Lynn about a concept she calls 25% time and a project it led her to become involved within genomic research. 25% time is her own method of learning while collaborating with someone else for a greater good. A recent project leads her to become involved with the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Australia. Through cloud adoption and some lean startup practices, they were able to drop the run time for a machine learning algorithm against a genomic dataset from 500 hours to 10 minutes.
Why listen to this podcast:
- 25% time is a way to learn, study, or collaborate with someone else for a greater good. It’s unbilled time in the service of offers. Using the idea of 25% time along with some personal events that occurred in her life, Lynn became involved with genomic researchers in Australia.
- Price of genomic sequencing has dropped. The price drop has enabled researchers to create huge repositories of genomic data; however, it was mostly on-prem. The idea of building data pipelines was pretty new in the genome community. Additionally, the genome itself is 3 billion data points. A variant of as little at 10-15 variants can be statistically significant.
- The challenge was to leverage cloud resources. To gain a quick win and buy-in for Commonwealth Scientific and Industrial Research Organisation (or CSIRO an independent Australian federal government agency) for cloud adoption, a first step was to capture interest in the idea. So the team stored their reference data in the cloud and enabled access via a Jupyter Notebook.
- They demonstrated a use case against the genomic data set leveraging a synthetic phenotype (or a fake disease) called hipsterdom. The solution became a basis for global discussion that got more people involved in the community.
- By leveraging cloud resources, the CSIRO was able to get a run their dataset that took 500 hours against an on-prem Spark cluster to 10 minutes.
- Learning new programming language has unseen benefits. For example, Ballerina (a language written as an integration language between APIs) interested Lynn because of its live visual diagrams; however, benefited her with some of the cloud pipelines because of its ability to produce YAML files.
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1/18/2019 • 26 minutes, 38 seconds
Charles Humble and Wes Reisz Take a Look Back at 2018 and Speculate on What 2019 Might Have in Store
In this podcast Charles Humble and Wes Reisz talk about autonomous vehicles, GDPR, quantum computing, microservices, AR/VR and more.
* Waymo vehicles are now allowed to be on the road in California running fully autonomous; they seem to be a long way ahead in terms of the number of autonomous miles they’ve driven, but there are something like 60 other companies in California approved to test autonomous vehicles.
* It seems reasonable to assume that considerably more regulation around privacy will appear over the next few years, as governments and regulators grapple with not only social media but also who owns the data from technology like AR glasses or self-driving cars.
* We’ve seen a huge amount of interest in the ethical implications of technology this year, with Uber getting into some regulatory trouble, and Facebook being co-opted by foreign governments for nefarious purposes. As software becomes more and more pervasive in people's lives the ethical impact of what we all do becomes more and more profound.
* Researchers from IBM, the University of Waterloo, Canada, and the Technical University of Munich, Germany, have proved theoretically that quantum computers can solve certain problems faster than classical computers.
* We’re also seeing a lot of interest around human computer interaction - AR, VR, voice, neural interfaces. We had a presentation at QCon San Francisco from CTRL-labs, who are working on neural interfaces - in this case interpreting nerve signals - and they have working prototypes. Much like touch this could open up computing to another whole group of people.
12/28/2018 • 35 minutes, 18 seconds
Java Language Architect Brian Goetz on Java and the JDK
On this week’s podcast, Wes Reisz talks with Brian Goetz. Brian is the Java Language Architect at Oracle. The two start with a discussion on what the six-month cadence has meant to the teams developing Java. Then move to a review of the features in Java 9 through 12. Finally, the two discuss the longer-term side projects (such as Amber, Loom, and Valhalla) and their role in the larger release process for the JDK.
* The JVM’s sixth-month cadence changed the way the JDK is delivered and planned. While it definitely provides more rapid delivery at expected intervals, the release train approach turned out to also improve flexibility and efficiency.
* Oracle JDK and OpenJDK are almost identical. Most of the JDK distributions are forks from OpenJDK with different bug fixes and backports applied. So the difference between the distributions now is largely which bug fixes are picked up.
* Local Variable inference (which was released as part of Java 10) illustrated the tension on making changes to the language. Many people wanted the change, but many others felt it would enable people to write bad code. Oracle had to balance the two views when making the change.
* The number of Java versions allow finer grain decision making on what is appropriate for an application. With the adoption of containers, applications are bundled with an exact JDK version rather than having to use one from a systems level. The different versions give developers more options.
* Incubating features are new libraries added to the JDK. They were offered starting with Java 9 as a way for people to test and offer feedback more rapidly. With Java 12, preview features will be released. Preview features are similar but are core platform and language features.
* Shenandoah and ZGC are both low latency garbage collectors. They originally came from different sources. While both garbage collectors are similar, each has different performance characteristics under different workloads. The two garbage collectors represent options available to JVM developers.
* Most non-trivial JDK features take more than six months to develop. Longer term side projects like Amber, Loom, Valhalla are where these features are developed prior to being released with a version of the JDK. The projects range from language enhancements to concurrency work.
12/23/2018 • 41 minutes, 18 seconds
Tanya Reilly on Site Reliability Engineering and the Evolution of the New York City Fire Code
This week on the InfoQ Podcast, Wes Reisz talks to Tanya Reilly (Principal Engineer at Squarespace and previously a staff SRE at Google). Tanya discusses her research into how the fire code evolved in New York and draws on some of the parallels she sees in software. Along the way, she discusses what it means to be an SRE, what effective aspects of the role might look like, and her opinions on what we as an industry should be doing to prevent disasters. This podcast features discussion on paved roads, prevention, testing, firefighting (in software), and reliability questions to ask throughout the software lifecycle.
Why listen to this podcast:
- Teams increasingly are responsible for the entire software lifecycle. When this happens, they think about the software differently because they know their the ones that will get paged if it fails. This idea is at the core of the “You Build It, You Run It” philosophy in DevOps.
- The role of SRE is to define how to do things in a really reliable way. The focus is to make the majority of the operations work go away, and, for the things that can’t go away, it’s as easy as possible.
- At the very start of a project (when you’re writing the initial design), you should be thinking about the dependencies for a system and how will those that follow with be able to determine that. A great way to do this is to offer an API that people will want to use and then instrument it.
- We can learn a lot from the growth of fire safety regulations as metaphors for software, including: fireproof interior walls, socializing best practices, software inspections, and circuit breakers are all examples.
- The work SREs do varies in many places. SREs range from making recommendations on patterns to library creators in other areas. Occasionally, SREs are firefighters of last resort. In these cases, they’re the last resort though.
- We use error budgets and SLOs to quantify how many much risk we’re comfortable taking. It’s used to inform how much less (or more risk) we’re willing to take on.
- We need to consider software reliability throughout the full cycle of software development. When you build systems. Think about as if there will not be someone on call for it .
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12/17/2018 • 32 minutes, 27 seconds
Jason Maude on Building a Modern Cloud-Based Banking Startup in Java
On today’s podcast, Wes Reisz talks with Jason Maude of Starling Bank. Starling Bank is a relatively new startup in the United Kingdom working in the banking sector. The two discuss the architecture, technology choices, and design processes used at Starling. In addition, Maude goes into some of the realities of building in the cloud, working with regulators, and proven robustness with practices like chaos testing.
Why listen to this podcast:
- Starling Bank was created because the government lowered the barrier to entry for banking startups in reaction to previous industry bailouts.
- The system is composed of around 19 applications hosted on AWS and running Java and backed by a PostgreSQL database.
- These applications are not monolithic but are focused around common functionality (such as a Card or Payment Service).
- Java was chosen primarily because of its maturity and long term viability/reliability in the market.
- The heart of Starling is every action the system takes happens at least once and at most once. To help with these rules, everything in their system uses as a correlation id (UUID) and are used to make sure these two rules are met.
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11/30/2018 • 36 minutes, 18 seconds
Martin Fowler Discusses New Edition of Refactoring, Along With Thoughts on Evolutionary Architecture
Martin Fowler chats about the work he’s done over the last couple of years on the rewrite of the original Refactorings book. He discusses how this thought process has changed and how that’s affected the new edition of the book. In addition to discussing Refactors, Martin and Wes discuss his thoughts on evolutionary architecture, team structures, and how the idea of refactors can be applied in larger architecture contexts.
Why listen to this podcast:
- Refactoring is the idea of trying to identify the sequence of small steps that allows you to make a big change. That core idea hasn’t changed.
- Several new refactorings in the book deal with the idea of transforming data structures into other data structures, Combine Functions into Transform for example.
- Several of the refactorings were removed or not added to the book in favor of adding them to a web edition of the book.
- A lot of the early refactorings are like cleaning the dirt off the glass of a window. You just need them to be able to see where the hell you are and then you can start looking at the broader ones.
- Refactorings can be applied broadly to architecture evolution. Two recent posts How to break a Monolith into Microservices, by Zhamak Dehghani, and How to extract a data-rich service from a monolith by Praful Todkar on MartinFowler.com deal with this specifically.
- Evolutionary architecture is a broad principle that architecture is constantly changing. While related to Microservices, it’s not Microservices by another name. You could evolve towards or away from Microservices for example.
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11/2/2018 • 32 minutes, 55 seconds
Mitchell Hashimoto on Consul since 1.2 and its Role as a Modern Service Mesh
In June of this year, Consul 1.2 was released. The release expanded Consul’s capability around service segmentation (controlling who and how services connect East and West). On this week’s podcast, Wes and Mitchell discuss Consul in detail. The two discuss Consul’s design decisions around focusing on user space networking, layer 4 routing, Go, Windows’ performance characteristics, the roadmap for eBPF on Linux, and an interesting feature that Consul implements called Network Tomography. The show wraps with Mitchell’s discussion on some of the research that Hashicorp is doing around machine learning and security with Consul.
Why listen to this podcast:
- Consul is first and foremost a centralized service registry that provides discovery. While it has a key-value store, it is Consul’s least important feature.
With the June release (1.2), Consul entered more into the space of a service mesh with the focus on service segmentation (controlling how you connect and who can connect).
- Hashicorp attempts to limit the language fragmentation in the Company and has seen a lot of success leveraging Go across their platforms. Therefore, Consul is written in Go.
- Because Consul focused on layer 4 first, it is recommended to leverage the recent integration with Envoy for achieving high degrees of observability.
- All of the network routing with Consul happens in user space at this point; however, kernel space routing with eBPF is planned for the near term. The focus, at this point, is safely cross-compiling to every platform and addressing the most possible use cases. The focuses isn’t on the high performance use cases (yet).
- For any two servers across the globe in different data centers, instantly Consul can give you 99th percentile round-trip time between with uses a feature called Network Tomography.
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10/21/2018 • 34 minutes, 7 seconds
Camille Fournier on Platform Engineering, Engineering Ladders, and her Book “The Managers Path
On the podcast this week Charles Humble talks to Camille Fournier about running a platform team, how her current role differs from the CTO role she had a Rent the Runway, the skills developers need to acquire as they move from engineering to management positions, tends like Holacracy, and her book "The Manager's Path"
Why listen to this podcast:
- When looking for platform engineers Camille looks for people who understand what it takes to build and run distributed systems - network, availability, data - and customer empathy.
- The team needs to be focussed on taking the time do build robust software for operational excellence.
- The technical skills were different at Rent the Runway - these would tend to be more full-stack engineers who worked in a more iterative way.
- Much of what we do at work is really about human relationships. One thing about relationships is that they tend to be better when you have one on one conversations with people on our regular basis. A lot of the value of one on one meeting is that you are reenforcing the social connection you have with the other person.
- One of the most important things we do as engineering managers is stay abreast of how to make teams effective in the context of delivering software.
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10/12/2018 • 33 minutes, 19 seconds
Emmanuel Ameisen, Head of AI at Insight, on Building a Semantic Search System for Images
On this week’s podcast, Wes Reisz talks to Emmanuel Ameisen, head of AI for Insight Data Science, about building a semantic search system for images using convolution neural networks and word embeddings, how you can build on the work done by companies like Google, and then explores where the gaps are and where you need to train your own models. The podcast wraps up with a discussion around how you get something like this into production.
Why listen to this podcast:
- A common use case is the ability to search for similar things - I want to find another pair of sunglasses like these, or I want a cat that looks like this picture, or even a tool like Google’s Smart Reply, can all be considered broadly the domain of semantic search.
- For image classification you generally want a convolutional neural network. You typically use a model pre-trained with a public data set like Imagenet pre-trained to generate embeddings, using the pre-trained model up to the penultimate layer, and storing the value of the activations.
- From here the idea is to mix image embeddings with word embeddings. The embeddings, whether for words or images, are just a vector that represents a thing. There are many approaches to getting vectors for words, but the one that started it is word2vec.
