k8s-ai-cli 0.1.5

CLI that explains Kubernetes pod failures from logs using AI. Works locally with kubectl.

k8s-ai

A Python CLI for Kubernetes pod failure triage using AI-powered log analysis.

Features

• Reads pod logs directly through your local kubectl context
• Uses OpenAI Python SDK v1.x for log analysis
• Returns likely root cause, confidence level, and remediation guidance
• Supports --mock, --previous, --container, and --timeout

Installation

pip install k8s-ai-cli

Quick Start

k8s-ai default my-pod
k8s-ai default my-pod --mock
k8s-ai default my-pod --previous
k8s-ai default my-pod --container app

Mock Example

k8s-ai default my-pod --mock

Real Cluster Example

# Current pod logs
k8s-ai default my-pod

# Previous logs (useful for CrashLoopBackOff)
k8s-ai default my-pod --previous

# Target a specific container
k8s-ai default my-pod --container app

Environment Variables

k8s-ai requires an OpenAI API key.

Linux/macOS:

export OPENAI_API_KEY="your_api_key_here"

Windows PowerShell:

$env:OPENAI_API_KEY="your_api_key_here"

How It Works

1. Collects logs for the target pod using kubectl.
2. Sends relevant log context to an OpenAI-compatible model (OpenAI SDK v1.x).
3. Produces structured output with probable cause, confidence, and remediation steps.

Safety

• Runs locally on your machine.
• Uses your current kubectl permissions and context.
• Does not persist collected pod logs by default.

Roadmap

• Broader failure-pattern coverage for common Kubernetes workloads
• Optional structured output modes for CI and automation
• Additional debugging context integration (events/describe)

License

MIT