Add Next GitLab Runner Auto-scaling blueprint

doc/architecture/blueprints/runner_scaling/index.md

+---
+stage: none
+group: unassigned
+comments: false
+description: 'Next Runner Auto-scaling Architecture'
+---
+
+# Next Runner Auto-scaling Architecture
+
+## Summary
+
+GitLab Runner is a core component of GitLab CI/CD. It makes it possible to run
+CI/CD jobs in a reliable and concurrent environment. It has been initially
+introduced by Kamil Trzciński in early 2015 to replace a Ruby version of the
+same service. GitLab Runner written in Go turned out to be easier to use by the
+wider community, it was more efficient and reliable than the previous,
+Ruby-based, version.
+
+In February 2016 Kamil Trzciński implemented an auto-scaling feature to
+leverage cloud infrastructure to run many CI/CD jobs in parallel. This feature
+has become a foundation supporting CI/CD adoption on GitLab.com over the years,
+where we now run around 4 million builds per day at peak.
+
+During the initial implementation a decision was made to use Docker Machine:
+
+> Is easy to use. Is well documented. Is well supported and constantly
+> extended. It supports almost any cloud provider or virtualization
+> infrastructure. We need minimal amount of changes to support Docker Machine:
+> machine enumeration and inspection. We don't need to implement any "cloud
+> specific" features.
+
+This design choice was crucial for the GitLab Runner success. Since that time
+the auto-scaling feature has been used by many users and customers and enabled
+rapid growth of CI/CD adoption on GitLab.com.
+
+We can not, however, continue using Docker Machine. Work on that project was
+paused in July 2018 and there was no development made since that time (except
+for some highly important security fixes). In 2018, after Docker Machine
+entered the “maintenance mode”, we decided to create our own fork to be able to
+keep using this and ship fixes and updates needed for our use case. On
+September 26th, 2021 the project got archived and the documentation for it has
+been removed from the official page. This means that the original reason to use
+Docker Machine is no longer valid too.
+
+To keep supporting our customers and the wider community we need to design a
+new mechanism for GitLab Runner autoscaling. It not only needs to support
+auto-scaling, but it also needs to do that in the way to enable us to build on
+top of it to improve efficiency, reliability and availability.
+
+We call this new mechanism the “next GitLab Runner Scaling architecture”.
+
+*Disclaimer The following contain information related to upcoming products,
+features, and functionality.
+
+It is important to note that the information presented is for informational
+purposes only. Please do not rely on this information for purchasing or
+planning purposes.
+
+As with all projects, the items mentioned in this document and linked pages are
+subject to change or delay. The development, release and timing of any
+products, features, or functionality remain at the sole discretion of GitLab
+Inc.*
+
+## Proposal
+
+Currently, GitLab Runner auto-scaling can be configured in a few ways. Some
+customers are successfully using an auto-scaled environment in Kubernetes. We
+know that a custom and unofficial GitLab Runner version has been built to make
+auto-scaling on Kubernetes more reliable. We recognize the importance of having
+a really good Kubernetes solution for running multiple jobs in parallel, but
+refinements in this area are out of scope for this architectural initiative.
+
+We want to focus on resolving problems with Docker Machine and replacing this
+mechanism with a reliable and flexible mechanism. We might be unable to build a
+drop-in replacement for Docker Machine, as there are presumably many reasons
+why it has been deprecated. It is very difficult to maintain compatibility with
+so many cloud providers, and it seems that Docker Machine has been deprecated
+in favor of Docker Desktop, which is not a viable replacement for us. This
+issue contains a discussion about how people are using Docker Machine right
+now, and it seems that GitLab CI is one of the most frequent reasons for people
+to keep using Docker Machine.
+
+There is also an opportunity in being able to optionally run multiple jobs in a
+single, larger virtual machine. We can’t do that today, but we know that this
+can potentially significantly improve efficiency. We might want to build a new
+architecture that makes it easier and allows us to test how efficient it is
+with PoCs. Running multiple jobs on a single machine can also make it possible
+to reuse what we call a “sticky context” - a space for build artifacts / user
+data that can be shared between job runs.
+
+💡 Design a simple abstraction that users will be able to build on top of
+
+Because there is no viable replacement and we might be unable to support all
+cloud providers that Docker Machine used to support, the key design requirement
+is to make it really simple and easy for the wider community to write a custom
+GitLab auto-scaling plugin, whatever cloud provider they might be using. We
+want to design a simple abstraction that users will be able to build on top, as
+will we to support existing workflows on GitLab.com.
+
+The designed mechanism should abstract what Docker Machine executor was doing:
+providing a way to create - externally - Docker environment ready to execute
+our jobs and return credentials to Docker Engine API that we can hook into
+Docker executor.
