Deployment Correlation

Definition

Deployment correlation relates release versions and rollout events to changes in service behavior.

Signals

• Metrics
• Traces
• Events

Why use it

Compare an error-rate increase with the version and instances that received a release.

Common use cases

• Evaluate canaries
• investigate regressions
• compare versions before rollback.

Benefits

• Makes release hypotheses specific to a version and affected service.

Limitations

• Concurrent changes, traffic shifts, and partial rollouts can confound comparisons. Timing alone cannot prove a release caused an incident.

Practical pattern

Attach service, environment, and version to telemetry. Record rollout timing and compare equivalent cohorts and traffic conditions.

Supported by

Documented examples, not an exhaustive compatibility list. Features require suitable instrumentation and configuration; availability can depend on the runtime, backend, and subscription.

• Datadog — Deployment tracking compares service performance across deployed versions.
• Grafana — Release annotations provide a timeline for manual comparison.

Related concepts

• Event Correlation
• Metric Correlation
• Root Cause Analysis

Investigation patterns

• Deployments to Error Rate

Related guides

• What is Observability?
• DORA Metrics Explained
• Deployments: Compare Error Rate by Version

FAQ

Should every post-release spike trigger rollback?

Investigate impact, affected cohorts, and alternative explanations. Use your rollout policy and service objectives to decide.