What’s the difference between vanity metrics and leading indicators?

Vanity metrics (average CPU, total requests) look calm until customers scream. Leading indicators (p99 tails, burn-rate, queue depth, error spikes per version) move early and correlate with user pain. They’re also specific enough to gate automation.

Can this work for a monolith (not microservices)?

Yes. Add `service.version` and `git.sha` to the monolith’s telemetry, define SLOs on its critical endpoints, and compare new vs. baseline. The gating logic is the same. Many of our clients started with a monolith and saw the biggest gains.

How do we handle mobile releases?

Tag client telemetry with `app.version` and track crash rate, cold-start p95, and request failures per build. Use phased rollouts (App Store/Play Console) and gate on release health. Feature flags help decouple code ship from exposure.

We don’t have OpenTelemetry yet. Is this blocked?

No. Start by adding `service.version` and `git.sha` labels to Prometheus metrics and logs. You can retrofit traces later. The key is version-aware comparability and wiring queries into your rollout tool.

What thresholds should we use?

Start conservative: fail if new p99 is >15% worse than baseline, or if burn-rate >2x budget on the 1h window. Tune based on noise and business risk. Keep thresholds per service, not global.

How do we prevent alert fatigue?

Use dual-window burn-rate, alert on ratios (new vs. baseline), and aggregate by symptom (endpoint, dependency) rather than host. Make alerts actionable with rollback commands and owners. Kill any alert that didn’t inform a decision in the last month.

Reliability-observability · Oct 2, 2025 · 9 minute read

The Release Health Playbook: Catch Regressions With Signals That Actually Predict Incidents

If your rollout strategy is “watch Grafana and pray,” you’re shipping blind. Instrument release health with version-aware telemetry and wire it directly into your canaries, flags, and triage. Stop discovering regressions from Twitter complaints.

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The Release Health Playbook: Catch Regressions With Signals That Actually Predict Incidents

Key takeaways

Implementation checklist