~/talk

Developer Productivity Engineering Deep Dive

github:jreock
slides:none on file

Argues concrete DPE wins: a build cache (Gradle/Maven) reuses task outputs to cut builds — demo shows ~70% local time saved — and remote cache + Docker/Kubernetes agents enable test distribution for parallel runs; Netflix cuts a 62‑minute test cycle to under 5 minutes, a tiny team gains ~44 engineering days/year, and Gradle’s dataset shows ~5,600 days saved in a month. Adds analytics via build scans, and ML using XGBoost for predictive test selection (pre‑merge only); tools and demos are operational and repeatable.

AI-written summary · about

  1. 0:00Introduction and setup
  2. 1:24What is Developer Productivity Engineering
  3. 3:53Developer experience challenges
  4. 8:09Why developer joy matters
  5. 11:39Fast feedback cycles importance
  6. 19:05Build caching explained
  7. 25:43Build caching demo
  8. 29:58Test distribution techniques
  9. 33:06Machine learning in builds
  10. 39:00Efficient troubleshooting
  11. 42:07Eliminating flaky tests
  12. 46:39Metrics and observability
  13. 50:48Summary and next steps
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