Continuous Delivery - What does good really look like?
summary
Continuous delivery means keeping software permanently releasable by evaluating a deployable release candidate after every small commit using a deployment pipeline and automated tests. Measure success by throughput (lead time, release frequency) and stability (change‑failure rate, recovery time). Expect commit‑cycle feedback under five minutes, thousands+ fast in‑memory tests, and acceptance/production stages. Real results: Amazon deploys ~1.5 changes/sec, Volvo cuts rollout from six months to <20 minutes, SpaceX accepts updates 40 minutes prelaunch, Tesla reconfigures a factory in three hours, LMAX runs 13 months before first user‑facing bug.
AI-written summary · about
chapters (11)
- 0:00Introduction
- 1:36Two key metrics
- 2:52Speed vs quality
- 4:10The Art of Action
- 8:15Working
- 13:28Confidence
- 14:08Optimize for Learning
- 19:18Deployment Pipeline
- 23:23Software Engineering
- 24:13Impact
- 24:58Examples
related talks
55mThe Rationale for Continuous Delivery
40mSustainable Continuous Delivery: Patterns for rapid and reliable Releases
45mContinuous Delivery in a World of Constant Change
28mMinimum Viable Continuous Delivery
45mTurning continuous delivery into competitive business advantage
36mWhat do we know about continuous delivery – and what would we like to know
38mContinuous Delivery, or the magic button for on‑demand releases
32mContinuous Delivery Sounds Great But It Won’t Work Here
