K8sGPT
Diagnose and resolve Kubernetes cluster issues using AI analysis
Target Audience
- DevOps Engineers
- Site Reliability Engineers
- Kubernetes Administrators
- Cloud Platform Teams
Hashtags
Overview
K8sGPT scans your Kubernetes clusters to identify problems using codified SRE knowledge. It translates complex technical signals into easy-to-understand recommendations, helping teams prioritize critical issues. The AI-powered analysis cuts through noise to focus on what matters most, saving hours of manual troubleshooting.
Key Features
Workload Analysis
Identify critical issues in Kubernetes workloads
AI Noise Reduction
Focus on relevant cluster issues using AI filtering
Security Scanning
Integrate with Trivy for CVE vulnerability detection
SRE Knowledge Base
Built-in troubleshooting patterns from real-world experience
Multi-Cluster Support
Works with all CNCF-conformant Kubernetes clusters
Use Cases
Diagnose cluster configuration issues
Monitor workload health status
Triage security vulnerabilities
Automate SRE knowledge application
Pros & Cons
Pros
- Built-in SRE expertise codified into analyzers
- Supports multiple AI backends for flexibility
- Compatible with all major Kubernetes distributions
- Reduces troubleshooting time significantly
Cons
- Primarily focused on Kubernetes (no other infrastructure)
- Requires separate integration for CVE scanning
- Limited to N-2 Kubernetes versions support
Frequently Asked Questions
Which Kubernetes versions does K8sGPT support?
Supports all CNCF-conformant Kubernetes clusters up to N-2 releases
Can I use my own AI models with K8sGPT?
Yes, supports multiple AI backends including LocalAI for local model execution
Does K8sGPT replace security scanners like Trivy?
No, it integrates with Trivy to help triage identified vulnerabilities
Integrations
Reviews for K8sGPT
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