Stop debugging Kubernetes at 2 AM with 15 different kubectl commands.
When a pod enters CrashLoopBackOff in production, 80% of your time isn't spent fixing the problemβit's wasted context-switching between kubectl describe, previous logs, events, and YAML specs trying to find what actually broke.
I built π©Ί KubeDoctor β an autonomous Kubernetes diagnostic and incident triage platform that brings complete clarity in seconds.
Here is what's happening in the 28-second demo [watch video]:
π Instant Root Cause Analysis: Auto-diagnoses CrashLoopBackOff, Missing Secrets, Broken Service Selectors, and Node DiskPressure.
π‘ SRE-First Remediation: Generates the exact, copy-pasteable CLI command to fix the issue immediately without guesswork.
π Container Crash Forensics: Streams live container crash tracebacks with instant keyword search.
π Chronological Events Timeline: Correlates Kubernetes warning and normal events in real time.
π Automated Post-Mortem Export: Generates a complete 4-section Markdown incident report with one click.
Built with Python & the Kubernetes Client API, and tested end-to-end with Microsoft Playwright browser automation.
π Question for DevOps & Platform Engineers:
When an incident strikes in production, do you prefer getting the exact CLI fix to verify and run manually, or do you prefer the system to auto-heal autonomously?
Let me know your thoughts in the comments! π
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