The model
Continuous delivery makes a change releasable through repeatable build, validation, and deployment steps. Observability uses emitted signals to infer internal state from outside the system. Together they shorten feedback loops and make it possible to detect whether a release behaves as expected.
A concrete walk-through
A pipeline can build an artifact once, run checks, deploy it to a small cohort, and compare error rate and latency before widening rollout. Logs explain individual events, metrics show aggregated trends, and traces connect work across service boundaries. A rollback plan should identify what state changes are reversible.
Costs and failure cases
A green pipeline only proves its configured checks passed. A deployment can expose a configuration or migration issue that tests did not model. Alerts need actionable thresholds; excessive noisy alerts train responders to ignore the signal.
Check your understanding
A release doubles p95 latency while average latency barely changes. Which percentile, trace, and rollout data would you inspect to decide whether to halt or roll back?