splunk-ai-operator

Splunk AI Operator Documentation

Welcome to the Splunk AI Operator documentation!

Getting Started

1. Installation Guide - Install the operator in your Kubernetes cluster
2. API Reference - Complete CRD specification
3. Local Development - Set up local development environment
4. Troubleshooting - Common issues and solutions

Deployment Guides

• Helm Deployment - Deploy using Helm charts
• AWS EKS Deployment - Production deployment on AWS EKS

Configuration Guides

• Storage Configuration - Persistent storage for Weaviate vector database
• Storage Artifacts - S3/GCS/Azure storage for AI models
• Ingress Configuration - Expose AI services externally
• Webhook Certificates - Configure admission webhook TLS

Project Documentation

• Open Source Readiness - OSS preparation checklist
• OSS Preparation Summary - Complete summary of OSS prep work
• Documentation Organization - How docs are organized

Quick Reference

Check if Platform is Ready

kubectl get aiplatform <name> -n <namespace>

View Status Details

kubectl get aiplatform <name> -n <namespace> -o jsonpath='{.status.conditions}'

Watch Events

kubectl get events -n <namespace> --watch --field-selector involvedObject.name=<name>

Common Tasks

Configure persistent storage:

spec:
  storage:
    vectorDB:
      size: "100Gi"
      storageClassName: "gp3"

Enable external access:

spec:
  ingress:
    enabled: true
    className: nginx
    hosts:
      - host: ai.example.com
        paths:
          - path: /
            pathType: Prefix

Check what’s failing:

kubectl get aiplatform <name> -o jsonpath='{.status.conditions}' | jq '.[] | select(.status=="False")'

Need Help?

1. Check Error Handling and Events for troubleshooting guides
2. View operator logs: kubectl logs -n splunk-ai-operator-system deployment/splunk-ai-operator-controller-manager
3. Report issues with diagnostic info (see troubleshooting guide)

Documentation Organization

• Getting Started - Installation and basic setup
• Configuration Guides - Detailed configuration for specific features
• Monitoring - Understanding status and troubleshooting
• Architecture - System design and components

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