Cluster Events Hub
Filter and search Kubernetes events, correlate with failing pods, and prioritize warning patterns.
AI for SRE and Platform Teams
Troubleshoot Kubernetes faster with AI-guided diagnosis.
KubePilot combines cluster events, node pressure, pod diagnostics, and topology views into one workflow. Engineers can inspect incidents and run AI analysis without jumping across multiple tools.
Built for CrashLoopBackOff, scheduling failures, mount issues, and noisy clusters
What teams get from KubePilot
A practical incident workflow that blends observability context with AI recommendations.
Node and Resource Health
Detect pressure signals and capacity hotspots early with CPU and memory utilization visibility.
Pod Deep Inspection
Open pod diagnostics for status, conditions, events, and logs in one drill-down panel.
AI Root-Cause Guidance
Use AI suggestions to triage faster and identify safer remediation actions during incidents.
Product Screenshots
These screenshots are sourced from the repository docs folder for GitHub-friendly documentation.
How incident triage works
A simple 4-step loop to reduce mean-time-to-resolution.
1. Open Cluster Events and identify warnings, pressure, and failing pods.
2. Inspect a problematic pod for logs, event history, and container state.
3. Run AI Analyze to infer probable root cause and remediation strategy.
4. Validate impact using topology and cluster health before/after action.
Install and run
Use source build for now and run locally on your current kubeconfig context.
git clone https://github.com/kubepilot/kubepilot.git
cd kubepilot
make dashboard-install
make dashboard
make build
KUBEPILOT_KUBECONFIG="$HOME/.kube/config" ./dist/kubepilot serve --dashboard-port=8383