Kubernetes Observability Stack

Multiple teams shared a Kubernetes platform but had no unified visibility into cluster health, application latency, or logs. Incidents required correlating information across separate tools, leading to slow root-cause analysis and prolonged outages. Alerting was noisy and uncorrelated.

A single observability stack combines Prometheus for metrics, Loki for logs, and Grafana for visualization. kube-prometheus-stack provides out-of-the-box Kubernetes dashboards and alert rules. Promtail ships logs to Loki, with structured logging conventions enforced across services. Alertmanager routes alerts based on labels and severity, with critical alerts going to PagerDuty and informational alerts to Slack.

The stack was deployed via Helm with a custom values overlay for multi-cluster federation. Service-specific Prometheus scrape configs and recording rules were defined for key SLIs. Grafana dashboards were provisioned from ConfigMaps for version control. Long-term metric storage was configured via Thanos with S3 backend, enabling months of historical data without overloading local storage.

Grafana is secured with SSO via OAuth, with role-based access control per team. Prometheus and Loki have network policies restricting access to the observability namespace. Sensitive log data is scrubbed via Promtail pipeline stages before ingestion. Remote write to Thanos uses short-lived STS tokens.

SLOs were defined for each service with error-budget-based alerting — alerts fire only when the error budget is being consumed, reducing noise. Dashboards show latency percentiles, request rates, error rates, and log volume per service. A "golden signals" dashboard gives on-call engineers an immediate view of system health during incidents.

Mean time to detection dropped significantly. On-call engineers now see correlated metrics and logs in a single pane, enabling faster root-cause analysis. SLO-based alerting reduced alert fatigue and focused attention on issues that actually impact users.