- For both image embeddings and word embeddings you can typically use pre-trained models, meaning that you only need to train the final step of bringing the two models together.
- Before deploying to production it is important that you validate the model against biases such as sexism, typically using outside people to a carry out a through audit.
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10/8/2018 • 35 minutes, 19 seconds
Ben Kehoe, Cloud Robotics Research Scientist, Discusses Serverless @iRobot
On this week’s podcast, Wes Reisz talks with Ben Kehoe of iRobot. Ben is a Cloud Robotics Research Scientist where he works on using the Internet to allow robots to do more and better things. AWS and, in particular, Lambda is a core part of cloud enabled robots. The two discuss iRobot’s cloud architecture. Some of the key lessons on the podcast include: thoughts on logging, deploying, unit/integration testing, service discovery, minimizing costs of service to service calls, and Conway’s Law.
Why listen to this podcast:
- The AWS Platform, including services such as Kinesis, Lambda, and IoT Gateway were key components in allowing iRobot to build out everything they needed for Internet-connected robots in 2015.
- Cloud-enabled Roombas talk to the cloud via the IoT Gateway (which is MQQT) and are able to perform large file uploads using mutually authenticated certificates signed via an iRobot Certificate Authority. The entire system is event-driven with lambda being used to perform actions based on the events that occur.
- When you’re using serverless, you are using managed infrastructure rather than building your own. So that means, when they exist, you have to accept the limitations of the infrastructure. For example, until recently Lambda didn’t have an SQS integration. So because of that limitation, you have to have inventive ways to make things work as you want.
- Serverless is all about the total cost of ownership. It’s not just about development time, but across on areas that need to support operating the environment.
- iRobot takes an approach of unit testing functions locally but does integration testing on a deployed set of functions. A library called Placebo helps engineers record events sent to the cloud and then replay them for local unit tests.
- For logging/tracing, iRobot packages up information that a function uses into a structured record that is sent to CloudWatch. They then pipe that into SumoLogic to be able to trace executions. Most of the difficulties that happen tend to happen closer to the edge.
- iRobot uses Red/Black deployments to have a completely separate stack when deploying. In addition, they flatten (or inline) their function calls on deployment. Both of these techniques are used as cost optimization techniques to prevent lambdas calling lambdas when not needed.
- Looking towards the future of serverless, there is still work to be done to offer the same feature set that more traditional applications can use with service meshes.
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9/21/2018 • 38 minutes, 31 seconds
Vaughn Vernon on Developing a Domain Driven Design first Actor-Based Microservices Framework
Vaughn Vernon is thought-leader in the space of reactive software and Domain Driven Design (DDD). Vaughn has recently released a new open source project called vlingo. The platform is designed to support DDD at the framework and toolkit level. On today’s podcast, Vaughn discusses what the framework is all about, why he felt it was needed, and some of the design decisions made in developing the platform, including things like the architecture, actor model decisions, clustering algorithm, and how DDD is realized with the framework.
Why listen to this podcast:
- Vlingo is an open source system for building distributed, concurrent, event-driven, reactive microservices that supports (at the framework level) Domain Driven Design.
- The platform is in the early stages. It runs on the JVM. There is a port to C#. All code is pushed up stream.
- The platform uses the actor model and all messages are sent in a type-safe way.
- Vlingo supports clustering and uses a bully algorithm to achieve consensus.
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9/14/2018 • 34 minutes, 2 seconds
Justin Cormack on Decomposing the Modern Operating System
On today’s podcast, Justin Cormack discusses how the modern operating system is being decomposed with toolkits and libraries such as LinuxKit, eBPF, XDP, and what the kernel space service mesh Cilium is doing. Wes Reisz and Justin Cormack also discuss how Cilium differs from service meshes like an Istio, Linkerd2 (previously Conduit), or Envoy. Justin is a systems engineer at Docker. He previously was working with unikernels at Unikernel Systems in Cambridge before being acquired by Docker. (edited)
*Key Takeaways:*
* LinuxKit is an appliance way of thinking about your operating system and is gaining adoption. There are contributions now from Oracle, Cloudflare, Intel, etc. Docker has seen interesting use cases such as customers running LinuxKit on large cloud providers directly on bare metal (more on this coming soon).
* The operating system of today is really unchanged since the Sun workstation of the 90’s. Yet everything else about software has really changed such as automation, build pipelines, and delivery.
* XDP (eXpress Data Path) is a packet processing layer for Linux that lets you run fast in kernel compiled safe program in kernel called eBPF. It’s used for things like packet filtering and encapsulation/decapsulation.
* Cilium is an in-kernel, high performance service mesh that leverages eBPF. Cilium is very good at layer 4 processing, but doesn’t really do the layer 7 things that some of the other services meshes can offer (such as proxying http/1 to http/2)
9/7/2018 • 32 minutes, 21 seconds
Mike Lee Williams on Probabilistic Programming, Bayesian Inference, and Languages like PyMC3
Probabilistic Programming has been discussed as a programming paradigm that uses statistical approaches to dealing with uncertainty in data as a first class construct. On today’s podcast, Wes talks with Mike Lee Williams of Cloudera’s Fast Forward Labs about Probabilistic Programming. The two discusses how Bayesian Inference works, how it’s used in Probabilistic Programming, production-level languages in the space, and some of the implementations/libraries that we’re seeing.
Key Takeaways
* Federated machine learning is an approach of developing models at an edge device and returning just the model to a centralized location. By taking the averages of the edge models, you can protect privacy and distribute processing of building models.
*Probabilistic Programming is a family of programming languages that make statistical problems easier to describe and solve.
*It is heavily influenced by Bayesian Inference or an approach to experimentation that turns what you know before the experiment and the results of the experiment into concrete answers on what you should do next.
* The Bayesian approach to unsupervised learning comes with the ability to measure uncertainty (or the ability to quantify risk).
* Most of the tooling used for Probabilistic Programming today is highly declarative. “You simply describe the world and press go.”
* If you have a practical, real-world problem today for Probabilistic Programming, Stan and PyMC3 are two languages to consider. Both are relatively mature languages with great documentation.
* Prophet, a time-series forecasting library built at Facebook as a wrapper around Stan, is a particularly approachable place to use Bayesian Inference for forecasting use cases general purpose.
8/31/2018 • 33 minutes, 16 seconds
Uncle Bob Martin on Clean Software, Craftsperson, Origins of SOLID, DDD, & Software Ethics
Wes Reisz sits down and chats with Uncle Bob about The Clean Architecture, the origins of the Software Craftsperson Movement, Livable Code, and even ethics in software. Uncle Bob discusses his thoughts on how The Clean Architecture is affected by things like functional programming, services meshes, and microservices.
Why listen to this podcast:
* Michael Feathers wrote to Bob and said if you rearrange the order of the design principles, it spells SOLID.
* Software Craftsperson should be used when you talking about software craftsmanship in a gender-neutral way to steer clear of anything exclusionary.
* Clean Architecture is a way to develop software with low coupling and is independent of implementation details.
* Clean Architecture and Domain Driven Design (DDD) are compatible terms. You would find the ubiquitous language and bounded context of DDD at the innermost circles of a clean architecture.
* Services do not form an architecture. They form a deployment pattern that is a way of decoupling and therefore has no impact on the idea of clean architecture.
* There is room for “creature comforts” in a code base that makes for more livable, convenient code.
* “We have no ethics that are defined [in software].” If we don’t find a way to police it ourselves, governments will. We have to come up with a code of ethics.
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8/24/2018 • 30 minutes, 6 seconds
Arun Gupta on Managed Container Control Planes on AWS
Arun Gupta discusses with Wes Reisz some of the container-focused services that AWS offers, including differentiating ECS and EKS. Arun goes into some detail the role that Amazon Fargate plays and goals behinds EKS. Arun wraps ups discussing some of the open source work that AWS has recently been doing in the container space.
Why liste to this podcast:
- ECS & EKS are both managed control planes; Amazon Fargate is a technology used to provision clusters.
- ECR is the Amazon Container registry (similar to the Docker Registry).
- EKS is an opinionated why of running a Kubernetes cluster on AWS. It is a highly available managed control plane available on US East 1 and US West 2
- EKS uses a split account. The control plane runs in an Amazon account and the workers run in customer’s account.
- Upstream compatibility is a core tenant of EKS.
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7/6/2018 • 24 minutes, 35 seconds
Anastasiia Voitova on Cryptography and the Design of Cryptographic Libraries
In this podcast Wes Reisz is talking to Anastasiia Voitova, known as @vixentael in the security communities. She started her career as a mobile application developer, and in recent years has moved to focus mainly on designing and developing graphics software. We’re going to talk about cryptography, how to design libraries to be usable by developers, and designing cryptographic libraries. We’ll also discuss about her talk from the recent QCon New York , called “Making Security Usable”.
Why listen to this podcast:
- Choosing a good encryption algorithm isn’t enough - the parameters need to be chosen carefully as well
- Algorithms like MD5 should not be used for hashing any more
- Security is not just the encryption layer - it is the design of the whole system
- Backups should be encrypted as well
- Logs may contain sensitive GDPR data and need to be processed accordingly
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6/29/2018 • 27 minutes, 1 second
Matt Klein on Lyft’s Envoy, Including Edge Proxy, Service Mesh, & Potential AI Use Cases
On today’s podcast, Wes Reisz talks to Matt Klein about Envoy. Envoy is a modern, high performance, small footprint edge and service proxy. While it was originally developed at Lyft (and still drives much of their architecture), it is a fully open source driven project. Matt addresses on this podcast what he sees as the major design goals of Envoy, answers questions about a sidecar performance impact, discusses observability, and thinks out loud on the future of Envoy.
Why listen to this podcast:
- Envoy’s goal is to abstract the network from application programmers. It’s really about helping application developers focus on building business logic and not on the application plumbing.
- Envoy is a large community driven project, not a cohesive product that does one thing. It can be used as a foundational building blocks to extend into a variety of use cases, including as an edge proxy, as a service mesh sidecar, and as a substrate for building new products.
- While there is performance cost for using sidecar proxies, the rich featureset is often a worthwhile tradeoff. With that said, there is work being done that is greatly improving Envoy’s performance.
- Envoy is built to run Lyft. There were no features that were in Envoy when it was open sourced that were not used at Lyft.
- Envoy emits a rich set of logs and has a plugable tracing system. The goal is observability first and one of the main project goals.
- Lyft deploys Envoy master twice per week.
- Envoy’s roadmap includes work on automating settings (rate limits and retries), focus on ease of operation (such as where things got routed what the internal timings), and additional protocol support such as Kafka.
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6/22/2018 • 34 minutes, 59 seconds
Pam Selle on Serverless Observability
On this podcast, Pam Selle (an engineer for IOPipe who builds tooling for serverless observability) talks about the case for serverless and the challenges for developing observability solutions. Some of the things discussed on the podcast include tips for creating boundaries between serverless and non-serverless resources and how to think of distributed tracing in serverless environments.
Why listen to this podcast:
- Coca Cola was able to see a productivity gain of 29% by adopting serverless (as measured by the amount of time spent on business productivity applications).
- Tooling for serverless is often a challenge because resources are ephemeral. To address the ephemeral nature of serverless, you need to think about what information you will need to log ahead of time.
- Monitoring should focus on events important to the business.
- Build barriers between serverless and flat scaling non-serverless resources to prevent issues. Queues are an example of ways to protect flat scaling resources.
- In-memory caches are a handy way to help serverless functions scale when fronting databases.
- There are limitations with tracing and profiling on serverless. Several external products are available to help.
- Serverless (and Microservices) are not for every solution. If you are choosing between two things, and one of them lets you ship and the other does not choose the thing that lets you ship.
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6/4/2018 • 28 minutes, 40 seconds
Serverless and the Serverless Framework with David Wells
The Serverless Framework is quickly becoming one of the more popular frameworks used in managing serverless deployments. David Wells, an engineer working on the framework, talks with Wes Reisz about serverless adoption and the use of the open source Serverless Framework.
On this week’s podcast, the two dive into what it looks like to use the tool, the development experience, why a developer might want to consider a tool like the serverless framework, and finally wraps up with what the tool offers in areas like CI/CD, canaries, and blue/green deployment.
Why listen to this podcast:
- Serverless allows you to focus on the core business functionality and less on the infrastructure required to run your systems.
- Serverless Framework allows you to simplify the amount of configuration you need for each cloud provider (for example, you can automate much of the configuration required for CloudFormation with AWS)
- Serverless Framework is an open source CLI tool that supports all major cloud providers and several on-prem solutions for managing serverless functions.
