Java - microservices
summary
Beekeeper moves a Python monolith into ~40 services over four years to speed deploys and enable mixed tech stacks, then solves the resulting duplication with a Yeoman generator to cut bootstrap from an hour to ~3 minutes, a custom Gradle plugin published to centralize build checks, and a test-support + Wiremock pattern so dependency upgrades are verifiable. Operations use Kubernetes readiness probes, ELK for centralized logs, and Jenkins automation; multi-repo layout creates the most pain.
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chapters (15)
- 0:00Introduction to Beekeeper
- 2:40Why switch to microservices
- 5:27Monolith vs microservices trade-offs
- 7:35Benefits of microservices architecture
- 10:48Developer experience focus
- 11:31Choosing frameworks and repositories
- 13:41Bootstrapping services efficiently
- 15:27Gradle plugin for consistency
- 18:17Testing microservices challenges
- 21:58Health checks and dependencies
- 24:23Kubernetes and readiness checks
- 25:28Centralized logging setup
- 27:15Reusable configuration bundles
- 27:57Automation with Jenkins
- 28:17Conclusion and key takeaways
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