How do I avoid blowing up Prometheus with change metadata?

Keep high-cardinality fields (commit_sha, feature_flag) off hot-path metrics. Put them on traces and logs, and emit low-cardinality change counters (deploy_started_total{service="api"}). Use Grafana annotations for human context.

We’re on Datadog/New Relic. Does this still apply?

Yes. The pattern is tool-agnostic: emit change events, enrich traces, define SLOs with multi-window burn alerts, and gate rollouts. Replace the PromQL and Argo examples with your vendor’s equivalents (Datadog monitors, NerdGraph, Spinnaker/Kayenta).

Will this work with service meshes like Istio or Linkerd?

Absolutely. Meshes expose golden signals automatically. Use Flagger for canary analysis on top of Istio/Linkerd, and make sure `x-request-id`/`trace_id` is propagated from edge to workloads so logs and traces correlate.

What about legacy monoliths with no tracing?

Start by injecting an ingress proxy that adds a request ID and logs it. Use that ID to correlate logs across tiers, then gradually add OpenTelemetry agents. You can still do burn rate and queue growth today.

Reliability-observability · Nov 20, 2025 · 10 minute read

The Correlation Engine: Predicting Incidents and Rolling Back Before Users Notice

Stop guessing. Wire your telemetry to the change stream, surface real leading indicators, and let rollouts auto-correct before the pager lights up.

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The Correlation Engine: Predicting Incidents and Rolling Back Before Users Notice

Key takeaways

Implementation checklist