The InfoQ Podcast

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Mike Lee Williams on Probabilistic Programming, Bayesian Inference, and Languages like PyMC3 Aug 31, 2018

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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.

Uncle Bob Martin on Clean Software, Craftsperson, Origins of SOLID, DDD, & Software Ethics Aug 24, 2018

Show notes

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. More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2Nebspj You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq Subscribe: www.youtube.com/infoq Like InfoQ on Facebook: bit.ly/2jmlyG8 Follow on Twitter: twitter.com/InfoQ Follow on LinkedIn: www.linkedin.com/company/infoq Check the landing page on InfoQ: https://bit.ly/2Nebspj

Arun Gupta on Managed Container Control Planes on AWS Jul 06, 2018

Show notes

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. You can subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq Subscribe: www.youtube.com/infoq Like InfoQ on Facebook: bit.ly/2jmlyG8 Follow on Twitter: twitter.com/InfoQ Follow on LinkedIn: www.linkedin.com/company/infoq Check the landing page on InfoQ: https://bit.ly/2tWT8t9

Anastasiia Voitova on Cryptography and the Design of Cryptographic Libraries Jun 29, 2018

Show notes

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 More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2yRWdQc You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq Subscribe: www.youtube.com/infoq Like InfoQ on Facebook: bit.ly/2jmlyG8 Follow on Twitter: twitter.com/InfoQ Follow on LinkedIn: www.linkedin.com/company/infoq Check the landing page on InfoQ: https://bit.ly/2yRWdQc

Matt Klein on Lyft’s Envoy, Including Edge Proxy, Service Mesh, & Potential AI Use Cases Jun 22, 2018

Show notes

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. You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq Subscribe: www.youtube.com/infoq Like InfoQ on Facebook: bit.ly/2jmlyG8 Follow on Twitter: twitter.com/InfoQ Follow on LinkedIn: www.linkedin.com/company/infoq Check the landing page on InfoQ: https://bit.ly/2tmUKMl

Pam Selle on Serverless Observability Jun 04, 2018

Show notes

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. More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2Jc6FXc You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. https://bit.ly/2Jc6FXc Subscribe: www.youtube.com/infoq Like InfoQ on Facebook: bit.ly/2jmlyG8 Follow on Twitter: twitter.com/InfoQ Follow on LinkedIn: www.linkedin.com/company/infoq Check the landing page on InfoQ: https://bit.ly/2Jc6FXc

Serverless and the Serverless Framework with David Wells May 27, 2018

Show notes

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. More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2IWayeE You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq Subscribe: www.youtube.com/infoq Like InfoQ on Facebook: bit.ly/2jmlyG8 Follow on Twitter: twitter.com/InfoQ Follow on LinkedIn: www.linkedin.com/company/infoq Check the landing page on InfoQ: https://bit.ly/2IWayeE

Colin Eberhardt on WebAssembly May 11, 2018

Show notes

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. More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2G8QtzB You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq Subscribe: www.youtube.com/infoq Like InfoQ on Facebook: bit.ly/2jmlyG8 Follow on Twitter: twitter.com/InfoQ Follow on LinkedIn: www.linkedin.com/company/infoq Check the landing page on InfoQ: https://bit.ly/2G8QtzB

Martin Thompson on Aeron, Binary vs Text for Message Encoding, and Raft May 07, 2018

Show notes

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) More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2Ilewk5 You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq Subscribe: www.youtube.com/infoq Like InfoQ on Facebook: bit.ly/2jmlyG8 Follow on Twitter: twitter.com/InfoQ Follow on LinkedIn: www.linkedin.com/company/infoq Check the landing page on InfoQ: https://bit.ly/2Ilewk5

Building a Data Science Capability with Stephanie Yee, Matei Zaharia, Sid Anand and Soups Ranjan Apr 27, 2018

Show notes

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. More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2Jym1RI You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq Subscribe: www.youtube.com/infoq Like InfoQ on Facebook: bit.ly/2jmlyG8 Follow on Twitter: twitter.com/InfoQ Follow on LinkedIn: www.linkedin.com/company/infoq Check the landing page on InfoQ: https://bit.ly/2Jym1RI

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