Software Engineering Daily

Amazon’s container offerings include ECS (Elastic Container Service), EKS (Elastic Kubernetes Service), and Fargate. Through these different offerings, Amazon provides a variety of ways that a user can manage Kubernetes clusters and standalone container instances. The choice of which containerization system to choose depends on the needs of the user, and the tradeoffs they want to make on control and portability.

Amazon’s container products have been designed in the context of a shifting competitive landscape. Kubernetes presents a potential long-term threat to Amazon’s status as the most popular cloud provider. Properly responding to this threat has required Amazon to extend itself into the world of open source, contributing to Kubernetes and having more conversations with customers who want their products to have the high quality user experience of AWS along with the open characteristics of Kubernetes.

Abby Fuller is a principal technologist with Amazon who works on containers and Linux. Abby joins the show to describe Amazon’s perspective on containers and Kubernetes.

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When the Kubernetes project was started, Amazon Web Services was the dominant cloud provider. Most of the code that runs AWS is closed source, which prevents an open ecosystem from developing around AWS. Developers who deploy their application onto AWS are opting into a closed, controlled ecosystem, which has both costs and benefits.

The software industry has a history of closed and open ecosystems existing at the same time. AWS represented a huge closed ecosystem. With the amount of money at stake in the cloud business, it was only a matter of time before a more open ecosystem emerged.

Since the creation of Kubernetes, the world of cloud computing has evolved rapidly. Google and Microsoft have both invested heavily into Kubernetes, and Amazon itself has adapted to the newer competitive landscape with a Kubernetes offering of its own. Amazon has also made efforts to become more publicly involved in open source projects, including Kubernetes.

Kelsey Hightower has been a part of the Kubernetes ecosystem since the project was started. He is one of the most recognizable faces in the world of Kubernetes, delivering keynotes, appearing on podcasts, and co-authoring the popular Kubernetes Up and Running. Kelsey joins the show to discuss the progress in the Kubernetes ecosystem, and the competitive dynamics between Kubernetes and AWS.

Announcements

We are hiring a software engineer who can work across both mobile and web. This role will work on SoftwareDaily.com, our iOS app, and our Android application. We are looking for someone who learns very quickly and can produce high quality code at a fast pace. If you are interested in working with us, send an email to [email protected].

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Cruise is a company that is building a fully automated self-driving car service.

The infrastructure of a self-driving car platform presents a large number of new engineering problems. Self-driving cars collect vast quantities of data as they are driving around the city. This data needs to be transferred from the cars onto cloud servers. The data needs to be used for training machine learning models. These models must be tested in a simulated environment, which provides more data to be integrated back into the self-driving system that is deployed to the cars.

As the cars drive around the city, they can communicate with custom cloud services to get information about traffic, navigation, and weather. Cloud services are also used for internal tooling that can help with automotive diagnostics, configuration changes, deployments, and security policy management.

The software platform used to manage infrastructure at Cruise is a combination of cloud products, open source tools, and custom built infrastructure that is mostly deployed to Kubernetes. Karl Isenberg is an engineer at Cruise, and he joins the show to talk about the engineering requirements of building a self-driving car service, and Cruise’s approach to platform engineering.

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The container orchestration wars ended in 2016 with Kubernetes being the most popular open source tool for deploying and managing infrastructure. Since that time, most large enterprises have been implementing a “platform strategy” based around Kubernetes.

A platform strategy is a plan for creating a consistent experience for software engineers working throughout an enterprise. At most companies, a software engineer should be thinking about business logic–whether that logic is related to banking, insurance, oil and gas, or e-commerce. 

Today, engineers at many enterprises need to think about continuous delivery, application deployment, security policy management, and other deeply technical problems that have nothing to do with the business that they are actually working at. Kubernetes is a foundational open source building block that allows enterprises to base the rest of their infrastructure decisions around. Kubernetes has made it much more viable for enterprises to pursue a platform strategy.

With widespread adoption of Kubernetes, there is a business opportunity for companies that can offer other platform solutions that build on top of Kubernetes. A service mesh is one such tool. A service mesh provides networking and security features for all the services in an organization.

The service mesh category is a large business opportunity because it sits on the critical path of every network request that goes through an enterprise. It is a potential insertion point for lots of other products including logging agents, distributed tracing, network packet scanning, security policy management, and A/B testing.

The potential for business expansion is why so many businesses are entering the service mesh category today, from cloud providers to API gateways. Buoyant was one of the first companies to work on a service mesh tool, with the Linkerd open source project. William Morgan is the CEO of Buoyant, and he returns to the show to discuss the competitive dynamics of the service mesh market.

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Kubernetes has created a widespread system for deploying and managing infrastructure. As Kubernetes has been increasingly adopted, companies are thinking about how to leverage that common layer of infrastructure. With the common infrastructure abstraction of Kubernetes, it becomes easier to adopt other abstractions that are uniform across the entire company. 

This has created a market opportunity for products such as a service mesh.

A service mesh consists of sidecar containers that get deployed alongside services in a distributed system. Each sidecar container is used as a proxy for all the communication that goes through the service it is deployed with. This consistent proxying layer provides each service with benefits such as security, routing, telemetry, and policy management.

Istio is a service mesh that was created and open sourced by Google. Istio is built around the Envoy service proxy sidecar and a control plane that manages the Envoy sidecars. Since the launch of Istio, some of the Google employees who were working on Istio have started Tetrate, a company with the goal of commercializing Istio into a product that enterprises will pay for.  