+
+💡 Migrate existing Docker Machine solution to a plugin
+
+Once we design and implement the new abstraction, we should be able to migrate
+existing Docker Machine mechanisms to a plugin. This will make it possible for
+users and customers to immediately start using the new architecture, but still
+keep their existing workflows and configuration for Docker Machine. This will
+give everyone time to migrate to the new architecture before we drop support
+for the legacy auto-scaling entirely.
+
+💡 Build plugins for AWS, Google Cloud Platform and Azure
+
+Although we might be unable to add support for all the cloud providers that
+Docker Machine used to support, it seems to be important to provide
+GitLab-maintained plugins for the major cloud providers like AWS, Google Cloud
+Platform and Azure.
+
+💡 Write a solid documentation about how to build your own plugin
+
+It is important to show users how to build an auto-scaling plugin, so that they
+can implement support for their own cloud infrastructure.
+
+💡 Build a PoC to run multiple builds on a single machine
+
+We want to better understand what kind of efficiency can running multiple jobs
+on a single machine bring. It is difficult to predict that, so ideally we
+should build a PoC that will  help us to better understand what we can expect
+from this.
+
+## Details
+
+How the abstraction for the custom provider will look exactly is something that
+we will need to prototype, PoC and decide in a data-informed way. There are a
+few proposals that we should describe in detail, develop requirements for, PoC
+and score. We will choose the solution that seems to support our goals the
+most.
+
+In order to describe the proposals we first need to better explain what part of
+the GitLab Runner needs to be abstracted away. To make this easier to grasp
+these concepts, let's take a look at the current auto-scaling architecture and
+sequence diagram.
+
+![GitLab Runner Autoscaling Overview](gitlab-autoscaling-overview.png)
+
+On the diagrams above we see that currently a GitLab Runner Manager runs on a
+machine that has access to a cloud provider’s API. It is using Docker Machine
+to provision new Virtual Machines with Docker Engine installed and it
+configures the Docker daemon there to allow external authenticated requests. It
+stores credentials to such ephemeral Docker environments on disk. Once a
+machine has been provisioned and made available for GitLab Runner Manager to
+run builds, it is using one of the existing executors to run a user-provided
+script. In auto-scaling, this is typically done using Docker executor.
+
+### Custom provider
+
+In order to reduce the scope of work, we only want to introduce the new
+abstraction layer in one place.
+
+A few years ago we introduced the Custom Executor feature in GitLab Runner. It
+allows users to design custom build execution methods. The custom executor
+driver can be implemented in any way - from a simple shell script to a
+dedicated binary - that is then used by a Runner through os/exec system calls.
+
+Thanks to the custom executor abstraction there is no more need to implement
+new executors internally in Runner. Users who have specific needs can implement
+their own drivers and don’t need to wait for us to make their work part of the
+“official” GitLab Runner. As each driver is a separate project, it also makes
+it easier to create communities around them, where interested people can
+collaborate together on improvements and bug fixes.
+
+We want to design the new Custom Provider to replicate the success of the
+Custom Executor. It will make it easier for users to build their own ways to
+provide a context and an environment in which a build will be executed by one
+of the Custom Executors.
+
+There are multiple solutions to implementing a custom provider abstraction. We
+can use raw Go plugins, Hashcorp’s Go Plugin, HTTP interface or gRPC based
+facade service. There are many solutions, and we want to choose the most
+optimal one. In order to do that, we will describe the solutions in a separate
+document, define requirements and score the solution accordingly. This will
+allow us to choose a solution that will work best for us and the wider
+community.
+
+## Status
+
+Status: RFC.
+
+## Who
+
+Proposal:
+
+<!-- vale gitlab.Spelling = NO -->
+
+| Role                         | Who
+|------------------------------|------------------------------------------|
+| Authors                      | Grzegorz Bizon, Tomasz Maczukin          |
+| Architecture Evolution Coach | Kamil Trzciński                          |
+| Engineering Leader           | Elliot Rushton, Cheryl Li                |
+| Product Manager              | Darren Eastman, Jackie Porter            |
+| Domain Expert / Runner       | Arran Walker                             |
+
+DRIs:
+
+| Role                         | Who
+|------------------------------|------------------------|
+| Leadership                   | Elliot Rushton         |
+| Product                      | Darren Eastman         |
+| Engineering                  | Tomasz Maczukin        |
+
+Domain experts:
+
+| Area                         | Who
+|------------------------------|------------------------|
+| Domain Expert / Runner       | Arran Walker           |
+
+<!-- vale gitlab.Spelling = YES -->