- The serverless space has room to grow in offering a local development space. Much of the workflow today involves frequent deploy and scoping the deployment for different stages.
- Serverless Framework is open source and invites contributions from the community.
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5/27/2018 • 32 minutes, 23 seconds
Colin Eberhardt on WebAssembly
In this podcast Wes Reisz talks to Colin Eberhardt, the Technology Director at Scott Logic, talks about what WebAssembly (WASM) is, a bit of the history of JavaScript, information about WebAssembly, and plans for WebAssembly 2.0 including the threading model and GC.
Why listen to this podcast:
- WebAssembly brings another kind of virtual machine to the browser that is a much more low-level language.
- One of the goals of WebAssembly is to make a new assembly language that is a compilation target for a wide range of other languages such as C++, Java, C# and Rust. C++ is highly mature, Rust is maturing rapidly. Java and C# are a little further behind because of the lack of garbage collection support in WebAssembly. At some point in the future WebAssemblywill have it’s own garbage collection perhaps by using the Javascript garbage collector.
- At runtime you use JavaScript to invoke functions that are exported by your WebAssembly instance. It should be noted that at the moment there is quite a lot of complexity involved in interfacing between WebAssembly and JavaScript. A lot of this complexity comes from the type system.
- WebAssembly only supports four types - 2 integer types and 2 floating point types. To model strings you share the same piece of linear memory - memory that can read from and write to from both WebAssembly and JavaScript.
- WebAssembly is still a very young technology. Future plans include threading support, garbage collection support, multiple value returns.
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5/11/2018 • 32 minutes, 24 seconds
Martin Thompson on Aeron, Binary vs Text for Message Encoding, and Raft
Martin Thompson discusses consensus in distributed systems, and how Aeron uses Raft for clustering in the upcoming release. Martin is a Java Champion with over 2 decades of experience building complex and high-performance computing systems. He is most recently known for his work on Aeron and Simple Binary Encoding (SBE). Previously at LMAX he was the co-founder and CTO when he created the Disruptor.
* Aeron is a messaging system designed for modern multi-core hardware. It is highly performant with a first class design goal of making it easy to monitor and understand at runtime. The product is able to simultaneously achieve the lowest latency and highest throughput of any messaging system available today.
Why listen to this podcast:
* Aeron uses a binary format on the wire rather than a text based protocol. This is largely done for performance reasons. Text is commonly used in messaging to make debugging simpler but the debugging problem can be solved using tools like Wireshark and the dissectors that come with it.
* In a forthcoming release of Aeron will support clustering. Raft was chosen over PAXOS for this since it is more strict. This means that there are fewer potential states the system can be in making it easier to reason about.
* RAFT is an RPC-based protocol, expecting synchronous interactions. Aeron is asynchronous by its nature, but the underlying Aeron protocol was designed to support consensus, meaning that a lot of things which would typically need to be done synchronously can be done asynchronously and/or in parallel.
* Static clusters will be added first to Aeron, with dynamic clustering after that, and then cryptography again with the intention of keeping the latency and throughput high. (edited)
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5/7/2018 • 34 minutes, 22 seconds
Building a Data Science Capability with Stephanie Yee, Matei Zaharia, Sid Anand and Soups Ranjan
In this podcast, recorded live at QCon.ai, Principal Technical Advisor & QCon Chair Wes Reisz and InfoQ Editor-in-chief Charles Humble chair a panel discussion with Stephanie Yee, data scientist at StitchFix, Matei Zaharia, professor of computer science at Stanford and chief scientist at Data Bricks, Sid Anand, chief data engineer at PayPal, and Soups Ranjan, director of data science at CoinBase.
Why listen to this podcast:
- Before you start putting a data science team together make sure you have a business goal or question that you want to answer; If you have a specific question, like increasing lift on a metric, or understanding customer usage patterns, you know where you can get the data from, and you can then figure out how to organise that data.
- You need to make sure you have the right culture for the team - and find people who are excited about solving the business problems and be interested in it. Also look at the environment you are going to provide.
- Your first hire shouldn’t be a data scientist (or quant). You need support to productionise the models - and if you don’t have a colleague to help productionise it then don’t hire the quant first.
- Given the scarcity of talent it is worth remembering that Data Scientists come from a variety of different backgrounds - Some people have computer science backgrounds, some may be astrophysicists or neuroscientists who approach problems in different ways.
- There are two common ways to structure a data science team: one is a vertical team that does everything, the other, more common in large companies, is when you have a separate data science team and an infrastructure team.
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4/27/2018 • 43 minutes, 9 seconds
Streaming: Danny Yuan on Real-Time, Time Series Forecasting @Uber
On this week’s podcast, Danny Yuan, Uber’s Real-time Streaming/Forecasting Lead, lays out a thorough recipe book for building a real-time streaming platform with a major focus on forecasting. In this podcast, Danny discusses everything from the scale Uber operates at to what the major steps for training/deploy models in an iterative (almost Darwinistic) fashion and wraps with his advice for software engineers who want to begin applying machine learning into their day-to-day job.
Why listen to this podcast:
* Uber processes 850,000 - 1.3 million messages per second in their streaming platform with about 12 TB of growth per day. The system’s queries scan 100 million to 4 billion documents per second.
* Uber’s frontend is mobile. The frontend talks to an API layer. All services generate events that are shuffled into Kafka. The real-time forecasting pipeline taps into Kafka to processes events and stores the data into Elasticsearch. * There is a federated query layer in front of Elasticsearch to provide OLAP query capabilities.
* Apache Flink’s advanced windowing features, programming model, and checkpointing convinced Uber to move away from the simplicity of Apache Samza.
* The forecasting system allows Uber to remove the notion of delay by using recent signals plus historical data to project what is happening now and what will happen into the future.
* Uber’s pipeline for deploying ML models: HDFS, feature engineering, organizing into data structures (similar to data frames), deploy mostly offline training models, train models, & store into a container-based model manager.
* A model serving layer is used to pick which model to use, forecasting results are stored in an OLAP data store, a validation layer compares real results against forecast results to verify the model is working as desired, and a rollback feature enables poor performing models to be automatically replaced by previous one.
* “Without output, you don’t have input.” If you want to start leveraging machine learning, developers just need to start doing. Start with intuition and practice. Over time ask questions and learn what you need, then apply a laser focus to gain that knowledge.
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3/31/2018 • 26 minutes, 59 seconds
Sander Mak on the Java Module System
Sander Mak and Wes Reisz discuss the Java module system and how adoption is going. Topics discussed on this podcast include Java modularity steps / migrations, green field projects, some of the concerns that caused the EC to initially vote no on Java 9, and a new tool for building custom JREs called JLink. Additionally, as Java 10 was recently released a short bit at the end was added to discuss some of the latest news with Java.
Why listen to this podcast:
• People quickly moved to Java 8 because of features like Streams and Lambdas. Java 9 has a different story around modularity and application architecture. Adoption is slower and more intentional.
• Migrating large codebases to use modularity is hard. Many of the projects using modules are greenfield, and those large codebases that are moving now are most often using the classpath.
• Jlink is a new command line tool released with Java 9. It allows developers to create their own lightweight, customized JRE for a module-based Java application.
• Java version scheme has dropped the 1.* prefix. Future releases of the JDK will have the version number and follow the form *.0.1 (i.e. 9.0.1)
• While the module system will likely show it’s benefit mostly for new development, many 3rd party libraries are moving to adopt modularity and removing their dependencies on JDK internal APIs. It’s improving the experience for teams adopting modularity.
• There are no known open JEPS regarding the enhancement of the Java module system.
• Java 10 has been released. The release features changes to the freely available Java versions, local variable type inference (var), experimental GRAAL JIT compiler, application class data sharing, improved container support/awareness, and others.
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3/23/2018 • 35 minutes, 47 seconds
Jendrik Joerdening and Anthony Navarro on Self-Racing Cars Using Deep Neural Networks
Jendrik Joerdening and Anthony Navarro describe how a team of 18 Udacity students entered a self-racing car event They had very limited experience of building autonomous control systems for vehicles and had just 6 weeks to do it with only 2 days with the physical car. They describe the architecture, how they co-ordinated a very diverse team, and how they trained the models.
Why listen to this podcast:
- Last year a team of 18 Udacity Self-Driving Cars students competed at the 2017 Self Racing Cars event held at Thunderhill Raceway in California.
- The students had all taken the first term of a three term program on Udacity which covers computer vision and deep learning techniques.
- The team was extremely diverse. They co-ordinated the work via Slack with a team in 9 timezones and 5 different countries.
- The team developed a neural network using Keras and Tensorflow which steered the car based on the input from just one front-facing camera in order to navigate all turns on the racetrack.
- They received a physical car two days before the start of the event.
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3/16/2018 • 37 minutes, 58 seconds
Andrea Magnorsky on Paradigm Shifts and the Adoption of Programming Languages
On this podcast, we talk with Andrea Magnorsky, who is a tech lead at Goodlord on their engineering squads; she has a background in Scala, C#, and organised conferences. Today we’ll be talking about paradigm shifts.
Why listen to this podcast:
* A programming paradigm has a loose definition. It’s just about finding a way of doing things.
* There are a number of different ways to think about problems - and different paradigms do this in different ways.
* To shift paradigms, you have to un-learn some of your instincts.
* When adopting a new paradigm if people don’t want to learn anything, then they won’t.
* Multiple paradigms help you apply different ways of thinking about solutions to problems because solutions vary across languages.
* Quick ways to start gaining knowledge and adoption for new languages are to use a new language as a test harness for your existing code.
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3/3/2018 • 31 minutes, 45 seconds
Anne Currie on Organizational Tech Ethics, including Scale, GDPR, Algorithmic Transparency
On this podcast, Anne Currie joins the tech ethics discussion started on the Theo Schlossnagle podcast from a few weeks ago. Wes Reisz and Anne discuss issues such as the implications (and responsibilities) of the massive amount of scale we have at our fingertips today, potential effects of GDPR (EU privacy legislation), how accessibility is a an example of how we could approach tech ethics in software, and much more.
Why listen to this podcast:
- Ethics in software today is particularly important because of the scale we have available with cloud native architectures.
- Accessibility offers a good approach to how we can evolve the discussion on tech ethics with aspects that include both a carrot and a stick.
- Bitcoin mining power consumption is an example of something we never considered to have such negatives.
- The key to establishing what we all should and shouldn’t be doing with tech ethics is to start conversations and share our lessons with each other.
If you want to find out what every software developer, data scientists or ops should know about GDPR, download our free guide "Perspectives on GDPR": https://bit.ly/2FRvLnP
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2/23/2018 • 31 minutes, 50 seconds
Oliver Gould on Service Mesh for Microservices, LinkerD, and the Recently Released Conduit
This week on The InfoQ Podcast Wes Reisz talks with the CTO of Bouyant Oliver Gould. Bouyant is the maker the LinkerD Service Mesh and the recently released Conduit. In the podcast, Oliver defines a service mesh, clarifies the meaning of the data and control plane, discusses what a Service Mesh can offer a Microservice application owners, and, finally, discusses some of the considerations they took into account developing Conduit.
Why listen to this podcast:
- Service mesh is dedicated infrastructure that handles interservice communication.
- There are two components to a service mesh: the data plane handles communication and the control plane is about policy and config.
- LinkerD and Conduit are two open service meshes made by Bouyant. Conduit has a small memory footprint and provides a convention over configuration approach to service mesh deployment.
- Adopting Rust (language used for implementing the data plane in Conduit) requires thinking of memory differently, and the best way to adopt Rust is to read other people’s code.
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2/9/2018 • 33 minutes, 4 seconds
Theo Schlossnagle on Software Ethics and the Presence of Doing Good
This week's podcast features a chat with Theo Scholossnagle. Theo is the CEO of Circonus and co-chairs the ACM Queue. In this podcast, Theo and Wes Reisz chat about the need for ethical software, and how we as technical leaders should be reasoning about the software we create. Theo says, "it's not about the absence of evil, it's about the presence of good." He challenges us to develop rigor around ethical decisions we make in software just as we do for areas like security. With the incredible implications of machine learning and AI in our future, this week's podcast touches on topics we should all consider in the systems we create.
Why listen to this podcast:
- The ubiquitous society impact of computers is surfacing the need for deeper conversations on software ethics.
- Ethics are a set of constructs and constraints to help us reason about right and wrong.
- Algorithmic interpretability of models can be difficult to reason about; however, accountability for algorithms can be enforced in other ways.
- Questions to be considered when writing software should evolve into: What am I building, why am I building it, and who will it hurt?
