Merge strategies to keep builds healthy at scale

Merging changes in a monorepo can be challenging, especially as team size grows. The main issue is that dependencies between different changes can cause implicit conflicts, leading to failed builds and delayed releases. To address this, merge automation can be used to validate changes with the latest mainline before merging them. Batching changes can also reduce the number of CIs needed, but may increase wait times in case of failures. Predictive modeling can identify which PRs are likely to pass or fail, reducing the number of CIs needed. Multi-queues can be used to run different builds independently, and further optimization techniques such as reordering changes, fail-fast testing, and splitting test execution can also improve merge efficiency. By combining these strategies, teams can reduce the time it takes to merge changes from hours to under an hour, even in cases with a 10% failure rate.

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