- Where to run commands
- Rolling out changes
- Cleaning up
To be able to turn on/off features behind feature flags in any of the GitLab Inc. provided environments such as staging and production, you need to have access to the Chatops bot. The Chatops bot is currently running on the ops instance, which is different from https://gitlab.com or https://dev.gitlab.org.
Follow the Chatops document to request access.
Once you are added to the project test if your access propagated, run:
/chatops run feature --help
To increase visibility, we recommend that GitLab team members run feature flag related Chatops commands within certain Slack channels based on the environment and related feature. For the staging and development environments of GitLab.com, the commands should run in a channel for the stage the feature is relevant too.
For example, use the
#s_monitor channel for features developed by the
Monitor stage, Health group.
For all production environment Chatops commands, use the
As per the template, where a feature would have a (potentially) significant user
impact and the feature is being enabled instance wide prior to release, please copy
the Slack message and repost in the
#support_gitlab-com channel for added visibility
and awareness, preferably with a link to the issue, MR, or docs.
Regardless of the channel in which the Chatops command is ran, any feature flag change that affects GitLab.com will automatically be logged in an issue.
The issue is created in the gl-infra/feature-flag-log project, and it will at minimum log the Slack handle of person enabling a feature flag, the time, and the name of the flag being changed.
The issue is then also posted to GitLab Inc. internal Grafana dashboard as an annotation marker to make the change even more visible.
Changes to the issue format can be submitted in the Chatops project.
When the changes are deployed to the environments it is time to start rolling out the feature to our users. The exact procedure of rolling out a change is unspecified, as this can vary from change to change. However, in general we recommend rolling out changes incrementally, instead of enabling them for everybody right away. We also recommend you to not enable a feature before the code is being deployed. This allows you to separate rolling out a feature from a deploy, making it easier to measure the impact of both separately.
GitLab’s feature library (using Flipper, and covered in the Feature Flags process guide) supports rolling out changes to a percentage of time to users. This in turn can be controlled using GitLab Chatops.
For an up to date list of feature flag commands please see the source
Note that all the examples in that file must be preceded by
If you get an error “Whoops! This action is not allowed. This incident will be reported.” that means your Slack account is not allowed to change feature flags or you do not have access.
For example, to enable a feature for 25% of all users, run the following in Slack:
/chatops run feature set new_navigation_bar 25 --dev /chatops run feature set new_navigation_bar 25 --staging
These two environments have different scopes.
dev.gitlab.org is a production CE environment that has internal GitLab Inc.
traffic and is used for some development and other related work.
staging.gitlab.com has a smaller subset of GitLab.com database and repositories
and does not have regular traffic. Staging is an EE instance and can give you
a (very) rough estimate of how your feature will look/behave on GitLab.com.
Both of these instances are connected to Sentry so make sure you check the projects
there for any exceptions while testing your feature after enabling the feature flag.
Once you are confident enough that these environments are in a good state with your feature enabled, you can roll out the change to GitLab.com.
Similar to above, to enable a feature for 25% of all users, run the following in Slack:
/chatops run feature set new_navigation_bar 25
This will enable the feature for GitLab.com, with
new_navigation_bar being the
name of the feature.
This command does not enable the feature for 25% of the total users.
Instead, when the feature is checked with
enabled?, it will return
true 25% of the time.
If you are not certain what percentages to use, simply use the following steps:
Between every step you’ll want to wait a little while and monitor the appropriate graphs on https://dashboards.gitlab.net. The exact time to wait may differ. For some features a few minutes is enough, while for others you may want to wait several hours or even days. This is entirely up to you, just make sure it is clearly communicated to your team, and the Production team if you anticipate any potential problems.
Feature gates can also be actor based, for example a feature could first be
enabled for only the
gitlab project. The project is passed by supplying a
/chatops run feature set --project=gitlab-org/gitlab some_feature true
For groups the
--group flag is available:
/chatops run feature set --group=gitlab-org some_feature true
Note that actor-based gates are applied before percentages. For example, considering the
gitlab-org/gitlab and a given example feature as
you run these 2 commands:
/chatops run feature set --project=gitlab-org/gitlab some_feature true /chatops run feature set some_feature 25
some_feature will be enabled for both 25% of users and all users interacting with
Once the change is deemed stable, submit a new merge request to remove the feature flag. This ensures the change is available to all users and self-managed instances. Make sure to add the ~”feature flag” label to this merge request so release managers are aware the changes are hidden behind a feature flag. If the merge request has to be picked into a stable branch, make sure to also add the appropriate “Pick into X” label (e.g. “Pick into XX.X”). See the process document for further details.
When a feature gate has been removed from the code base, the feature record still exists in the database that the flag was deployed too. The record can be deleted once the MR is deployed to each environment:
/chatops run feature delete some_feature --dev /chatops run feature delete some_feature --staging
Then, you can delete it from production after the MR is deployed to prod:
/chatops run feature delete some_feature