Shift left on checks
Run smoke synthetics in staging and again on canary slices before full rollout. Include contract tests for downstream APIs, rate limits, and auth flows so surprises don't reach customers.
Block deploys when SLO burn is already high or key monitors are flapping. A simple budget gate prevents pushing risk onto an unhealthy system.
Record the deploy ID in Watch.Dog so alerts and traces show which build is live where.
Automate rollbacks
Trigger rollback on failing health checks within minutes, not after a human debate. Health signals should include synthetic journeys, not just CPU and 200-counts.
Make rollback commands part of runbooks and pipeline steps so anyone on-call can execute safely. Store them alongside feature flag toggles as a first responder kit.
Verify rollback success with a second round of synthetics and customer journey checks before reopening traffic.
Pipeline safeguards
- Canary stages
- Automatic rollback hooks tied to customer SLIs
- Feature flag kill switches with audit trails
Keep stakeholders aware
Notify status page owners when risky deploys begin so comms stay ahead of customers. Pre-draft messaging for known-risk releases and keep it ready in Slack.
Log deploy IDs in incidents to speed triage and postmortems. If a rollback happens, annotate the status page and dashboards with the exact build that was reverted.
Review deploy health weekly: which safeguards fired, which were noisy, and where you need more coverage.
Measure and tune
Track rollback frequency, canary failure rates, and time-to-detect after each deployment. Use those metrics to tune thresholds and decide when to invest in more synthetic coverage.
Give teams a dry-run mode so they can rehearse rollbacks and feature flag kills outside of incidents.