Advanced Feature Flagging: It's All About The Data - Dave Karow
Feature flags deliver the control needed to decouple deploy from release but can break traditional monitoring and KPIs.
Cloud-native teams use feature flags to "kill the release night," and they rethink how they monitor system health and user behavior to automate early detection of anomalies. Moving faster and limiting risk with progressive delivery techniques will make you safer but only if you improve early visibility, not compromise it.
We'll look at advanced implementation techniques that marry the precision control of feature flags with automated ingest of data and statistical computation of KPIs. This allows teams to proactively identify system performance and user behavior differences between the status quo and new code. Advanced feature flagging implementations “build-in” observability to every release. When you push a feature to 5% of users, it becomes trivial to see how user and system behavior varies for those users vs. the other 95%. Teams further along this journey auto-calculate “do-no-harm" metrics, so it’s easy to detect unintended consequences of their work before ramping up to all users.
You’ll leave this session with a clear vision of how your team can automate statistical analysis of gradual releases to achieve the same benefits, either by enhancing your in-house solution or complementing it with available tools.