Kubernetes observability involves collecting metrics, logs, and traces to understand cluster internal state and performance. The three pillars include metrics for quantitative data, logs for timestamped events, and traces for request paths through microservices. Key tools include Metrics-Server for basic monitoring, Kube-Prometheus-Stack for comprehensive metrics and visualization, ELK stack for log management, and OpenTelemetry for distributed tracing. Implementation challenges include managing multiple data types, monitoring dynamic resources, handling large data volumes, and preventing data silos. Best practices emphasize setting up alerts, consistent resource labeling, application instrumentation, selective data collection, and compliance alignment.
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