Coroot addresses the fundamental friction in Kubernetes observability: the requirement to instrument every application with tracing libraries, metrics exporters, and logging frameworks before getting any visibility. By leveraging eBPF to capture network traffic, system calls, and application behavior at the kernel level, Coroot provides comprehensive observability from the moment it is deployed without touching a single line of application code.
The platform automatically generates application topology maps showing service dependencies and communication patterns, provides request-level latency analysis with breakdown by service and endpoint, correlates distributed traces with relevant log entries, and offers continuous CPU and memory profiling to identify performance bottlenecks. Anomaly detection algorithms establish baselines for normal behavior and alert when metrics deviate significantly, reducing alert fatigue through intelligent thresholding.
Coroot integrates with existing observability stacks by supporting OpenTelemetry for data export, Prometheus for metrics storage, and ClickHouse for high-performance log and trace analysis. The deployment model is Kubernetes-native with Helm chart installation that deploys eBPF agents as a DaemonSet across cluster nodes. With over 5,000 GitHub stars, Coroot competes with commercial observability platforms like Datadog by offering comparable functionality at a fraction of the cost through self-hosted deployment.
