Feature Flagging: Proven Patterns for Control and Observability in Continuous Delivery

Dave Karow

[video:https://youtu.be/cpfjfUqbVds width:300 height:200 align:right]

Are you moving faster than fast? Congrats! Chances are you already use feature flags to decouple code deployments from feature rollouts. Whether you use a roll-your-own feature-flagging solution (with a few quirks) or a feature-flags-as-a-service solution, hopefully you post feature flag rollout changes to something like Datadog so that when a flag rollout lines up with an obvious spike, you know whom to have a talk with. It's a solid start, but that’s just the basics. What do data-driven CD ninjas do? They build in observability to every feature release, so when they push a feature to 5 percent of users, it’s zero work to see how user and system behavior for those users compares to the other 95 percent. Ninjas also auto-calculate guardrail metrics, so when a change is pushed to locally optimize something, it’s easy to detect unintended consequences that impact organization-wide metrics. You’ll leave this session with a clear vision of how your team can achieve the same benefits, by either enhancing your in-house solution or adopting a commercial tool.

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