How Bazel Achieves Test Parallelism
Fine-Grained Dependency Analysis
Bazel uses a dependency graph to identify which tests can run independently in parallel. Tests that don’t interfere with each other are executed simultaneously.
Dynamic Test Scheduling
Bazel automatically schedules tests based on available resources (multi-core machines or distributed systems). It maximizes resource usage by running as many tests in parallel as possible.
Remote Execution and Caching
Tests can be offloaded to remote machines, increasing parallel execution. Caching skips re-running tests with unchanged dependencies, speeding up the testing process.
Remember the Three Pillars
- Dependency Graph – What tests can run together.
- Dynamic Scheduling – How tests are efficiently scheduled.
- Remote Execution + Caching – Where tests run and how Bazel skips unnecessary work.
Both CPS and Bazel solve problems of parallelism and concurrency by organizing tasks and scheduling them efficiently. While CPS is more about program flow and concurrency within the code, Bazel applies similar ideas at a higher level to optimize build and test workflows.
Best Practices for Maximizing Test Isolation and Parallelism
- Keep Tests Small and Focused: The smaller and more focused a test is, the faster it will run, and the easier it will be to parallelize with other tests.
- Avoid Global State: Global state can introduce dependencies between tests that Bazel cannot account for. Always aim for stateless tests.
- Use Bazel’s Test Tags: Bazel allows you to tag tests (for example,
integration,unit,slow). You can use these tags to group and manage your tests. - Monitor and Optimize: Regularly monitor your test runtimes and look for opportunities to optimize.
vs CPS?
Both CPS and Bazel solve problems of parallelism and concurrency by organizing tasks and scheduling them efficiently. While CPS is more about program flow and concurrency within the code, Bazel applies similar ideas at a higher level to optimize build and test workflows.