The InfoQ Podcast

Martin Fowler, Chief Scientist at ThoughtWorks and author of influential tech books, dives into his recent work on the updated edition of Refactoring. He explains how the core idea of small, incremental changes remains relevant. Martin shares insights on evolutionary architecture, highlighting its capacity for adaptability beyond microservices. He also discusses modern refactoring practices, the shift from traditional programming languages to more accessible options, and the challenges of deploying distributed systems in the ever-evolving landscape of software development.

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. More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2S3ZiSx 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/2S3ZiSx

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. More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2RJdwYR 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/2RJdwYR

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. More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2RAEUrV 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/2RAEUrV

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. More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2NYsXNN 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/2NYsXNN

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. More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2MwEWxb 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/2MwEWxb

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)

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.

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 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