debug-prod

Debug production issues in Kubernetes by systematically gathering data on pods, logs, metrics, alerts, and deployments to identify patterns and pinpoint likely root causes. This approach correlates signals across system components to diagnose unexpected downtime or critical service failures.

Investigate production alerts by aggregating data across Prometheus, Kibana, and Slack to identify patterns in logs and metrics. This systematic approach correlates alerts with deployment events and pod states, suggesting likely causes for the observed service degradation.

Diagnosing a production deployment failure requires a namespace, alert name, pod filter, and time range. Optionally providing a Jira issue key adds further context, enabling the investigation to gather targeted pod logs, metrics, and deployment data for root cause analysis.

Find the root cause of unexpected downtime by analyzing pod logs and metrics together to reveal patterns across Kubernetes, Prometheus, and Kibana. Collecting these data points alongside alert histories and deployment records identifies likely systemic causes.

Production service unexpected downtime after a recent deployment often stems from configuration or resource issues identified by analyzing deployment data alongside pod metrics and logs. Correlating these deployment events with alerts and Kibana logs isolates the triggering pattern.