O2 SRE Agent Setup

Overview

The O2 SRE Agent is a background service that powers AI-driven features in OpenObserve Enterprise. It handles AI request processing, tool execution, and intelligence for observability workflows.

Features Enabled by SRE Agent

AI Assistant

Natural language querying of logs, metrics, and traces
Automated SQL/PromQL/VRL query generation
Resource creation (dashboards, alerts) via chat
Multi-data source correlation and troubleshooting
Script generation (Python/VRL)
Query validation before execution
Context-aware on the Traces page (picks up the current stream, time range, search mode, and selected trace) and presents summarized tool results for readability

Custom Toolsets & Skills (Enterprise)

The SRE Agent can be extended with org-scoped custom toolsets that are loaded into the agent's available tools for chat and RCA requests. Supported toolset kinds are MCP, CLI, skill, and generic. Manage them under Management > AI Toolsets.

Incident Management & RCA

Automated incident detection and grouping
AI-powered Root Cause Analysis
Automated RCA reanalysis (append-only delta analysis triggered on incident lifecycle events)
Alert correlation and event tracking
Incident lifecycle management

Prerequisites

OpenObserve Enterprise License (v0.60.0+)
AI Provider API Key with available quota (Anthropic, OpenAI, or Google Gemini)
O2_AI_ENABLED set to "true" in your OpenObserve configuration

Configuration Methods

Method 1: Helm Chart Deployment (Recommended)

If you're deploying OpenObserve using the official Helm charts, the SRE Agent is already included. You just need to enable and configure it.

Official Helm Charts:

Step 1: Add Helm Repository

helm repo add openobserve https://charts.openobserve.ai
helm repo update

Step 2: Update Values File

Update your values.yaml with the following configuration:

Minimal Configuration (Direct API - No Gateway):

enterprise:
  enabled: true

  # Required when O2_AI_ENABLED is "true"
  sreagent:
    enabled: true
    config:
      O2_SRE_HOST: "0.0.0.0"
      O2_SRE_PORT: "8000"
      O2_SRE_LOG_LEVEL: "INFO"
      ADK_ENABLE_JSON_SCHEMA_FOR_FUNC_DECL: "true"
      O2_AI_GATEWAY_ENABLED: "false"
      O2_AI_PROVIDER: "anthropic"  # Options: anthropic, openai, gemini
      O2_AI_MODEL: "claude-3-5-sonnet-20241022"
      O2_AI_GATEWAY_URL: ""  # Leave empty when not using gateway
      O2_AGENT_URL: ""  # Leave empty - auto-generated
      O2_TOOL_API_URL: ""  # Leave empty - auto-generated
      # MCP validation settings
      O2_MCP_VALIDATION_ENABLED: "true"
      O2_MCP_VALIDATION_RETRY: "true"
      O2_MCP_CONTENT_VALIDATION_ENABLED: "true"
      O2_MCP_CONTENT_VALIDATION_MODE: "hybrid"
      O2_MCP_RESPONSE_VALIDATION_ENABLED: "true"

  # IMPORTANT: Requires sreagent.enabled to be true
  parameters:
    O2_AI_ENABLED: "true"
    O2_AGENT_URL: ""  # Leave empty - auto-generated
    O2_TOOL_API_URL: ""  # Leave empty - auto-generated

# AI API Key (REQUIRED)
auth:
  O2_AI_API_KEY: "your-api-key-here"

Configuration with AI Gateway:

# Enable AI Gateway
aiGateway:
  enabled: true
  gatewayServiceName: "ai-gateway"
  port: 80

enterprise:
  enabled: true

  sreagent:
    enabled: true
    config:
      O2_SRE_HOST: "0.0.0.0"
      O2_SRE_PORT: "8000"
      O2_SRE_LOG_LEVEL: "INFO"
      ADK_ENABLE_JSON_SCHEMA_FOR_FUNC_DECL: "true"
      O2_AI_GATEWAY_ENABLED: "true"  # Auto-set when aiGateway.enabled: true
      O2_AI_PROVIDER: "anthropic"  # Can be omitted when using gateway
      O2_AI_MODEL: "claude-3-5-sonnet-20241022"
      O2_AI_GATEWAY_URL: ""  # Auto-configured when aiGateway.enabled: true
      O2_AGENT_URL: ""
      O2_TOOL_API_URL: ""
      O2_MCP_VALIDATION_ENABLED: "true"
      O2_MCP_VALIDATION_RETRY: "true"
      O2_MCP_CONTENT_VALIDATION_ENABLED: "true"
      O2_MCP_CONTENT_VALIDATION_MODE: "hybrid"
      O2_MCP_RESPONSE_VALIDATION_ENABLED: "true"

  parameters:
    O2_AI_ENABLED: "true"
    O2_AGENT_URL: ""
    O2_TOOL_API_URL: ""

auth:
  O2_AI_API_KEY: "your-api-key-here"

