2018-12-05 23:21:45 +05:30
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# Rolling out changes using feature flags
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[Feature flags](feature_flags.md) can be used to gradually roll out changes, be
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it a new feature, or a performance improvement. By using feature flags, we can
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comfortably measure the impact of our changes, while still being able to easily
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disable those changes, without having to revert an entire release.
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## When to use feature flags
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Starting with GitLab 11.4, developers are required to use feature flags for
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non-trivial changes. Such changes include:
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2019-03-02 22:35:43 +05:30
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- New features (e.g. a new merge request widget, epics, etc).
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- Complex performance improvements that may require additional testing in
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2018-12-05 23:21:45 +05:30
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production, such as rewriting complex queries.
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- Invasive changes to the user interface, such as a new navigation bar or the
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removal of a sidebar.
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- Adding support for importing projects from a third-party service.
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In all cases, those working on the changes can best decide if a feature flag is
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necessary. For example, changing the color of a button doesn't need a feature
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flag, while changing the navigation bar definitely needs one. In case you are
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uncertain if a feature flag is necessary, simply ask about this in the merge
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request, and those reviewing the changes will likely provide you with an answer.
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When using a feature flag for UI elements, make sure to _also_ use a feature
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flag for the underlying backend code, if there is any. This ensures there is
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absolutely no way to use the feature until it is enabled.
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## The cost of feature flags
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When reading the above, one might be tempted to think this procedure is going to
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add a lot of work. Fortunately, this is not the case, and we'll show why. For
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this example we'll specify the cost of the work to do as a number, ranging from
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0 to infinity. The greater the number, the more expensive the work is. The cost
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does _not_ translate to time, it's just a way of measuring complexity of one
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change relative to another.
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Let's say we are building a new feature, and we have determined that the cost of
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this is 10. We have also determined that the cost of adding a feature flag check
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in a variety of places is 1. If we do not use feature flags, and our feature
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works as intended, our total cost is 10. This however is the best case scenario.
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Optimising for the best case scenario is guaranteed to lead to trouble, whereas
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optimising for the worst case scenario is almost always better.
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To illustrate this, let's say our feature causes an outage, and there's no
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immediate way to resolve it. This means we'd have to take the following steps to
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resolve the outage:
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1. Revert the release.
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1. Perform any cleanups that might be necessary, depending on the changes that
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were made.
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1. Revert the commit, ensuring the "master" branch remains stable. This is
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especially necessary if solving the problem can take days or even weeks.
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1. Pick the revert commit into the appropriate stable branches, ensuring we
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don't block any future releases until the problem is resolved.
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As history has shown, these steps are time consuming, complex, often involve
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many developers, and worst of all: our users will have a bad experience using
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GitLab.com until the problem is resolved.
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Now let's say that all of this has an associated cost of 10. This means that in
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the worst case scenario, which we should optimise for, our total cost is now 20.
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If we had used a feature flag, things would have been very different. We don't
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need to revert a release, and because feature flags are disabled by default we
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don't need to revert and pick any Git commits. In fact, all we have to do is
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disable the feature, and _maybe_ perform some cleanup. Let's say that the cost
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of this is 1. In this case, our best case cost is 11: 10 to build the feature,
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and 1 to add the feature flag. The worst case cost is now 12: 10 to build the
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feature, 1 to add the feature flag, and 1 to disable it.
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Here we can see that in the best case scenario the work necessary is only a tiny
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bit more compared to not using a feature flag. Meanwhile, the process of
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reverting our changes has been made significantly cheaper, to the point of being
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trivial.
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In other words, feature flags do not slow down the development process. Instead,
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they speed up the process as managing incidents now becomes _much_ easier. Once
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continuous deployments are easier to perform, the time to iterate on a feature
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is reduced even further, as you no longer need to wait weeks before your changes
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are available on GitLab.com.
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## Rolling out changes
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The procedure of using feature flags is straightforward, and similar to not
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using them. You add the necessary tests (make sure to test both the on and off
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states of your feature flag(s)), make sure they all pass, have the code
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reviewed, etc. You then submit your merge request, and add the ~"feature flag"
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label. This label is used to signal to release managers that your changes are
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hidden behind a feature flag and that it is safe to pick the MR into a stable
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branch, without the need for an exception request.