- Ethics in software will take industry reform, deeper conversations, and developing a culture of questioning the software we’re building
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2/2/2018 • 25 minutes
Chris Swan on DevOps and NoOps, plus Operations and Code Validation in a Serverless Environment
On this week’s podcast, Wes Reisz talks with Chris Swan. Chris is the CTO for the global delivery organisation at DXC Technology. Chris is well versed in DevOps, Infrastructure, Culture, and what it means to put all these together. Today’s topics include both DevOps and NoOps, and what Chris calls LessOps, what Operations means in a world of Serverless, where he sees Configuration Management, Provisioning, Monitoring and Logging heading. The podcast then wraps talking about where he sees validating code in a serverless deployment, such as canaries and blue-green deployments.
Why listen to this podcast:
* Serverless still requires ops - even if the ops aren’t focused on the technology
* Even with minimal functions, the amount of configuration may exceed it by a factor of three
* Disruptive services often move the decimal point
* ML is the ability to make the inferences and AI is the ability to make decisions based on those inferences
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1/19/2018 • 35 minutes, 6 seconds
Architecting a Modern Financial Institution with Vitor Olivier, Thoughts on Immutability, CI/CD, FP
This week’s podcast features a chat with Vitor Olivier. Vitor is a partner at NuBank (a technology-centric bank in Brazil). This podcast hits on topics from several of Nubank’s recent QCon talks and includes things like: Nubank’s stack, functional programming, event sourcing, defining service boundaries, recommendations on reasoning about services, tips (or tweaks) on the second iteration of their initial architecture and more.
Why listen to this podcast:
- Property-based testing and Schemas (or Clojure.Spec)are complementary.
- Clojure’s functional nature and Datomic’s features are a match for Nubank’s requirements.
- A (micro)service needs to be able to create the full representation of the core feature it’s handling.
- GraphQL is useful to abstract away the distributed system complexity from the mobile (or frontend) developers.
- Nubank’s uses a combination of monitoring and sanity checks in real time at various level to keep systems consistent.
- Once an invariant is broken, the system will try to fix it automatically.
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1/12/2018 • 38 minutes, 1 second
Charles Humble and Wes Reisz Take a Look Back at 2017 and Speculate on What 2018 Might Have in Store
In this podcast Charles Humble and Wes Reisz talk about Java 9 and beyond, Kotlin, .NET Core 2, the surge in interest in organisational culture, quantum computing and more.
Why listen to this podcast:
- Java had a big year with Java 9 shipping, Java EE going open-source and moving to Eclipse as EE4J, and IBM open-sprucing J9. From next year the platform will also be on a bi-annual release cycle with the next two versions (expected to be Java 10 and 11) both shipping during 2018.
- Kotlin joined Scala, Clojure, and Groovy as a strong alternative language for the JVM particularly for mobile where it was buoyed by Google’s official blessing of it as a language for Android development at Google IO.
- On InfoQ we also saw a big surge in interest around .NET linked to .NET Core 2, and at both InfoQ and at QCon San Fransisco we also saw an upsurge in interest around organizational culture with one of the culture tracks (the Whole Engineer) moving to one of the larger rooms.
- We started to see Quantum computers emerging from the labs, with IBM making a 16 Qbit quantum processor available via their cloud for developers to play with, and the corresponding library available for Python on Github,
- Another major trend from the year was the availability of machine learning libraries for software developers to build and train models
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12/29/2017 • 29 minutes, 22 seconds
Kolton Andrus on Gremlin’s Newly Announced SaaS Chaos Engineering Product and Running Game Days
Gremlin is a Software as a Service that lets you plan, control and undo Chaos engineering experiments built by engineers with experience from Netflix, AWS, Dropbox and others. In this podcast Wes talks to Kolton Andrus about the Gremlin product and architecture and related topics such as running Game Days.
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12/22/2017 • 33 minutes, 59 seconds
Fast Data with Dean Wampler
In this podcast, Deam Wampler discusses fast data, streaming, microservices, and the paradox of choice when it comes to the options available today building data pipelines.
Why listen to this podcast:
* Apache Beam is fast becoming the de-facto standard API for stream processing
* Spark is great for batch processing, but Flink is tackling the low-latency streaming processing market
* Avoid running blocking REST calls from within a stream processing system - have them asynchronously launched and communicate over Kafka queues
* Visibility into telemetry of streaming processing systems is still a new field and under active development
* Running the fast data platform is easily launched on an existing or new Mesosphere DC/OS runtime
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12/8/2017 • 29 minutes, 39 seconds
Changhoon Kim on Programmable Networking Switches with PISA and the P4 DSL
In this podcast, Werner Schuster talks to Changhoon Kim, who is a Director of System Architecture at Barefoot Networks, and is actively working for the P4 language consortium. They talk about the new PISA (protocol independence switch architecture) which promises multi-terabit switching, and P4, a domain-specific programming language designed for networking.
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11/27/2017 • 29 minutes, 59 seconds
Apache Beam Founder Tyler Akidau Discusses Streaming System and Their Complexities
In this podcast, we are talking to Tyler Akidau, a senior engineer at Google, who leads the technical infrastructure and data processing teams in Seattle, and a founding member of the Apache Beam PMC and a passionate voice in the streaming space. This podcast will cover data streaming and the 2015 DataFlow Model streaming paper [http://www.vldb.org/pvldb/vol8/p1792-Akidau.pdf] and much of the concepts covered, such as why dealing with out-of-order data is important, event time versus processing time, windowing approaches, and finally preview the track he is hosting at QConf SF next week.
Why listen to this podcast:
- Batch processing and streaming aren’t two incompatible things; they are a function of different windowing options.
- Event time and processing time are two different concepts, and may be out of step with each other.
- Completeness is knowing that you have processed all the events for a particular window.
- Windowing choice can be answered from the what, when, where, how questions.
- Unbounded versus bounded data is a better dimension than stream or batch processing.
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11/9/2017 • 44 minutes, 56 seconds
Guy Podjarny on OSS Security, Serverless, and the Equifax Hack
In this podcast, Wes talks to Guy Podjarny (Founder/CEO Synk). The two discuss the space between open source software and third-party dependencies, including a discussion of the Equifax hack (and what we can learn from it), the role of serverless architectures today (and what it means to application surface area), and then finally they wrap with security hygiene best practices with OSS and serverless.
Why listen to this podcast:
- The majority of security vulnerabilities that exist in applications today comes from vulnerable third-party libraries, rather than the application’s own code.
- An application shouldn’t permit total leak of all data because of a single vulnerability - defence in depth is important.
- Equifax couldn’t have failed more spectacularly in the way they handled it.
- The Equifax hack serves as a wake-up call to pay attention to vulnerabilities in dependencies.
- If your build system breaks the build when a dependency vulnerability is found automatically, it will be applied sooner.
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10/30/2017 • 46 minutes, 10 seconds
Julien Viet on the Newly Released Eclipse Vert.x 3.5.0 and Plans for Vert.x 4.0
In this podcast, QCon Chair Wesley Reisz talks to Julien Viet. Viet is the project lead for Vert.x and a principal engineer at RedHat having taken over as project lead for Vert.x from Tim Fox in January 2016. They talk about the newly released Vert.x 3.5.0, and the plans for Vert.x 4.0.
Why listen to this podcast:
* Vert.x adds RxJava2 support for streams and backpressure.
* Vert.x is a polyglot set of APIs, custom aligned for the specific language.
* It is unopinionated and can be used with any environments, since it doesn’t enforce a particular framework.
* Verticles communicate in-VM or through peer-to-peer networking for distributed applications.
* Vert.x 4.0 is on the roadmap for the future.
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10/23/2017 • 29 minutes, 52 seconds
Incident Response Across Non-Software Industries with Emil Stolarsky
What can software learn from industries like aerospace, transportation, or even retail during national disasters? This week’s podcast is with Emil Stolarsky and was recorded live after his talk on the subject at Strangeloop 2017. Interesting points from the podcast include several stories from Emil’s research, including the origin of the checklist, how Walmart pushed decision making down to the store level in a national disaster, and where the formalized conversation structure onboard aircraft originated. The podcast mentions several resources you can turn to if you want to learn more and wraps with some of the ways this research is affecting incident response at Shopify.
Why listen to this podcast:
* Existing industries like aerospace have built a working history of how to resolve issues; it can be applicable to software issues as well.
* Crew Resource Management helps teams work together and take ownership of problems that they can solve, instead of a command-and-control mandated structure.
* Checklists are automation for the brain.
* Delegating authority to resolve system outages removes bottlenecks in processes that would otherwise need managerial sign off.
* When designing an alerting system, make sure it doesn’t flood with irrelevant alerts and that there’s clear observability to what is going wrong.
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10/15/2017 • 22 minutes, 48 seconds
Charity Majors on Honeycomb.io, the Social Side of Debugging and Testing in Production
In this podcast, recorded live at Strange Loop 2017, Wes talks to Charity, cofounder and CEO of honeycomb.io. They discuss the social side of debugging and her Strange Loop talk “Observability for Emerging Infra: What got you Here Won't get you There”. Other topics include advice for testing in production, shadowing and splitting traffic, and sampling and aggregation.
Why listen to this podcast:
- Statistical sampling allows for collecting more detailed information while storing less data, and can be tuned for different event types.
- Testing in production is possible with canaries, shadowing requests, and feature switches
- Pulling data out of systems is just noise - it becomes valuable once someone has looked at it and indicates the meaning behind it.
- Instrumenting isn’t just about problem detection - it can be used to ask business questions later
- You can get 80% of the benefit from 20% of the work in instrumenting the systems.
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10/7/2017 • 34 minutes, 57 seconds
Nora Jones on Establishing, Growing, and Maturing a Chaos Engineering Practice
Nora Jones, a senior software engineer on Netflix’ Chaos Team, talks with Wesley Reisz about what Chaos Engineering means today. She covers what it takes to build a practice, how to establish a strategy, defines cost of impact, and covers key technical considerations when leveraging chaos engineering.
Why listen to this podcast:
- Chaos engineering is a discipline where you formulate hypotheses, perform experiments, and evaluate the results afterwards.
- Injecting a bit of failure over time is going to make your system more resilient in the end.
- Start with Tier 2 or non-critical services first, and build up success stories to grow chaos further.
- As systems become more and more distributed, there becomes a higher need for chaos engineering.
- If you’re running your first experiment, get your service owners in a war room and get them to monitor the results of the test as it is running.
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10/1/2017 • 42 minutes, 56 seconds
Shubha Nabar Discusses Einstein, the Machine Learning System in Salesforce
Shubha Nabar is a senior director of data science for Salesforce Einstein. Prior to working for Salesforce, she was a data scientist at LinkedIn and Microsoft. In the podcast she discusses Salesforce Einstein and the problem space that they are trying to solve, explores the differences between enterprise and consumer for machine learning, and then talks about the Optimus Prime Scala library that they use in Salesforce.
Why listen to this podcast:
* The volume of data, and hardware advances have made it possible to do machine learning to do them a lot faster.
* AI is a science of building intelligent software, encompassing many aspects of intelligence that we tend to think of as human.
* If you can’t measure something, you can’t fix it.
* You have to think about what you can automate, rather than having a human to try and engineer out all those features.
* Get feedback on design.
Nora Jones, a senior software engineer on Netflix’ Chaos Team, talks with Wesley Reisz about what Chaos Engineering means today. She covers what it takes to build a practice, how to establish a strategy, defines cost of impact, and covers key technical considerations when leveraging chaos engineering.
Why listen to this podcast:
- Chaos engineering is a discipline where you formulate hypotheses, perform experiments, and evaluate the results afterwards.
- Injecting a bit of failure over time is going to make your system more resilient in the end.
- Start with Tier 2 or non-critical services first, and build up success stories to grow chaos further.
- As systems become more and more distributed, there becomes a higher need for chaos engineering.
- If you’re running your first experiment, get your service owners in a war room and get them to monitor the results of the test as it is running.
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9/29/2017 • 25 minutes, 31 seconds
Simon Brown on the Role of the Software Architect in a Continuous Delivery Environment
This week's podcast features Simon Brown well known for his work training software architects. Topics include the differences between a tech lead and an architect, how much documentation is enough and what that looks like in a continuous delivery environment.
What you'll learn on this podcast:
• As an industry we seem to have lost our knowledge of how to do architecture well in the context of modern agile software teams.
• Architecture is about the expensive decisions; things that are costly to change later.
• Ideally architects should code in the production code base. If you are not able to do this at least be involved in quality reviews and peer reviews in the production code so you can get feedback on your designs.
• It is often said the the code is the only documentation you need but the code can’t tell you everything. You do need to document the things you can’t get from the code such as the architectural drivers, they key quality attributes and so on along with some high level diagrams and how you operate the system.
