Blogs
on February 8, 2024
How GitHub’s Developer Experience team improved innerloop development
Building confidence in new code before deploying is a crucial part of any good development loop. This is especially challenging when working in a distributed or microservice system with multiple teams operating on different services. This modular team structure gives rise to an important question: how can we provide teams with fast and reliable development cycles when testing and shipping requires them to test inside an ecosystem of other services? Optimizing the solution to this problem greatly improves engineering efficiency and can contribute to more successful outcomes for the organization as a whole.
This problem is one the Developer Experience (DX) team at GitHub grappled with again and again, ultimately delivering a solution we call “Hubber Codespace” (HCS). HCS is a tool that Hubbers (people who work at GitHub) can use to locally stand up the entire distributed GitHub ecosystem in any environment by simply querying an endpoint or adding a couple lines of configuration to their development containers.
In this post, we’ll tell you how we landed on the HCS solution to this common problem over some possible alternatives, and you’ll get a first-hand look at how GitHub’s developer-first mindset helped us deliver the best tool for Hubbers to ship code quickly and safely in our own distributed environment.
One big (un)-happy environment
To understand the problem we were trying to solve, we have to go back in time. There was a point at which GitHub was just a couple teams and a much simpler product. Back then, having a monorepo in which everyone iterated and built confidence in their changes made sense. Splitting responsibilities up across repositories would have added overhead that bogged down early Hubbers. Fast forward to today, and GitHub has grown into a big organization with hundreds of different teams. Now, the balancing act of evaluating between velocity vs. complexity can look very different.
Let’s consider these complexities a bit further. Different services can have entirely different sets of dependencies and even have dependencies on different versions of the same software (for example, one service requires Ruby 2.2 while another requires Ruby 2.4). In smaller collaborative settings, the engineers can easily reconcile these needs. But this complexity grows exponentially as more teams are introduced. Trying to provide a single environment in which these kinds of disparate services can run and interact in development becomes difficult to do. It can result in ad-hoc “hacks” in development loops like deleting a .ruby-version file depending on which service’s development loop you’re working through. These are the kinds of problems that you encounter when trying to work with a monorepo that contains the codebases for a set of disparate services.
So, we decided to design a new solution. Instead of bringing the developers to the ecosystem, what if we brought the ecosystem to the developers?
Enter HCS
This line of thinking led us to build HCS, a Docker-Compose project that does exactly that. In the post “How we build containerized services at GitHub using GitHub,” we detailed how we build containerized services that power microservices on the GitHub.com platform and many internal tools. Our task now was to take these containers and wire them up such that partner teams could spin up a full GitHub ecosystem on demand. This would allow them to test their changes in an integrated environment. Developers could see how their code behaves when introduced to GitHub’s distributed system, rather than only observing it in the isolated environment of the application being developed before deploying within the full system. In this way, developers could gain confidence that the services they were changing behaved correctly when interacting with their up and downstream dependencies.
When considering how to orchestrate all the required containers, a few solutions came to mind: Docker-Compose, an internal tool called Codespace-Compose that allows us to SSH tunnel between multiple codespaces, and Minikube. Any of these three solutions could solve the ecosystem problem and would have unique tradeoffs. Let’s look at some of those tradeoffs now.
Minikube offers a robust Kubernetes architecture, but we had concerns about the overall user experience. We ultimately decided against it as the issues we identified, such as networking complexity and long cycle times, could bog down development speed.
Codespace-Compose allows us to easily connect teams’ everyday development environments, but we reasoned that, since Codespace-Compose is an internal experiment without any SLA, we’d incur a maintenance cost on our own team by adopting this.
Docker-Compose seemed to fit our needs the best. It didn’t incur any additional maintenance burden since it’s publicly available and actively managed. It offers all the same benefits of Minikube without the long cycle time. Most importantly, using Docker in Docker in a codespace, which allows us to create docker containers on a host which is a docker container itself, is a well-paved path that has lots of prior art. Given all these considerations, we decided on orchestrating our containers using Docker-Compose.
After deciding on Docker-Compose as our orchestrator, the next steps were to figure out the interface. Docker-Compose already supplies end users with commands, but we wanted to optimize the UX around HCS. To do this, we built a user-friendly CLI in Golang with parallel versioning to HCS. This abstracted away all the complexity of using the two together. Simply download a specific release version for HCS, get the same version of the CLI binary, and you’re good to go!
CLI and release automation
Ensuring HCS is useful means ensuring a couple of things. One important goal is ease of use. Docker-Compose already offers an interface for end users, but considering some of the built in commands are long and use predictable options, we decided to wrap it in a custom Golang CLI. This abstracted many of the underlying details away, such as static file locations, formatting options, entrypoint commands, etc. to improve end-user experience. The code below shows this by juxtaposing the Docker-Compose commands with their equivalent HCS CLI command.
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