How to use feature flags

This document will take you through how to add, remove, and modify feature flags.

When to use feature flags

Feature flags, as opposed to experimental features, are intended to be strictly short-lived. They are designed to be useful for A/B testing, and the values of all active feature flags are added to every event log for the purpose of analytics.

How it works

Each feature flag is either a static feature flag, or a “rollout” flag.

  • A static feature flag has a single value (currently only “true” or “false”) for all users that haven’t overriden it.
  • A rollout flag assigns a random (but stable) value to each user. Each rollout flag is created with a percentage of users that should be randomly assigned the value “true”.

A user is identified either by their user ID (if logged in), or by an anonymous user ID in local storage.

The set of evaluated feature flags is appended to each event log so they can be queried against for analytics.

Example lifecycle of a feature flag (for frontend A/B testing)

The standard use of a feature flag for A/B testing a frontend feature will look like the following:

  1. Implement the feature that you want to be behind a feature flag
  2. Deploy to
  3. Create the feature flag through the GraphQL API
  4. Measure the effect of the feature flag
  5. Disable or delete the feature flag
  6. Remove the code that references the feature flag

Implement the feature flag


In the frontend, evaluated feature flags map for the current user is available on the SourcegraphWebAppState. The map can be prop-drilled into the components that need access to the feature flags.

Ensure that a default value is set for feature flags so that (i) code can be deployed before creating the feature flag, (ii) deleting the feature flag is safe before removing referenced code, (iii) enterprise deployments continue to work as expected.

You can add a new feature flag by adding the name as a new case to the FeatureFlagName type:

export type FeatureFlagName = ... | 'my-feature-flag'

Feature flags are stored in a map with the type Map<FeatureFlagName, boolean>. Using FeatureFlagName as the map key ensures that we can only access feature flags defined in the type. Deleting a flag name from FeatureFlagName type will also result in a compiler error if the flag is still referenced somewhere.

Example usage:

const evaluatedFeatureFlagValue = featureFlags.get('my-feature-flag') ?? false

featureFlags.get('unknown-feature-flag') // compiler error


In the backend, the featureflag package provides the implementation of feature flag functionality.

The entrypoint for most developers that wish to read feature flags should be the featureFlag.FromContext function, which retrieves the current set of feature flags from a request’s context object. featureFlag.GetBool / featureFlag.GetBoolOr can then be used to read flags from the FlagSet that featureFlag.FromContext returns.


import ""

flags := featureFlag.FromContext(ctx)
value := flags.GetBoolOr("foo", false)


When writing code that uses feature flags, you may wish to avoid needing to pass a context.Context (for featureFlag.FromContext()) in every function that consumes it for a variety of reasons (avoiding mixing concerns, lack of type safety, etc.). See search: add Features type #28969 for an example of a pattern in the search code base that successfully minimizes the need to pass around a full context object.

Create the feature flag through the GraphQL API

To create a rollout feature flag, currently the best way is to use the GraphQL API.

Go to, then create a feature flag like the following:

mutation CreateFeatureFlag{
    name: "myFeatureFlag",
    rolloutBasisPoints: 5000,

The value of rolloutBasisPoints is measured in increments of 0.01% (a basis point). To create a feature flag that applies to 50% of users, set rolloutBasisPoints to 5000.

Measure the effect of the feature flag

Feature flags are added as a column to all event logs, so in order to measure any effect, there needs to be a related event for it. For example, to compare the number of ShareButtonClicked events between groups where myFeatureFlag is enabled and disabled, you could use a query like the following:

	JSON_VALUE(feature_flags, '$.myFeatureFlag') AS my_flag, 
FROM `` 
WHERE name = 'ShareButtonClicked' 
GROUP BY my_flag;

Disable or delete the feature flag

In most cases, after an A/B test is performed, a feature flag should be deleted. That can be done with a GraphQL query like the following:

mutation DeleteFeatureFlag{
    name: "myFeatureFlag",

Once a feature flag is deleted, it will no longer be added to events as metadata, so removing the code path that uses it will not change any measurements.

Remove the code that references the feature flag

Once the feature flag is deleted, the code that references it can be safely deleted without changing any of the measurements.

Feature flag overrides

In addition to feature flags as described above, you can also create feature flag overrides. This is useful if you’d like to test a feature flag locally by assigning your user a specific value, or if you’d like to do an A/B test on members of the Sourcegraph org.

Overrides can either apply to a single user or an entire org. If both are set, a user override takes precedence over an org override.

If an override for a feature flag exists for a user (or the user’s org), the value of the override will be used instead of the value that would have been randomly selected for a user.

Creating an override

To create a feature flag override, you can use a graphql query like the following:

mutation CreateFeatureFlagOverride{
    namespace: "Vx528v=", 
    flagName: "myFeatureFlag",
    value: false,

The namespace argument is the graphql ID of either a user or an organization.

Listing all feature flags (including A/B tests)

To list all currently running A/B tests:

query FetchFeatureFlags {
  featureFlags {
    ... on FeatureFlagBoolean {
    ... on FeatureFlagRollout {

Further reading