• As you step into the role of architect go and find a mentor or a local meet-up. The major change is that you have to influence and lead people.
This podcast is sponsored by AppDynamics. Software architects play a critical role in designi¬¬¬ng, executing, and migrating large infrastructures to the cloud. Download AppDynamic’s FREE eBook “10 Tips for Enterprise Cloud Migration” and launch your migration project with a proven plan. Download the eBook now at http://infoq.link/web_sndcld_appdynamics
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9/23/2017 • 29 minutes, 2 seconds
Twitter's Yao Yue on Latency, Performance Monitoring, & Caching at Scale
This week's podcasts features Yao Yue of Twitter. Yao spent the majority of her career working on caching systems at Twitter. She has since created a performance team that deals with edge performance outliers often exposed by the enormous scale of Twitter. In this podcast, she discusses standing up the performance team, thoughts on instrumenting applications, and interesting performance issues (and strategies for solving them) they’ve seen at Twitter.
Why listen to this podcast:
* Performance problems can be caused by a few machines running slowly causing cascading failure
* Aggregating stats on a minute-by-minute basis can be an effective way of monitoring thousands of servers
* Being able to record second-by-second is often too expensive to centrally aggregate, but can be stored locally
* Distinguishing between request timeout and connection/network timeouts is important to prevent thundering herds
* With larger scale organisations, having dedicated performance teams helps centralise skills to solve performance problems
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9/18/2017 • 30 minutes, 18 seconds
Linda Rising on the Importance of Patterns, Her Journey, & Patterns for Driving Change/Innovation
On the InfoQ Podcast this week, Wes Reisz talks with the Queen of Patterns, Linda Rising. Linda discusses her thoughts on the importance of patterns, she answers questions about what really is a pattern, and how she became involved in working with them. Throughout the podcast she discusses a variety of organizational and personal patterns and finally wraps with patterns to apply when driving change and innovation.
Why listen to this podcast:
- You have to realise that there’s nothing you can do about other people. The only person you can affect is yourself.
- A pattern is not a band-aid that you use once. You use it in a context where you use it in conjunctions with other patterns.
- Take baby steps when driving change in an organisation, and seek out a pocket of receptive people to drive it.
- Slack is an important part to have in life, so that if something comes along you can absorb it without having to stop doing something else.
- Listen, Listen, Listen.
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9/8/2017 • 35 minutes, 14 seconds
Security Considerations and the State of Microservices with Sam Newman
Wesley Reisz talks with Sam Newman about microservices. They explore the current state of the art with regards the architectural style and corresponding tooling and deployment platforms. They then discuss how microservices increase the surface area of where sensitive information can be read or manipulated, but also have the potential to create systems that are more secure.
Why listen to this podcast:
- Different organisations have different risk appetites for new technology, so what may be appropriate for one organisation may not be appropriate technology choices for another.
- If you are deploying micro services then you need to know why you are doing it and what benefits you expect to get from deploying them.
- Micro services are defined by their independently deployable units rather than their size.
- Using a cryptographic token that is verifiable off line is a common pattern for passing authentication contexts around to different services.
- Serverless architectures redeuce the need to monitor server patching but does not diminish the need for monitoring application runtime or library dependencies from security patching.
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8/18/2017 • 35 minutes, 56 seconds
Jessica Kerr on Productivity, Slack Chatbots, Yak Shaving, & Why Diversity Matters for Innovation
Wesley Reisz talks with Jessica Kerr about her focus on developer productivity. Topics include her work at Atomist building Slack Chatbots, an approach to categorizing Yak Shaving (in an effort to prioritize and automate development dependencies), how an innovation culture drives diversity, and, finally, the role of 10x developers in the lifecycle of a company or product.
Why listen to this podcast:
- There are five kinds of Yak to shave
- Atomist uses a Slack chatbot to automate and track commits, builds, push requests etc.
- Agile retrospectives are a great way to encourage an innovation culture
- Diverse teams flourish in innovation cultures
- 10x developers are great for launching products, but teams are needed as products scale up
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8/11/2017 • 33 minutes, 26 seconds
Martin Hadley on R and the modern R ecosystem
Werner Schuster talks to Martin Hadley, data scientist at University of Oxford. They discuss the state of the R language, the rich R ecosystem that covers development (RStudio), notebooks for publication (R Notebooks, RPubs), writing web apps (Shiny), and the pros/cons of the different data frames implementations.
Why listen to this podcast:
- R is the tool for working with rectangular data
- Modern data frame implementations are Tibble and data.table (for large amounts of data)
- RMarkdown and R Notebooks allow to explore data and then publish it the results and (interactive) visualization
- Use Shinyapps to publish server side R applications
- Tidyverse is the place to look for modern R packages
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7/21/2017 • 26 minutes, 49 seconds
Pony Language Designer Sylvan Clebsch on Pony’s Design, Garbage Collection, and Formal Verification
In this podcast Charles Humble talks to Sylvan Clebsch, who is the designer of the actor-model language Pony programming and now works at Microsoft Research in Cambridge in the Programming Language Principles group. They talk about the inspirations behind Pony, how the garbage collector avoids stop-the-world pauses, the queuing systems, work scheduler, and formal verification.
Why listen to this podcast:
* Pony scales from a Raspberry Pi through a 64 core half terabyte machine to a 4096 core SGI beast
* An actor has a 256-byte overhead, so creating hundreds of thousands of actors is possible
* Actors have unbounded queues to prevent deadlock
* Each actor garbage collects its own heap, so global stop-the-world pauses are not needed
* Because the type system is data-race free, it’s impossible to have concurrency problems in Pony
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7/7/2017 • 34 minutes, 7 seconds
Kotlin Lead Language Designer Andrey Breslav on Android Support, Language Features and Future Plans
Why listen to this podcast:
- Kotlin is an officially supported language on Google Android platforms
- Kotlin Native and Kotlin JS will allow code reuse between server, client and mobile devices
- Type safety means that references can be checked for nullability Great tooling is a driver in what kind of language features are (and aren’t) adopted
- Coroutines provide a way of creating maintainable asynchronous systems
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6/22/2017 • 29 minutes, 4 seconds
Sid Anand on Building Agari’s Cloud-native Data Pipelines with AWS Kinesis and Serverless
Wesley Reisz talks to Sid Anand, a data architect at cybersecurity company Agari, about building cloud-native data pipelines. The focus of their discussion is around a solution Agari uses that is built from Amazon Kinesis Streams, serverless functions, and auto scaling groups.
Sid Anand is an architect at Agari, and a former technical architect at eBay, Netflix, and LinkedIn. He has 15 years of data infrastructure experience at scale, is a PMC for Apache Airflow, and is also a program committee chair for QCon San Francisco and QCon London.
Why listen to this podcast
- Real-time data pipeline processing is very latency sensitive
- Micro-batching allows much smaller amounts of data to be processed
- Use the appropriate data store (or stores) to support the use of the dataIngesting data quickly into a clean database with minimal indexes can be fast
- Communicate using a messaging system that supports schema evolution
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6/9/2017 • 25 minutes, 38 seconds
Sachin Kulkarni Describes the Architecture Behind Facebook Live
Wesley Reisz talks to Sachin Kulkarni, Director of Engineering at Facebook, about the engineering challenges for Facebook live, and how it compares to the video upload platform at Facebook.
Why listen to this podcast:
- Facebook Infrastructure powers the board family of apps including the Facebook app, Messenger and Instagram. It is largely a C++ shop. There is some Java and Python, and the business logic is all done in PHP. The iOS apps are written in Objective C and the Android apps are in Java.
- The video infra team at Facebook builds the video infrastructure across the whole company. Projects include a distributed video encoding platform which results in low latency video encoding, video upload and ingest.
- Facebook Live does encoding on both the client and the server. The trade-off between encoding on the client side and the server side is mostly around the quality of the video vs. latency and reliability.
- Facebook gets around 10x speed-up by encoding data in parallel compared to serial.
- They also have an AI-based encoding system which resulted in 20% smaller files than raw H.264.
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5/26/2017 • 31 minutes, 38 seconds
Martijn Verburg on the JCP EC “No” Vote for the Java Modules
Wesley Reisz talks to Martijn Verburg, co-founder of the London Java Community and CEO of jClarity, about the JCP EC “no” vote on the Java Platform Module System (JPMS), which is due to be shipped as part of Java 9. The talk about what JPMS offers, how it works, what the no vote means and what happens next.
Why listen to this podcast:
- Jigsaw isn’t dead
- The “no” vote was based on the submission being a bit early, and without expert group consensus that it should be submitted
- Since the vote started, several amendments have been made which addressed some of the concerns listed by those who voted “no”
- Daily calls with the expert group and interested parties will work to resolve the outstanding issues promptly
- A resubmission is due within 30 days with a future vote expected to go through
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5/19/2017 • 22 minutes, 35 seconds
Daniel Bryant on Microservices and Domain Driven Design
Wesley Reisz talks to Daniel Bryant on moving from monoliths to micro-services, covering bounded contexts, when to break up micro-services, event storming, practices like observability and tracing, and more.
Why listen to this podcast:
- Migrating a monolith to micro-services is best done by breaking off a valuable but not critical part first.
- Designing a greenfield application as micro-services requires a strong understanding of the domain.
- When a request enters the system, it needs to be tagged with a correlation id that flows down to all fan-out service requests.
- Observability and metrics are essential parts to include when moving micro-services to production.
- A service mesh allows you to scale services and permit binary transports without losing observability.
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5/12/2017 • 36 minutes, 35 seconds
Rossen Stoyanchev on Reactive Programming with Spring 5 and Spring WebFlux
Rossen Stoyanchev talks to Wesley Reisz about blocking and non-blocking architectures, upcoming changes in Spring including Spring WebFlux, the reactive web stack in Spring framework 5, due this summer. He also discusses the differences between rxJava and Reactor.
Why listen to this podcast:
- Spring Framework 5 is due to be released June 25 2017
- Spring Web Flux provides a web programming model designed for asynchronous APIs
- Back-pressure is important in a server environment; less so within a UI environment
- It’s possible to use a Spring Web Flux client within a Spring MVC applciation
- Managing sets of thread pools is more complicated than having a scalable asynchronous system
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5/5/2017 • 34 minutes, 18 seconds
Richard Feldman Discusses Elm and How It Compares to React.js for Front-end Programming
Why listen to this podcast:
- Using a compiler to catch errors at compile time instead of at runtime means much easier refactoring of code.
- Incrementally replacing small parts of an existing JavaScript application with Elm is a safer strategy than trying to write an entirely new application in Elm
- Elm packages are semantically versioned and gated by the publishing process, so minor versions cannot remove functionality without bumping the major version.
- The UI in an Elm application results in messages that transform the immutable state of the application; this allows a debugger to view the state transitions and the messages that triggered them, including record and replay of those messages.
- Elm has been benchmarked as being faster than Angular and React whilst being smaller code, which is attributed to the immutable state and pure functional elements.
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4/28/2017 • 39 minutes, 59 seconds
Jean Barmash on Inter-Service RPC with gRPC/Thrift, Designing Public APIs, & Lean/Constraint Theory
Jean Barmash is Director of Engineering at Compass, Founder & Co-Organizer, NYC CTO School Meetup. Live in New York City. He has over 15 years of experience in software industry, and has been part of 4 startups over the last seven years, 3 as CTO / VPE and one of which he co-founded. Prior to his entrepreneurial adventures, Jean held a variety of progressively senior roles in development, integration consulting, training, and team leadership. He worked for such companies as Trilogy, Symantec, Infusion and Alfresco, consulting to Fortune 100 companies like Ford, Toyota, Microsoft, Adobe, IHG, Citi, BofA, NBC, and Booz Allen Hamilton.
Jean will speak at QCon New York 2017: http://bit.ly/2nN7KKo
Why listen to this podcast:
- The Compass backend is mostly written in Java and Python, with Go increasingly a first class language. The main reason for Go being added was developer productivity.
- The app is based on a Microservices architecture with around 40-50 services in total.
- Binary RPC, originally Thrift and Finagle, is used as the communication protocol, but the company is gradually moving to gRPC still with Thrift. One advantage that gRPC offers is better Python support than Finagle.
- The company has built a code generation framework which takes Thrift and converts it to a RESTful API for clients to consume.
- Constraint theory is about how you manage the one constraint in a system or team that prevent you increasing throughput; for example if your software engineering team only has one front end engineer do you ask back-end engineers to pick off some front-end tasks, or bring in a contractor.