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When the changes are deployed it is time to start rolling out the feature to our
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users. The exact procedure of rolling out a change is unspecified, as this can
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vary from change to change. However, in general we recommend rolling out changes
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incrementally, instead of enabling them for everybody right away. We also
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recommend you to _not_ enable a feature _before_ the code is being deployed.
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This allows you to separate rolling out a feature from a deploy, making it
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easier to measure the impact of both separately.
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GitLab's feature library (using
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[Flipper](https://github.com/jnunemaker/flipper), and covered in the [Feature
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Flags](feature_flags.md) guide) supports rolling out changes to a percentage of
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users. This in turn can be controlled using [GitLab
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chatops](https://docs.gitlab.com/ee/ci/chatops/).
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For example, to enable a feature for 25% of all users, run the following in
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Slack:
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```
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/chatops run feature set new_navigation_bar 25
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```
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This will enable the feature for GitLab.com, with `new_navigation_bar` being the
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name of the feature. We can also enable the feature for <https://dev.gitlab.org>
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or <https://staging.gitlab.com>:
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```
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/chatops run feature set new_navigation_bar 25 --dev
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/chatops run feature set new_navigation_bar 25 --staging
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```
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If you are not certain what percentages to use, simply use the following steps:
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1. 25%
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1. 50%
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1. 75%
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1. 100%
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Between every step you'll want to wait a little while and monitor the
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appropriate graphs on <https://dashboards.gitlab.net>. The exact time to wait
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may differ. For some features a few minutes is enough, while for others you may
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want to wait several hours or even days. This is entirely up to you, just make
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sure it is clearly communicated to your team, and the Production team if you
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anticipate any potential problems.
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Once a change is deemed stable, submit a new merge request to remove the
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feature flag. This ensures the change is available to all users and self-hosted
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instances. Make sure to add the ~"feature flag" label to this merge request so
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release managers are aware the changes are hidden behind a feature flag. If the
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merge request has to be picked into a stable branch (e.g. after the 7th), make
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sure to also add the appropriate "Pick into X" label (e.g. "Pick into 11.4").
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One might be tempted to think this will delay the release of a feature by at
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least one month (= one release). This is not the case. A feature flag does not
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have to stick around for a specific amount of time (e.g. at least one release),
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instead they should stick around until the feature is deemed stable. Stable
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means it works on GitLab.com without causing any problems, such as outages. In
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most cases this will translate to a feature (with a feature flag) being shipped
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in RC1, followed by the feature flag being removed in RC2. This in turn means
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the feature will be stable by the time we publish a stable package around the
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22nd of the month.
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2018-12-13 13:39:08 +05:30
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## Implicit feature flags
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The [`Project#feature_available?`][project-fa],
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[`Namespace#feature_available?`][namespace-fa] (EE), and
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[`License.feature_available?`][license-fa] (EE) methods all implicitly check for
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a feature flag by the same name as the provided argument.
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For example if a feature is license-gated, there's no need to add an additional
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explicit feature flag check since the flag will be checked as part of the
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`License.feature_available?` call. Similarly, there's no need to "clean up" a
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feature flag once the feature has reached general availability.
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You'd still want to use an explicit `Feature.enabled?` check if your new feature
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isn't gated by a License or Plan.
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[project-fa]: https://gitlab.com/gitlab-org/gitlab-ee/blob/4cc1c62918aa4c31750cb21dfb1a6c3492d71080/app/models/project_feature.rb#L63-68
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[namespace-fa]: https://gitlab.com/gitlab-org/gitlab-ee/blob/4cc1c62918aa4c31750cb21dfb1a6c3492d71080/ee/app/models/ee/namespace.rb#L71-85
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[license-fa]: https://gitlab.com/gitlab-org/gitlab-ee/blob/4cc1c62918aa4c31750cb21dfb1a6c3492d71080/ee/app/models/license.rb#L293-300
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### Undefined feature flags default to "on"
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An important side-effect of the [implicit feature
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flags][#implicit-feature-flags] mentioned above is that unless the feature is
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explicitly disabled or limited to a percentage of users, the feature flag check
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will default to `true`.
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As an example, if you were to ship the backend half of a feature behind a flag,
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you'd want to explicitly disable that flag until the frontend half is also ready
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to be shipped. You can do this via ChatOps:
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```
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/chatops run feature set some_feature 0
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```
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Note that you can do this at any time, even before the merge request using the
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flag has been merged!
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