- Feature flags for user applications
- Feature flags in GitLab development
This document only covers feature flags used in the development of GitLab itself. Feature flags in deployed user applications can be found at Feature Flags feature documentation.
The following highlights should be considered when deciding if feature flags should be leveraged:
- By default, the feature flags should be off.
- Feature flags should remain in the codebase for as short period as possible to reduce the need for feature flag accounting.
- The person operating with feature flags is responsible for clearly communicating the status of a feature behind the feature flag with responsible stakeholders. The issue description should be updated with the feature flag name and whether it is defaulted on or off as soon it is evident that a feature flag is needed.
- Merge requests that make changes hidden behind a feature flag, or remove an existing feature flag because a feature is deemed stable must have the ~”feature flag” label assigned.
When development of a feature will be spread across multiple merge requests, you can use the following workflow:
- Introduce a feature flag which is off by default, in the first merge request.
- Submit incremental changes via one or more merge requests, ensuring that any new code added can only be reached if the feature flag is on. You can keep the feature flag enabled on your local GDK during development.
- When the feature is ready to be tested, enable the feature flag for a specific project and ensure that there are no issues with the implementation.
- When the feature is ready to be announced, create a merge request that adds documentation about the feature, including documentation for the feature flag itself, and a changelog entry. In the same merge request either flip the feature flag to be on by default or remove it entirely in order to enable the new behavior.
One might be tempted to think that feature flags will delay the release of a feature by at least one month (= one release). This is not the case. A feature flag does not have to stick around for a specific amount of time (e.g. at least one release), instead they should stick around until the feature is deemed stable. Stable means it works on GitLab.com without causing any problems, such as outages.
Please also read the development guide for feature flags.
Starting with GitLab 11.4, developers are required to use feature flags for non-trivial changes. Such changes include:
- New features (e.g. a new merge request widget, epics, etc).
- Complex performance improvements that may require additional testing in production, such as rewriting complex queries.
- Invasive changes to the user interface, such as a new navigation bar or the removal of a sidebar.
- Adding support for importing projects from a third-party service.
In all cases, those working on the changes can best decide if a feature flag is necessary. For example, changing the color of a button doesn’t need a feature flag, while changing the navigation bar definitely needs one. In case you are uncertain if a feature flag is necessary, simply ask about this in the merge request, and those reviewing the changes will likely provide you with an answer.
When using a feature flag for UI elements, make sure to also use a feature flag for the underlying backend code, if there is any. This ensures there is absolutely no way to use the feature until it is enabled.
In order to build a final release and present the feature for self-managed users, the feature flag should be at least defaulted to on. If the feature is deemed stable and there is confidence that removing the feature flag is safe, consider removing the feature flag altogether. It’s strongly recommended that the feature flag is enabled globally on production for at least one day before making this decision. Unexpected bugs are sometimes discovered during this period.
The process for enabling features that are disabled by default can take 5-6 days from when the merge request is first reviewed to when the change is deployed to GitLab.com. However, it is recommended to allow 10-14 days for this activity to account for unforeseen problems.
Feature flags must be documented according to their state (enabled/disabled), and when the state changes, docs must be updated accordingly.
Changing the default state or removing the feature flag has to be done before the 22nd of the month, at least 3-4 working days before, in order for the change to be included in the final self-managed release.
In addition to this, the feature behind feature flag should:
- Run in all GitLab.com environments for a sufficient period of time. This time period depends on the feature behind the feature flag, but as a general rule of thumb 2-4 working days should be sufficient to gather enough feedback.
- The feature should be exposed to all users within the GitLab.com plan during the above mentioned period of time. Exposing the feature to a smaller percentage or only a group of users might not expose a sufficient amount of information to aid in making a decision on feature stability.
While rare, release managers may decide to reject picking or revert a change in a stable branch, even when feature flags are used. This might be necessary if the changes are deemed problematic, too invasive, or there simply isn’t enough time to properly measure how the changes behave on GitLab.com.
When reading the above, one might be tempted to think this procedure is going to add a lot of work. Fortunately, this is not the case, and we’ll show why. For this example we’ll specify the cost of the work to do as a number, ranging from 0 to infinity. The greater the number, the more expensive the work is. The cost does not translate to time, it’s just a way of measuring complexity of one change relative to another.
Let’s say we are building a new feature, and we have determined that the cost of this is 10. We have also determined that the cost of adding a feature flag check in a variety of places is 1. If we do not use feature flags, and our feature works as intended, our total cost is 10. This however is the best case scenario. Optimizing for the best case scenario is guaranteed to lead to trouble, whereas optimizing for the worst case scenario is almost always better.
To illustrate this, let’s say our feature causes an outage, and there’s no immediate way to resolve it. This means we’d have to take the following steps to resolve the outage:
- Revert the release.
- Perform any cleanups that might be necessary, depending on the changes that were made.
- Revert the commit, ensuring the “master” branch remains stable. This is especially necessary if solving the problem can take days or even weeks.
- Pick the revert commit into the appropriate stable branches, ensuring we don’t block any future releases until the problem is resolved.
As history has shown, these steps are time consuming, complex, often involve many developers, and worst of all: our users will have a bad experience using GitLab.com until the problem is resolved.
Now let’s say that all of this has an associated cost of 10. This means that in the worst case scenario, which we should optimize for, our total cost is now 20.
If we had used a feature flag, things would have been very different. We don’t need to revert a release, and because feature flags are disabled by default we don’t need to revert and pick any Git commits. In fact, all we have to do is disable the feature, and in the worst case, perform cleanup. Let’s say that the cost of this is 2. In this case, our best case cost is 11: 10 to build the feature, and 1 to add the feature flag. The worst case cost is now 13:
- 10 to build the feature.
- 1 to add the feature flag.
- 2 to disable and clean up.
Here we can see that in the best case scenario the work necessary is only a tiny bit more compared to not using a feature flag. Meanwhile, the process of reverting our changes has been made significantly and reliably cheaper.
In other words, feature flags do not slow down the development process. Instead, they speed up the process as managing incidents now becomes much easier. Once continuous deployments are easier to perform, the time to iterate on a feature is reduced even further, as you no longer need to wait weeks before your changes are available on GitLab.com.