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4/14/2017 • 32 minutes, 10 seconds
Eric Horesnyi on High Frequency Trading and how Hedge Funds are Applying Deep Learning to Markets
Eric Horesnyi, CEO @streamdata.io, talks to Charles Humble about how hedge funds are applying deep learning as an alternative to the raw speed favoured by HFT to try and curve the market.
Why listen to this podcast:
- Streamdata.io was originally built for banks and brokers, but more recently hedge funds have begun using the service.
- Whilst Hedge Funds like Renaissance Technologies have been using mathematical approaches for some time deep learning is now being applied to markets. Common techniques such as gradient descent and back propagation apply equally well to market analysis.
- The data sources used are very broad. As well as market data the network might be using, sentiment analysis from social networks, social trading data, as well as more unusual data such as retail data, and IoT sensors from farms and factories.
- By way of contrast High Frequency Trading focusses on latency. From an infrastructure stand-point you can play with propagation time, Serilization (the thickness of the pipe), and Processing time for any active component in chain.
- One current battleground in HFT is around using FPGA to build circuits dedicated to feed handlers. Companies such as Novasparks are specialists in this area.
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3/24/2017 • 30 minutes, 29 seconds
Greg Murphy on Gamesparks, Game Tuning and Orchestrating Deployment Across Three Cloud Providers
Greg Murphy is the COO of Gamesparks, a cloud-based platform providing and a rich mobile back-end service for game developers to engage with their users. Greg takes us inside Gamesparks discussing the architecture, machine learning and what it’s like to launch in the China market.
Why listen to this podcast:
Gamesparks
Engagement Engine
Tuning the Gaming Experience
The Architecture
SDK’s and Real-time Data Transfers
Server-side Scripts
Managing Noisy neighbours and Security
The Developer Experience
Deploying Across Three Cloud Providers
Machine Learning
The China Market
Notes and links can be found on: http://bit.ly/2neCjEV
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3/10/2017 • 30 minutes, 29 seconds
Architecting SQL Server on Linux: Slava Oks on Drawbridge, LibOS, & Addressing Between Windows/Linux
Wesley Reisz talks to Slava Oks, who has worked at Microsoft for over 20 years on flagship products, including SQL Server. He also led the kernel team who worked on the Midori operating system. More recently, he has worked on bringing SQL Server to Linux.
Why listen to this podcast:
- Microsoft SQL Server runs on Linux through a containerised approach called Drawbridge
- Drawbridge implements a Linux loader and a minimal set of ABI calls to allow an in-process NT user mode kernel to run
- SQL Server runs on top of a SQL platform layer (called SQL OS) that could be ported to run on Drawbridge
- SQL Server had supportability commands added to allow the state of the system to be measured with SQL calls
- A number of efficiency gains were applied to both the Drawbridge components and the SQL Server code to bring performance to within 20% of the equivalent process running on Windows
Notes and links can be found on: http://bit.ly/2kVfatX
Drawbridge
ABIs
Security
LibOS
Linux
SQL OS
Supportability
Some assembly required
Addressing
Performance
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2/24/2017 • 30 minutes, 17 seconds
Jonas Bonér on the Actor Model, Akka, Reactive Programming, Microservices and Distributed Systems
Jonas Bonér, CTO of LightBend and creator Akka, discusses using Akka when developing distributed systems. He talks about the Actor Model, and how every Microservice needs to be viewed as a system to be successful.
Why listen to this podcast:
- Akka is JVM-based framework design for developing distributed systems leveraging the Actor Model - an approach for writing concurrent systems that treat actors as universal primitives and the most successful model with abstraction has been streaming
- Circuit breakers in Akka are a backup and retry policy; they protect you by capturing failure data and allow you to roll back
- Every Microservice needs to be viewed as a system, it needs to have multiple parts that run on different machines in order to function and be fully resilient - thus is a Microsystem
- Two different trends have emerged when it comes to hardware and environments: one is the trend toward Multi-core, the is a movement toward virtualized environments and the cloud
- Saga pattern of managing long running transactions in a distributed system fits very well with messaging style architectures
Notes and links can be found on: http://bit.ly/2kwB2eB
Akka
The Actor Model
When Akka and the Actor Model is the perfect choice
Circuit breakers patterns in distributed systems
Two trends toward Multi-core
Reactive Manifesto
Event Driven vs. Message Driven
Reactive Programming and Streams
Microliths to Microsystems
What do you have to get right before you start trying to deploy a distributed systems?
Working with ML / AI at Lightbend to understand tracing through distributed system
Saga Pattern
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2/16/2017 • 38 minutes, 43 seconds
Peter Bourgon on Gossip, Paxos, Microservices in Go, and CRDTs at SoundCloud
Peter Bourgon discusses his work at Weaveworks, discovering and imlemeting CRDTs for time-stamped events at Soundcloud, Microservices in Go with Go Kit and the state of package management in Go.
Why listen to this podcast:
- We’ve hit the limits of Moore’s law so when we want to scale we have to think about how we do communication across unreliable links between unreliable machines.
- In an AP algorithm like Gossip you still make forward progress in case of a failure. In Paxos you stop and return failures.
- CRDTs give us a rigours set of rules to accommodate failures for maps, sets etc. in communication that result in am eventually consistent system.
- Go is optimised to readers/maintainers vs. making the programmers’ life easier. Go is closer to C than Java in that it allows you to layout memory very precisely, allowing you to, for example, optimise cache lines in your CPU.
- Bourgon started a project called Go Kit, which is designed for building microservices in Go. It takes inspiration from Tiwtter’s Scala-based Finagle which solved a lot of Micoservice concerns.
- Go has a number of community-maintained package managers but no good solution; work in ongoing to try and resolve this.
Notes and links can be found on: http://bit.ly/2kaHC9k
Work at Weaveworks
Gossip vs. Paxos
CRDTs at SoundCloud
Go
Go in large teams
Go and Java package management
Microservices in Go with Go Kit
Logging and tracing in a distributed environment
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1/27/2017 • 40 minutes, 14 seconds
Neha Batra - Pivotal Labs Pair Programming
In this week’s podcast Wes Reisz talks to Neha Batra, a software engineer at Pivotal Labs. Neha spoke about pair programming in her recent QCon San Francisco 2016 presentation, and has taken time to discuss techniques to get started with the practice as well as tips for implementing it on your team. Neha also touches on vulnerability based trust and how it can help effectively build a trusting team environment.
Why listen to this podcast:
- If you successfully start with pair programming, other tenants of XP are pulled along with you
- Ways to get creative with remote pairing to make it work
- The daily retro
- Overcoming hesitance with managers when trying to implement pair programming full time
- Vulnerability based trust building
Notes and links can be found on: http://bit.ly/2i2a0sJ
How has Pair Programming Evolved Over the Years?
6m:17s - A lot of the fundamentals are the same, but with XP we take it to the extreme to be able to do it eight hours a day.
6m:24s - To pair for eight hours a day we adapt to a lot of other process to create a simpler way of working, giving us an easier level to default to.
6m:44s - We use phrases in the team to make sure we agree on a test, that there are no false positives, when to refactor etc. This helps us avoid accruing code debt since we don’t do code reviews.
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1/6/2017 • 28 minutes, 40 seconds
Oliver Gould About Architecting to Avoid and Recover from Failure
In this week’s podcast, Robert Blumen talks to Oliver Gould at QCon San Francsico 2016. Oliver is the CTO of Buoyant where he leads open source development efforts. Prior to Buoyant he was a Staff Infrastructure Engineer at Twitter where he was technical lead on Observability, Traffic, Configuration and Co-ordination teams.
Why listen to this podcast:
- Stratification allows applications to own their logic while libraries take care of the different mechanisms, such as service discovery and load balancing
- Cascading failures can’t be tested or protected against, so having a fast time to recovery is important
- Having developers own their services with on-call mechanisms improves the reliability of the service; it’s best to optimise automatic restarts so problems can be addressed during normal working hours
- Post mortem analysis of failures are important to improve run books or checklists and to share learning between teams
- Incremental roll out of features with feature flags or weighted routing provides agility while testing with production load, which highlights issues that aren’t seen during limited developer testing
Notes and links can be found on: http://bit.ly/2ivoz9w
4m:05s - Each domain has different failure and operating modes, and the layered approach to resiliency means that the layer handles this automatically
4m:30s - Large systems may fail in unexpected ways
4m:35s - Twitter originally had the “Fail Whale” but this has been phased out as the system has become more stable
4m:50s - As Twitter grew, it needed to move quicker, with more engineers and less whale time
5m:10s - Automation and social tools were needed to improve the situation
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12/30/2016 • 33 minutes, 24 seconds
Chris Richardson on Domain-Driven Microservices Design
In this week’s podcast, Thomas Betts talks with Chris Richardson, a developer, architect, Java Champion and author of POJOs in Action. Before his workshop on Microservices w/ Spring Boot and Docker at QCon San Francisco 2016, Richardson took time to discuss his ideas on how to use DDD and CQRS concepts as a guide for implementing a robust microservices architecture.
Why listen to this podcast:
- "Microservice architecture" is a better term than "microservices". The latter suggests that a single microservice is somehow interesting
- The concepts discussed in Domain-Driven Design are an excellent guide for how to implement a microservices architecture
- Bounded Contexts correspond well to individual microservices
- Event sourcing and CQRS provide patterns for how to implement loosely coupled services
- When converting a monolith to microservices, avoid a big bang rewrite, in favor of an iterative approach
Notes and links can be found on: http://bit.ly/2hZ8TM1
11m:51s - Microservices must be loosely coupled, usually creating a model with one database per service.
12m:45s - There is a business requirement to maintain data consistency across services, and using an event driven architecture is a good way to achieve that.
13m:38s - Event sourcing is specific technique for persisting domain objects as a series of events.
14m:11s - Just as transactions don’t like to be split across microservices, queries cannot simply join across multiple data sources. CQRS provides a solution that accommodates querying via microservices and materialized views.
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12/23/2016 • 25 minutes, 26 seconds
Keith Adams on the Architecture of Slack, using MySql, Edge Caching, & the backend Messaging Server
In this week’s podcast, QCon chair Wesley Reisz talks to Keith Adams, chief architect at Slack. Prior he was an engineer at Facebook where he worked on the search type live backend, and is well-known for the HipHop VM [hhvm.com]. Adams presented How Slack Works at QCon SanFrancisco 2016.
Why listen to this podcast:
- Group messaging succeeds when it feels like a place for members to gather, rather than just a tool
- Having opt-in group membership scales better than having to define a group on the fly, like a mailing list instead of individually adding people to a mail
- Choosing availability over consistency is sometimes the right choice for particular use cases
- Consistency can be recovered after the fact with custom conflict resolution tools
- Latency is important and can be solved by having proxies or edge applications closer to the user
Notes and links can be found on: http://bit.ly/keith-adams
3m:30s Voice and video interactions are impacted by latency; the same is true of messaging clients
4m:00s The user interface can provide indications of presence, through avatars indicating availability and typing indicators
4m:15s Latency is important; sometimes the difference is between 100ms and 200ms so the message channel monitors ping timeout between server and client
4m:40s 99th percentile is less than 100ms ping time
5m:15s If the 99th percentile is more than 100ms then it may be server based, such as needing to tune the Java GC
5m:25s Network conditions of the mobile clients are highly variable
6m:20s Mobile clients can suffer intermittent connectivity
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12/16/2016 • 36 minutes, 24 seconds
Haley Tucker on Responding to Failures in Playback Features at Netflix
In this week’s podcast, Thomas Betts talks with Haley Tucker, a Senior Software Engineer on the Playback Features team at Netflix. While at QCon San Francisco 2016, Tucker told some production war stories about trying to deliver content to 65 million members.
Why listen to this podcast:
- Distributed systems fail regularly, often due to unexpected reasons
- Data canaries can identify invalid metadata before it can enter and corrupt the production environment
- ChAP, the Chaos Automation Platform, can test failure conditions alongside the success conditions
- Fallbacks are an important component of system stability, but the fallbacks must be fast and light to not cause secondary failures
- Distributed systems are fundamentally social systems, and require a blameless culture to be successful
Notes and links can be found on: http://bit.ly/2hqzQ6K
2m:05s - The Video Metadata Service aggregates several sources into a consistent API consumed by other Netflix services.
2m:43s - Several checks and validations were in place within the video metadata service, but it is impossible to predict every way consumers will be using the data.
3m:30s - The access pattern used by the playback service was different than that used in the checks, and led to unexpected results in production.
3m:58s - Now, the services consuming the data are also responsible for testing and verifying the data before it rolls out to production. The Video Metadata Service can orchestrate the testing process.
