Obliq AI SRE Agent Platform

A comprehensive AI-powered Site Reliability Engineering platform deployed as a single Helm chart.

Helm Chart Kubernetes AI/SRE Support

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📖 Documentation

⚡ Quick Install

Prerequisites

📚 Important Setup Guides:

💡 For local development: Run ./scripts/update-dependencies.sh to ensure all chart dependencies are resolved before local installation.

📋 Note: The --set-file global.kubeconfig.content=./kubeconfig parameter expects a kubeconfig file in the current directory. Make sure to:

1. Add Helm Repository

# Add the Obliq Charts Helm repository
helm repo add obliq-charts https://repo.obliq.avesha.io/
helm repo update

2. Create Registry Secret

# Get credentials from support@aveshasystems.com
kubectl create namespace avesha --dry-run=client -o yaml | kubectl apply -f -
kubectl create secret docker-registry registry \
  --docker-username=YOUR_USERNAME_FROM_AVESHA \
  --docker-password=YOUR_PASSWORD_FROM_AVESHA \
  --docker-email=your-email@company.com \
  --docker-server=https://avesha.azurecr.io/ \
  -n avesha

📚 For advanced secret management: Visit the Secret Management Guide

3. Install Options

💡 Optional: For easier environment variable management, see .env file setup.

📋 Note: If you need to create a custom kubeconfig file, you can download it from your Kubernetes cluster or cloud provider.

Minimal (Core AI Services)

# Set your OpenAI API key (get from https://platform.openai.com/api-keys)
export OPENAI_API_KEY="sk-your-openai-api-key"

# Install with LoadBalancer for external UI access
helm install obliq-sre-agent obliq-charts/obliq-sre-agent \
  --namespace avesha \
  --create-namespace \
  --set-file global.kubeconfig.content=./kubeconfig `# Path to your kubeconfig file` \
  --set global.env.openai.OPENAI_API_KEY="${OPENAI_API_KEY}" `# Required for AI services` \
  --set avesha-unified-ui.service.type=LoadBalancer `# Expose UI externally` \
  --timeout 15m

AWS Integration

📋 Prerequisites: Before running AWS integration, ensure you have:

# Core credentials
export OPENAI_API_KEY="sk-your-openai-api-key"  # Get from OpenAI platform
export AWS_ACCESS_KEY_ID="your-aws-access-key"  # AWS IAM user access key
export AWS_SECRET_ACCESS_KEY="your-aws-secret-key"  # AWS IAM user secret
export AWS_ROLE_ARN_AWS_MCP="arn:aws:iam::123456789012:role/your-aws-mcp-role"  # IAM role for AWS MCP
export AWS_ROLE_ARN_EC2_CLOUDWATCH_ALARMS="arn:aws:iam::123456789012:role/your-ec2-cloudwatch-role"  # IAM role for CloudWatch alarms
export AWS_REGION="us-west-2"  # AWS region for resources

# Install with AWS integration and LoadBalancer UI access
helm install obliq-sre-agent obliq-charts/obliq-sre-agent \
  --namespace avesha \
  --create-namespace \
  --set-file global.kubeconfig.content=./kubeconfig `# Path to your kubeconfig` \
  --set global.env.openai.OPENAI_API_KEY="${OPENAI_API_KEY}" `# Required for AI services` \
  --set aws-mcp.enabled=true `# Enable AWS MCP service` \
  --set cloudwatch-mcp.enabled=true `# Enable AWS CloudWatch integration` \
  --set aws-ec2-cloudwatch-alarms.enabled=true `# Enable AWS CloudWatch alarms monitoring` \
  --set global.env.aws.AWS_ACCESS_KEY_ID="${AWS_ACCESS_KEY_ID}" `# AWS API access` \
  --set global.env.aws.AWS_SECRET_ACCESS_KEY="${AWS_SECRET_ACCESS_KEY}" `# AWS API secret` \
  --set global.env.aws.AWS_ROLE_ARN_AWS_MCP="${AWS_ROLE_ARN_AWS_MCP}" `# AWS MCP role ARN` \
  --set global.env.aws.AWS_ROLE_ARN_EC2_CLOUDWATCH_ALARMS="${AWS_ROLE_ARN_EC2_CLOUDWATCH_ALARMS}" `# CloudWatch alarms role ARN` \
  --set global.env.aws.AWS_REGION="${AWS_REGION}" `# AWS region` \
  --set avesha-unified-ui.service.type=LoadBalancer `# Expose UI externally` \
  --timeout 15m

📋 For full integration with all services: See Complete Deployment Examples

⚠️ Important: Full integration requires additional setup:

4. Verify Installation

# Check pod status (all should be Running)
kubectl get pods -n avesha

# Check deployment status and notes
helm status obliq-sre-agent -n avesha

# Verify core services are ready
kubectl get deployments -n avesha

# Check for any issues
kubectl get events -n avesha --sort-by='.lastTimestamp' | tail -10

5. Access the UI

# Get the external IP (may take a few minutes to provision)
kubectl get service -n avesha avesha-unified-ui

# Access at: http://<EXTERNAL-IP>:80

🔐 Default Login Credentials:

Alternative access methods:

🗑️ Uninstall

# Uninstall the application
helm uninstall obliq-sre-agent -n avesha

# Remove the namespace (optional)
kubectl delete namespace avesha

📋 For complete configuration options: Visit the Parameters Reference

🆘 Troubleshooting

Common Issues

Basic Debugging

# Check pod status
kubectl get pods -n avesha

# View logs
kubectl logs -n avesha deployment/backend -f

# Check events
kubectl get events -n avesha --sort-by='.lastTimestamp' | tail -10

📞 Support

📊 For detailed service configuration: Visit the Services Guide