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@@ -148,3 +148,30 @@ 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.
### The benefits of feature flags
It may seem like feature flags are configuration, which goes against our [convention-over-configuration](https://about.gitlab.com/handbook/product/product-principles/#convention-over-configuration)
principle. However, configuration is by definition something that is user-manageable.
Feature flags are not intended to be user-editable. Instead, they are intended as a tool for Engineers
and Site Reliability Engineers to use to de-risk their changes. Feature flags are the shim that gets us
to Continuous Delivery with our mono repo and without having to deploy the entire codebase on every change.
Feature flags are created to ensure that we can safely rollout our work on our terms.
If we use Feature Flags as a configuration, we are doing it wrong and are indeed in violation of our
principles. If something needs to be configured, we should intentionally make it configuration from the
first moment.
Some of the benefits of using development-type feature flags are:
1. It enables Continuous Delivery for GitLab.com.
1. It significantly reduces Mean-Time-To-Recovery.
1. It helps engineers to monitor and reduce the impact of their changes gradually, at any scale,
allowing us to be more metrics-driven and execute good DevOps practices, [shifting some responsibility "left"](https://devops.com/why-its-time-for-site-reliability-engineering-to-shift-left/).
1. Controlled feature rollout timing: without feature flags, we would need to wait until a specific
deployment was complete (which at GitLab could be at any time).
1. Increased psychological safety: when a feature flag is used, an engineer has the confidence that if anything goes wrong they can quickly disable the code and minimize the impact of a change that might be risky.
1. Improved throughput: when a change is less risky because a flag exists, theoretical tests about
scalability can potentially become unnecessary or less important. This allows an engineer to
potentially test a feature on a small project, monitor the impact, and proceed. The alternative might
be to build complex benchmarks locally, or on staging, or on another GitLab deployment, which has an
outsized impact on the time it can take to build and release a feature.
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