Payment Service HTTP 503 Spike After Release

To diagnose HTTP 503 spikes after a release, you need to collect metrics, logs, and traces from data sources like Prometheus and Loki. This Skill automates that evidence collection and analyzes it to determine if a release regression is the likely cause.

To safely rollback a payment service deployment causing a 503 spike, this Skill analyzes collected evidence to confirm a release regression. It then proposes a recommended rollback action to a previous version after performing a dry run and approval.

Yes, this diagnosis process works with Prometheus and Loki data sources, along with Trace and Deploy data. It integrates with these systems to gather the evidence needed for detecting release regressions.

The best way to determine if a 503 error spike is a release regression is to correlate deployment data with error metrics and logs. This Skill uses decision logic to analyze collected evidence and identify if a recent release caused the spike.

You need a dry run before rolling back your payment service to ensure the proposed rollback path is safe and will not cause further disruption. This Skill recommends a rollback only after a dry run and explicit approval.