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12/9/2016 • 25 minutes, 1 second
Kolton Andrus on Lessons Learnt From Failure Testing at Amazon and Netflix and New Venture Gremlin
In this week's podcast, QCon chair Wesley Reisz talks to Kolton Andrus. Andrus is the founder of Gremlin Inc. He was a Chaos Engineer at Netflix, focused on the resilience of the Edge services. He designed and built FIT: Netflix’s failure injection service. Prior, he improved the performance and reliability of the Amazon Retail website.
Why listen to this podcast:
- Gremlin, Kolton Andrus' new start-up, is focused on providing failure testing as a service. Version 1, currently in closed beta, is focused on infrastructure failures.
- Lineage-driven Fault Injection (LDFI) allowed Netflix to dramatically reduce the number of tests they needed to run in order to explore a problem space.
- You generally want to run failure tests in production, but you can't start there. Start in developemnt and build up.
- Having failure testing at an application level, as Netflix does, so you can have request level fault injection for a specific user or a specific device.
- Being able to trace infrastructure with something like Dapper or Zipkin offers tremendous value. At Netflix, the failure injection system is integrated into the tracing system, which meant that when they caused a failure they could see all the points in the system that it touched.
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12/2/2016 • 28 minutes, 31 seconds
Preslav Le on How Dropbox Moved off AWS and What They Have Been Able to Do Since
As InfoQ previously reported in March 2016, Dropbox announced that they had migrated away from Amazon Web Services (AWS).
In this week's podcast Robert Bluman talks to Preslav Le. Preslav has been a software engineer at Dropbox for the past three years, contributing to various aspects of Dropbox’s infrastructure including traffic, performance and storage. He was part of the core oncall and storage oncall rotations, dealing with high emergency real world issues, from bad code pushes to complete datacenter outages.
Why listen to this podcast:
- Dropbox migrated away from Amazon S3 to their own data centres to allow them to optimise for their specific use case.
- They are experimenting with Shingled Magnetic Recording (SMR) drives for primary storage to increase storage density. All writes go to an SSD cache and then get pushed asynchronously to the SMR disk.
- Their average block size is 1.6MB with a maximum block size of 4MB. Knowing this allows the team to tune their storage system.
- Three languages are used for the backend infrastructure. Python is used mainly for business logic, Go is the primary language used for heavy infrastructure services, and in some cases, for example where more direct control over memory is needed, Rust is also used.
- Dropbox invest very heavily in verification and automation. A verifier scans every byte on disk and checks that it matches the checksum in the index.
- Verification is also used to check that each box has the block keys it should have.
Notes and links can be found on http://bit.ly/preslav-le
Dropbox’s motivation for moving off the cloud
2:40 - Dropbox used Amazon S3 and other services where it made sense, but they stored all the metadata in their own data centres.
3:30 - Initially this was done because Amazon had poor support for persistent storage at the time. This has since improved but it didn’t make sense for dropbox to move the metadata back.
4:01 - By that time the dropbox team was ready to tackle the storage problem and built their own in-house replacement for S3, called Magic Pocket. Magic Pocket allowed Dropbox to move away from Amazon altogether.
4:30 - The move saved money, but also allowed DropBox to optimise for their specific use case and be faster.
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11/18/2016 • 26 minutes, 16 seconds
Randy Shoup on Stitch Fix's Technology Stack, Data Science and Microservices
In this week's podcast QCon chair Wesley Reisz talks to Randy Shoup. Shoup is the vice president of engineering at Stitch Fix. Prior to Stitch Fix, he worked for Google as the director of engineering and cloud computing, CTO and co-founder of Shopilly, and chief engineer at Ebay.
Why listen to this podcast:
- Stitch Fix's business is a combination of art and science. Humans are much better with the machines, and the machines are much better with the humans.
- Stitch Fix has 60 engineers, with 80 data scientists and algorithm developers. This ratio of data science to engineering is unique.
- With Ruby-on-Rails on top of Postgres, the company maintains about 30 different applications on the same stack.
- The practice of Test Driven Development makes Continuous Delivery work, and the practice of having the same people build the code as those who operate the code makes both of these things much more powerful.
- Microservices gives feature velocity, the ability for individual teams to move quickly and independently of each other, and independent deployments.
- Microservices solve a scaling problem. They solve an organisational scaling problem, and a technological scaling problem. These are not the problems that you have early on in the startup.
- In the monolithic world, if you're not able to continue to vertically scale the application or the database or whatever your monolith is. And so for scaling reasons alone you might consider breaking it up into what we call microservices.
Notes and links can be found on http://bit.ly/randy-shoup-podcast
Data Science and Stitch Fix
1m:57s - Stitch Fix re-imagines retail, particularly for clothing. When you sign up, you fill out survey of the kinds of things that you like and you don't like, and we choose what we think you're going to enjoy based on the millions of customers that we have already. And we use a ton of data science in that process.
3m:00s - That goes into our algorithms and then our algorithms make personalised recommendations based on all the things we know about our other customers... there's a human element as well: we have 3,200 human stylists that are all around the United States and they choose the five items that go into the box [of clothing].
3m:29s - What we like is that this is a combination of art and science. Modern companies combine what machines are really good at, such as chugging through the 60 to 70 questions times the millions of customers, and combining that with the human element of the stylists, figuring out what things go together, what things are trending, what things are appropriate... Humans are much better with the machines, and the machines are much better with the humans.
[...]
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11/11/2016 • 26 minutes, 8 seconds
Tal Weiss on Observability, Instrumentation and Bytecode Manipulation on the JVM
In this week's podcast, QCon chair Wesley Reisz talks to Tal Weiss, CEO of OverOps, recently re-branded from Takipi. The conversation covers how the OverOps product works, explores the difference between instrumentation and observability, discusses bytecode manipulation approaches and common errors in Java based applications.
A keen blogger, Weiss has been designing scalable, real-time Java and C++ applications for the past 15 years. He was co-founder and CEO at VisualTao which was acquired by Autodesk in 2009, and also worked as a software architect at IAI Space Industries focusing on distributed, real-time satellite tracking and control systems.
Why listen to this podcast:
- OverOps uses a mixture of machine code instrumentation and static code analysis at deployment time to build up an index of the code
- Observability is how you architect your code to be able to capture information from its outputs. Instrumentation is where you come in from the outside and use bytecode or machine code manipulation techniques to capture information after the system has been designed and built.
- Bytecode instrumentation is a technique that most companies can benefit from learning a bit more about. Bytecode isn’t machine code - it is a high-level programming language. Being able to read it really helps you understand how the JVM works.
- There are a number of bytecode manipulation tools you can use to work with bytecode - ASM is probably the most well known.
- A fairly small number of events within an application’s life-cycle generate the majority of the log volume. A good practice is to regularly review your log files to consider if what is being logged is the right thing.
Notes and links can be found on http://bit.ly/2fInGsW
SaaS vs On-Premise
5:43 - OverOps started as a SaaS product, but given that a lot of the data it collects is potentially sensitive, they introduced a new product called Hybrid. Hybrid separates the data into two independent streams: data and metadata.
6:42 - The data stream is the raw data that is captured which is then privately encrypted using 256 bit AES encryption keys which are only stored on the production machine and by the user when they need to decrypt it. The metadata stream is not sensitive since it is just an abstract mathematical graph.
7:18 - Because the data stream is already privately encrypted, that stream can be stored behind a firewall and never needs to leave a company’s network.
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11/4/2016 • 28 minutes, 53 seconds
Cathy O'Neil on Pernicious Machine Learning Algorithms and How to Audit Them
In this week's podcast InfoQ’s editor-in-chief Charles Humble talks to Data Scientist Cathy O’Neil. O'Neil is the author of the blog mathbabe.org. She was the former Director of the Lede Program in Data Practices at Columbia University Graduate School of Journalism, Tow Center and was employed as Data Science Consultant at Johnson Research Labs. O'Neil earned a mathematics Ph.D. from Harvard University. Topics discussed include her book “Weapons of Math Destruction,” predictive policing models, the teacher value added model, approaches to auditing algorithms and whether government regulation of the field is needed.
Why listen to this podcast:
- There is a class of pernicious big data algorithms that are increasingly controlling society but are not open to scrutiny.
- Flawed data can result in an algorithm that is, for instance, racist and sexist. For example, the data used in predictive policing models is racist. But people tend to be overly trusting of algorithms because they are mathematical.
- Data scientists have to make ethical decisions even if they don’t acknowledge it. Often problems stem from an abdication of responsibility.
- Auditing for algorithms is still a very young field with ongoing academic research exploring approaches.
- Government regulation of the industry may well be required.
Notes and links can be found on http://bit.ly/2eYVb9q
Weapons of math destruction
0m:43s - The central thesis of the book is that whilst not all algorithms are bad, there is a class of pernicious big data algorithms that are increasingly controlling society.
1m:32s - The classes of algorithm that O'Neil is concerned about - the weapons of math destruction - have three characteristics: they are widespread and impact on important decisions like whether someone can go to college or get a job, they are somehow secret so that the people who are being targeted don’t know they are being scored or don’t understand how their score is computed; and the third characteristic is they are destructive - they ruin lives.
2m:51s - These characteristics undermine the original intention of the algorithm, which is often trying to solve big society problems with the help of data.
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9/16/2016 • 31 minutes, 32 seconds
John Langford on Vowpal Wabbit, Used by MSN, and Machine Learning in Industry
In this week's podcast QCon chair Wesley Reisz talks to Machine learning research scientist John Langford. Topics include his Machine Learning system Vowpal Wabbit, designed to be very efficient and incorporating some of the latest algorithms in the space. Vowpal Wabbit is used for news personalisation on MSN. They also discuss how to get started in the field and it’s shift from academic research to industry use.
Why listen to this podcast:
- Vowpal Wabbit is a ML system that attempts to incorporate some of the latest machine learning algorithms.
- How to learn ML: take a class or two, get accustomed with learning theory and practice.
- ML has moved from the research field into the industry, 4 out of 9 ICML tutorials coming from the industry.
- It’s hard to predict when you have enough data.
- AlphaGo is a milestone in artificial intelligence. It uses reinforcement learning, deep learning and existing moves played by Go masters.
- Deep Learning is currently a disruptive technology in areas such a vision or speech recognition.
- What’s trendy: Neural Networks, Reinforcement and Contextual Learning.
- Machine Learning is being commoditized.
Notes and links can be found on http://bit.ly/2b4YNqQ
How to Approach Machine Learning
6m:12s To start learning Machine Learning, Langford recommends taking a class or two, mentioning the course by Andrew Ng and another course by Yaser S. Abu-Mostafa.
6m:50s It is recommended to get accustomed with learning theory to avoid some of the rookie's mistakes.
Quick scan our curated show notes on InfoQ. http://bit.ly/2atBFgk
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8/19/2016 • 23 minutes, 35 seconds
Shuman Ghosemajumder on Security and Cyber-Crime
In this week's podcast, professor Barry Burd talks to Shuman Ghosemajumder. Ghosemajumder is VP of product management at Shape Security and former click fraud czar for Google. Ghosemajumder is also the co-author of the book CGI Programming Unleashed, and was a keynote speaker at QCon New York 2016 presenting Security War Stories.
Why listen to this podcast:
With more of our lives conducted online through technology and information retrieval systems, the use of advanced technology gives criminals the opportunity to be able to do things that they weren't able to do.
- Cyber-criminals come from all over the world and every socioeconomic background, so long as there's some level of access to computers and technology.
- You see organised cyber-crime focusing on large companies because of the fact that they get a much greater sense of efficiency for their attacks.
- Cyber-criminals are getting creative, and coming up with ways to interact with websites we haven't thought of before.
- You can have very large scale attacks that are completely invisible from the point of view of the application that's being attacked.
- The context of what are you are using software for is more important than just going through an understanding of the code level vulnerability.
Notes and links can be found on http://bit.ly/2atBFgk
The People Behind Cyber-Crime
5:28 - There are all kinds of different personalities and demographics involved. Cyber-criminals come from all over the world and every socioeconomic background, so long as there's some level of access to computers and technology. Even in cases where a cyber criminal doesn't know how to use technology directly, or how to create something like a piece of malware, they can still be involved in a cyber-criminal's scheme.
6:29 - A scheme which uses large groups of individuals and which doesn’t necessarily need to have skills itself, is stealing money from bank accounts. Being able to transfer money using malware on people’s machines from one account to another account that the cyber-criminal controls still involves getting that money out. That last step can involve a set of bank accounts that are assigned to real individuals.
