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Understanding machine learning models
Improving data analysis and decision-making
How Google uses logic in machine learning
What is a feature flag?
Feature flags are a current best practice to decouple deployment from exposure. A single release artifact can have features conditionally enabled without requiring a new deployment. These flags can be used to implement a variety of features, such as user-based opt-in, A/B testing , incremental rollback, and the graceful sunsetting of features.
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Feature Flagging Data
Once we were ready to test the new database, we simply flipped the toggle for a particular repository. On occasion, we needed to rollback due to performance issues. Because we were always writing to both databases, this rollback had very low risk.
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Flags and Trunk Development
The combination of trunk based development and feature flags provide several benefits over Gitflow and other branching strategies. With Gitflow, a feature is not merged in until it is ready for release. In addition, you are only able to rollback at the release level, not the feature...
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