The market demand for service mesh has been proven, but there are many competitors to Tetrate. Istio is open source and can be commercialized by other companies, as well as cloud providers such as Google and AWS. Linkerd is a service mesh built by the company Buoyant, which was the first company to focus exclusively on this space. There are other companies that are expanding existing products into service mesh: Kong, NGINX, and Hashicorp.

Zack Butcher is a founding engineer with Tetrate, and he joins the show to discuss the market for service mesh and the plan for Tetrate to build a business around Istio.

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A cloud provider gives a developer low-cost compute infrastructure on-demand. 

Cloud providers can be divided up into two categories: Layer 1 cloud providers and Layer 2 cloud providers. A Layer 1 cloud provider such as Amazon Web Services owns server hardware and sells compute infrastructure as a commodity. A Layer 2 cloud provider purchases compute infrastructure from a Layer 1 provider and builds a high quality developer experience on top of that compute infrastructure.

Heroku was the first Layer 2 cloud provider. Heroku’s first business was to provide a high quality developer experience and low cost containerization infrastructure on top of Amazon’s EC2 virtual machine infrastructure. Heroku has added features for continuous integration, relational databases, caches, and queueing.

Building a Layer 2 cloud provider is a very different challenge than building a Layer 1 cloud provider. A Layer 1 provider must focus on low level problems such as hardware infrastructure and virtualization. This does not leave much time for focusing on developer experience. A Layer 1 cloud provider must be able to serve every type of potential software customer. A Layer 2 provider can provide a streamlined experience.

Mark Turner is an engineer at Heroku. He joins the show to discuss the architecture and engineering of a Layer 2 cloud provider. Heroku is built on top of Amazon Web Services, and the core compute infrastructure is built on top of a pool of EC2 virtual machines that are continually scheduled with applications that users create on Heroku. Full disclosure: Heroku is a sponsor of Software Engineering Daily.

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New software abstractions always take advantage of the abstractions that have been built before.

Software libraries allow us to import code that sits on the same host as a new program. Open source software let us copy and paste existing code, or clone entire repositories. Cloud providers offer hosted tools and APIs that we can leverage to develop scalable, easy-to-use infrastructure.

When existing pieces of software are built into new software, the existing software becomes a dependency. Managing those dependencies is an engineering problem. Mya Pitzeruse is the founder of deps.cloud, a project with the goal of improving dependency changes across a company’s ecosystem. In today’s show, we talk about the modern dependency issues of a large company, and her perspective on how to address them. Mya has developed the project in public on FindCollabs, and we also spend some time talking about building in the open.

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“Serverless” is an execution model where applications are scheduled and deployed to servers that are not directly managed by the application developer. 

In serverless execution, an application only loads and operates when a user actually needs to get a response from that application. This saves on resources, because many applications do not need to run at all times–they only need to be available for user requests.

The serverless model was popularized by Amazon Web Services Lambda. When Lambda first launched in 2015, it was an experimental product. Today, it is a widely used product and the market has validated the desire for serverless execution. Other cloud providers have introduced different models of serverless functionality including Google Cloud Functions, Azure Functions, and Fastly edge computing.

Zack Bloom is director of product for product strategy at Cloudflare, and he joins the show to discuss Cloudflare’s model for serverless execution. Zack also discusses Cloudflare’s growing product line, including the fast, privacy-protecting DNS resolver 1.1.1.1. Zack is a rare mix of engineering, business strategy, and product vision, which made for a great conversation.

For more content, you can check out our episodes about serverless technology and episodes about Cloudflare.

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Java programs run in a different environment than they did ten years ago.

Modern infrastructure runs on containers sitting in a Kubernetes cluster. The optimal configuration for a Java program in that context is different than it was for an environment dominated by virtual machines and bare metal. When you are co-scheduling your services with each other, those services could be fighting for resources. You may want to optimize them with more ahead-of-time compilation.

Quarkus is a system for accelerating Java performance through the use of GraalVM. In a previous show, we explored the basics of GraalVM. In today’s show, Guillaume Smet and Emmanuel Bernard join the show to describe an application of GraalVM: the acceleration of Java. Guillaume and Emmaneul are engineers at Red Hat, and are working on changes to the Java ecosystem that are informed by the cloud and the rise of Kubernetes.

Sponsorship inquiries: [email protected]

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Dark Lang is a programming language that is tightly integrated with the cloud. 

Dark takes an opinionated approach that most developers are going to want to run their applications in the cloud, and this perspective influences how Dark looks at deployments, IDEs, exception handling, and other aspects of software development.

Paul Biggar is the founder of CircleCI, and ran the company for eight years before leaving to found Dark with Ellen Chisa. Ellen is a software engineer and the CEO of Dark. Paul and Ellen join the show to give their perspective on modern software engineering, and why it was time to build a new high level language that assumes the presence of a cloud.

It is difficult to get programmers to adopt a new language. It is even harder to get those programmers to pay for products built around that language. But the timing could be perfect for Dark. 

Software development is undergoing tremendous change–and many of these changes work to Dark’s advantage, such as the growing adoption of feature flags, low code tools, and sophisticated continuous delivery workflows. Whether or not Dark is a success, it is a bold project, and the team is working on something they believe in.

We also discussed AWS–and whether the largest cloud provider has an obligation to contribute back to the open source community.

Sponsorship inquiries: [email protected]

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