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8/1/2016 • 43 minutes, 15 seconds
Caitie McCaffrey on Engineering Effectiveness, Diversity, & Verification of Distributed Systems
In this week's podcast, QCon chair Wes Reisz and Werner Schuster talk to Caitie McCaffrey. McCaffrey works on distributed systems with the engineering effectiveness team at Twitter, and has experience building the large scale services and systems that power the entertainment industry at 343 Industries, Microsoft Game Studios, and HBO. McCaffrey's presentation at QCon New York was called The Verification of a Distributed System.
Why listen to this podcast:
- Twitter's engineering effectiveness team aims to help make dev tools better, and make developers happier and more efficient.
- Asking someone to speak at your conference or join your team solely because of their gender does more harm than people think.
- There is not one prescriptive way to make good, successful technology.
- Even when we don't have time for testing, there are options to increase your confidence in your system.
- The biggest problem when running a unit test is that it is only testing the input you hard code into the unit test.
Notes and links can be found on http://bit.ly/2al6BRp
Engineering Effectiveness
1:24 - The purpose of the engineering effectiveness team is to help make dev tools better, and to make Twitter's developers happier and more efficient.
2:44 - The team is trying to make infrastructure so that not every team has to solve the distributed problem on their own, and give developers some APIs and tools so that they can build systems easily.
More on this:
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7/22/2016 • 33 minutes, 11 seconds
Wendy Closson on Mindfulness and Algorithmic Approaches to Communicating
In this week's podcast, Barry Burd talks with Wendy Closson. With over a decade of experience immersed in development and championing agile practices, Closson coaches technology leaders to manage effectively, respond reasonably, and navigate the choppy waters of business. Closson's presentation at QCon New York was entitled Syntactic Sugar for English: Pragmatic Eloquence.
Why listen to this podcast:
- Software is a very abstract experience, so it can be difficult to communicate ideas about software to people outside.
- The majority of people in teams want to remain in their comfort zone, so don't want to change.
- Many problems that may seem technical in nature have to do with outside experiences.
- The algorithmic approach to communicating has to do with creating new habits around our speaking.
- With a single word you can elevate a population or destroy a friendship.
- Simplicity is divinity, where someone can look at your code and understand your intentions, and the same in real-life communication.
- Compromise isn't always the best thing. If no one's really feeling passionate about it, that's not going to create the best code.
Notes and links can be found on http://bit.ly/29Co4X2
How Understanding Developers Helps Coaching
1:20 - Software is a very abstract experience. It doesn't really live in the physical word, so it can be difficult to communicate ideas about software - using it or creating it - to people outside the software world.
1:58 - It's possible to manage without direct experience... When you think of your job as a service leadership job. It's your job to facilitate, to trust, to understand what people are saying. But without the background, that trust can be hard to keep; a lot of things can get lost in translation.
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7/12/2016 • 36 minutes, 15 seconds
Courtney Hemphill on VR, Augmented Reality, and the Importance of Animation in UX
In this week's podcast, Barry Bird talks to Courtney Hemphill, a partner and tech lead at Carbon Five. With over ten years of experience in software development, Hemphill has done full stack development for both startup and enterprise companies. Hemphill's presentation at QCon New York was entitled Algorithms for Animation.
Why listen to this podcast:
- Why developers in startups or enterprise firms should care about creating animations
- The interfaces we interact with in software are becoming more dynamic
- If you don't know what's wrong, you don't know how to fix it
- The most common code smells, according to Llewellyn Falco: Clutter, long lines, long methods, duplication, and inconsistency
- How do we make- in an agile way- the architectural work visible, and not ignore it?
- How do you have an incremental architecture and get measurements? If you say you're going to go away for six months and figure it out, that's not very measurable.
Notes and links can be found on InfoQ: http://bit.ly/29kq2ds
Why Developers Should Care About Creating Animations
1m:05s - The interfaces we interact with in software are becoming more dynamic.
1m:30s - We are moving closer to natural user interfaces, and this is something software engineers across the board need to consider when they are developing programs. You don't just have a pointer and a mouse and a keyboard- you can squish and stretch things, using your fingers and your hands.
1m:55s - Animations need to feel real, and that is all based in Math and Physics.
2m:15s - The animations you see on websites have always been an opportunity for us to have a more fundamental learning about what the program does without needing a lot of instruction.
2m:38s - Animation functions almost as a way for people to discover and explore an interface so they can interact and engage with it more easily.
The Importance of Animation Resembling Reality
3m:00s - If you've ever put on an Oculus Rift and experienced "judder" and felt immediately sick, that's the most extreme version.
3m:31s - If a computer is running slowly and you see frames dropped, you are sensing something underlying that is not right, and you immediately distrust it.
3m:42s - The further away you get from something that is smooth, the more you start to mistrust the platform and the data behind it.
Natural Textures vs Cartoon-Like Textures [...]
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7/1/2016 • 38 minutes, 54 seconds
James Shore, Llewellyn Falco, and Rebecca Wirfs-Brock on TDD and Architecture
In this week's podcast Richard Seroter talks to James Shore, author of The Art of Agile Development and one of the original signatories of the Agile Manifesto. Also on the podcast are Llewellyn Falco, creator of the open source testing tool ApprovalTests and co-founder of Teaching Kids Programming, and Rebecca Wirfs-Brock, inventor of Responsibility-Driven Design, as well as the author of books including Designing Object: Oriented Software and Object Design: Roles, Responsibilities and Collaborations.
Why listen to this podcast:
- A lot of people know how to do TDD and refactoring for the back end, but not for the font, but the basics are the same.
- The basics of Test-Driven Development are the same for the front or back end.
- If you don't know what's wrong, you don't know how to fix it.
- The most common code smells, according to Llewellyn Falco: Clutter, long lines, long methods, duplication, and inconsistency.
- How do we make, in an agile way, the architectural work visible, and not ignore it?
- How do you have an incremental architecture and get measurements? If I say to you I'm going to go away for six months and figure it out, that's not very measurable.
Notes and links can be found on InfoQ: http://bit.ly/1Pse2r1
1m:10s - The talk 'Agile Engineering for the Web' was about how do you bring typical Agile engineering ideas like TDD and refactoring to the front-end languages.
1m:33s - A lot of people know how to do these things on the back-end, but when you get to the front end a lot of people just throw up their hands.
2m:24s - I see CSS bugs all the time, because it's very hard to refactor CSS without breaking something.
Quick scan our curated show notes on InfoQ. http://bit.ly/1Pse2r1
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6/3/2016 • 30 minutes, 15 seconds
Lisa Crispin and Justin Searls on Testing and Innovation in Front End Technology
In this week's podcast Richard Seroter talks to Lisa Crispin who works on the tracker team at Pivotal Labs, and is an organiser of the Agile Alliance Technical Conference. Lisa is the co-author of several books on Agile Testing, and is also the 2012 recipient of the Agile Testing Days award for Most Influential Agile Testing Professional Person.
Richard also talks to Justin Searls, software craftsman, presenter of "How to Stop Hating Your Tests" and co-founder of Test Double, a company whose goal is to "improve how the world writes software."
Why listen to this podcast:
- Agile is mainstream, and being adopted by big enterprises, but there's a place to help small companies and startups.
- Cloud Foundry pair testers to write production code with the programmers.
- Developers have to be focused on right now, testers have freedom to look at more of the big picture
- People know testing is good and there a lot of tools for it, but some tools are ill-conceived.
- We need a better language for talking about good QA and full stack testing.
Notes and links can be found on InfoQ: http://bit.ly/1U0ip8Q
2m:00s - The first XP universe conferences were mainly about XP practices, values and principles, and were attended by developers
2m:17s - Over time, topics moved towards processes and frameworks, and the number of developers who attend Agile conferences has gone down dramatically.
3m:51s - Now Agile is mainstream, it's being adopted by big enterprises, but there's a place to help small companies and startups. That's usually where the innovation comes from, and the Agile Alliance wants to encourage innovation.
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5/27/2016 • 29 minutes, 2 seconds
GILT VP Heather Fleming on Unlocking the "Secret Sauce" of Great Teams
In this week's podcast QCon chair Wesley Reisz talks to Heather Fleming, who is the VP of product and program management at GILT, where she is responsible for not only the customer-facing website, but also back office things from distribution to order processing.
Why listen to this podcast:
- GILT treats every person as an individual, with a skillset that is outside their responsibilities.
- You should be able to be your authentic self wherever you are.
- Google found creating a psychologically safe work environment was key to high performing teams.
- You can kill a great team by taking away their autonomy and empowerment.
- Great engineers that want to be managers are fearful of losing their skill, and great engineers that don't want to be managers are put in those roles and are terrible managers.
Notes and links can be found on InfoQ: http://bit.ly/1U2Wgq9
1m 49s - One of the things that makes the culture at GILT so special is the "ingredients framework" that considers every person an individual, with a skillset that is outside what their title might say and what their role and responsibilities might be.
3m 29s - One of the team ingredients is called "motivator" - the ability to make sure that the team understands what they're working on, and more importantly the "why" and how it's driving business or customer value.
4m 35s - The relationship you have with your co-workers should be deeper than many of us are allowing them to be, because they are like your second family.
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Attend Heather Fleming's session at QCon New York 2016, Jun 13-17: http://bit.ly/1U2f3og
5/20/2016 • 15 minutes, 31 seconds
Uber's Chief Systems Architect on their Architecture and Rapid Growth
In this week's podcast QCon chair Wesley Reisz talks to Matt Ranney who is the Chief Systems Architect at Uber, where he's helping build and scale everything he can.
Why listen to this podcast:
- Expanding a company and team at this rate is genuinely hard. Lots of mistakes have been made along the way.
- Microservices allow companies to grow rapidly but have a cost in terms of aggregate velocity.
- Uber is gradually moving its marketplace development from Node.js to Go and Java. Java is used for the map services.
- Aggressive failure testing is used extensively in Uber.
- Some early design choices - like using JSON over HTTP - make formal verification basically impossible.
Notes and links can be found on InfoQ: http://bit.ly/1TH8app
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Attend Matt Ranney's session at QCon New York 2016, Jun 13-17: http://bit.ly/1TH75ht
5/13/2016 • 31 minutes, 28 seconds
Mads Torgersen on C# 7 and Beyond
Summary: In this week's podcast QCon chair Wesley Reisz talks to Mads Torgersen who leads the C# language design process at Microsoft, where he has been involved in five versions of C#, and also contributed to TypeScript, Visual Basic, Roslyn and LINQ. Before he joined Microsoft a decade ago, he worked as a university professor in Aarhus, Denmark, doing research into programming language design and contributing to Java generics.
Why listen to this podcast
• The overall theme for C# 7 will be features that make it easier to work with data, including language level support for tuples.
Roslyn, the compiler and API, allows a much more agile evolution of the language.
• The Omnisharp initiative aims to facilitate easier editing of C# code in other editors, including VS Code.
• IoT and Artificial Intelligence are emerging as key disruptive trends.
• The release may also include pattern matching for type switching.
• C# 7 is the first new release of the language to be completely built in the open.
More on this
• You can access our whole coverage on C#7 http://bit.ly/1ZlM4NI or have an overview on what's new on C# in general http://bit.ly/1rx6SGM.
• You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. http://bit.ly/24x3IVq
• Attend Mads Torgersen's session at QCon New York 2016, Jun 13-17. http://bit.ly/1YcBgAY
4/27/2016 • 20 minutes, 20 seconds
Adrian Cockcroft on Microservices, Terraservices and Serverless Computing
Summary: For our inaugural podcast QCon chair Wesley Reisz talks to Adrian Cockcroft, who works for Battery Ventures where he advises the firm and its portfolio companies about technology issues and also assists with deal sourcing and due diligence.
Why listen to this podcast
• Over the last year a large number of frameworks and libraries for building microservices have emerged and we're seeing a lot of rapid change.
• The stack you choose will often be based on the main language you use, so for example Netflix’s stack is language agnostic but the tooling is very Java-centric.
• Architectural choices can have a profound impact on success, so some-thing as simple as an overly long timeout with retries can cause your system to suffer from a congestion collapse problem. Have a large timeout at the edge, and progressively smaller and smaller timeouts as you get deeper into the system.
• Start with a monolith and move to a distributed architecture when you need to because of team size or to get better separation of concerns.
• Other disruptive trends include “serverless architecture” like AWS Lambda, and open source itself which is perhaps the true definition of disruptive.
More on this
• You can access our in-depth coverage on microservices http://bit.ly/1SRnFz3.
• You can also subscribe to our newsletter to receive weekly updates on the hottest topics from professional software development. http://bit.ly/24x3IVq
• Attend Adrian Cockcroft 's session at QCon New York 2016, Jun 13-17. http://bit.ly/1TvzlDQ