monitoring-observability

Monitoring Kubernetes clusters requires deploying Prometheus to scrape metrics, Grafana to visualize dashboards, and configuring alerting rules. This Skill guides you through installing these components, generating Prometheus scrape configs, and building Grafana dashboards tailored to your cluster's health and performance.

Structured logging with an ELK stack or Loki aggregates logs across microservices for centralized analysis. This Skill teaches log collection patterns, query syntax (LogQL), and best practices for extracting actionable insights from distributed application logs.

Distributed tracing with OpenTelemetry instruments applications to capture request flows across services, showing latency and failure points. This Skill provides patterns for integrating OpenTelemetry collectors and correlating traces with metrics and logs.

Yes. Prometheus collects time-series metrics; Grafana visualizes them via dashboards and alerts. This Skill covers the full integration, including PromQL queries, dashboard design, and alert rule configuration for production environments.

You'll need familiarity with Docker, Kubernetes basics, and understanding that observability requires three pillars: metrics (Prometheus), logs (ELK/Loki), and traces (OpenTelemetry). This Skill assumes you're ready to adopt these tools across a cloud-native stack.

Performance degradation in distributed systems stems from latency, resource saturation, and cascading failures across services. Observability prevents this by providing real-time visibility through metrics, logs, and traces, enabling proactive detection and faster incident response.