With Incidents & RCA:

enterprise:
  enabled: true

  sreagent:
    enabled: true
    config:
      O2_SRE_HOST: "0.0.0.0"
      O2_SRE_PORT: "8000"
      O2_SRE_LOG_LEVEL: "INFO"
      ADK_ENABLE_JSON_SCHEMA_FOR_FUNC_DECL: "true"
      O2_AI_GATEWAY_ENABLED: "false"
      O2_AI_PROVIDER: "anthropic"
      O2_AI_MODEL: "claude-3-5-sonnet-20241022"
      O2_AI_GATEWAY_URL: ""
      O2_AGENT_URL: ""
      O2_TOOL_API_URL: ""
      O2_MCP_VALIDATION_ENABLED: "true"
      O2_MCP_VALIDATION_RETRY: "true"
      O2_MCP_CONTENT_VALIDATION_ENABLED: "true"
      O2_MCP_CONTENT_VALIDATION_MODE: "hybrid"
      O2_MCP_RESPONSE_VALIDATION_ENABLED: "true"

  parameters:
    # AI Features
    O2_AI_ENABLED: "true"
    O2_AGENT_URL: ""
    O2_TOOL_API_URL: ""

    # Incidents and RCA
    O2_INCIDENTS_ENABLED: "true"
    O2_INCIDENTS_RCA_ENABLED: "true"
    O2_INCIDENTS_AUTO_RESOLVE_AFTER_MINUTES: "-1"
    O2_INCIDENTS_ALERT_GRAPH_ENABLED: "true"
    O2_INCIDENTS_REANALYSIS_COOLDOWN_MINUTES: "30"  # Minimum minutes between automatic reanalysis runs (user-triggered reanalysis bypasses it)

auth:
  O2_AI_API_KEY: "your-api-key-here"
  # Optional: MCP Authentication
  O2_MCP_USERNAME: "root@example.com"
  O2_MCP_PASSWORD: "SecurePassword123"

Step 3: Deploy

Multi-node deployment:

helm upgrade --install openobserve openobserve/openobserve \
  -f values.yaml \
  --namespace openobserve \
  --create-namespace

Standalone deployment:

helm upgrade --install openobserve openobserve/openobserve-standalone \
  -f values.yaml \
  --namespace openobserve \
  --create-namespace

Step 4: Verify Deployment

# Check SRE Agent pod
kubectl get pods -n openobserve | grep sreagent

# View logs
kubectl logs -n openobserve deployment/openobserve-sreagent --tail=50

# Check health
kubectl exec -n openobserve deployment/openobserve-router -- \
  curl -s http://openobserve-sreagent:8000/health

Method 2: Manual Deployment

For deployments not using the official Helm charts. Requires deploying two components separately.

Docker Image: public.ecr.aws/zinclabs/o2-sre-agent:latest

Step 1: Create Kubernetes Secret

apiVersion: v1
kind: Secret
metadata:
  name: o2-sre-agent-secrets
  namespace: openobserve
type: Opaque
stringData:
  ai-api-key: "your-api-key-here"
  # Optional
  mcp-username: "root@example.com"
  mcp-password: "SecurePassword123"

kubectl apply -f secret.yaml

Step 2: Deploy SRE Agent

apiVersion: apps/v1
kind: Deployment
metadata:
  name: o2-sre-agent
  namespace: openobserve
spec:
  replicas: 2
  selector:
    matchLabels:
      app: o2-sre-agent
  template:
    metadata:
      labels:
        app: o2-sre-agent
    spec:
      containers:
      - name: o2-sre-agent
        image: public.ecr.aws/zinclabs/o2-sre-agent:latest
        ports:
        - containerPort: 8000
          name: http

        env:
        # Server Configuration
        - name: O2_SRE_HOST
          value: "0.0.0.0"
        - name: O2_SRE_PORT
          value: "8000"
        - name: O2_SRE_LOG_LEVEL
          value: "INFO"

        # AI Provider Configuration
        - name: O2_AI_PROVIDER
          value: "anthropic"
        - name: O2_AI_MODEL
          value: "claude-sonnet-4-5-20250929"
        - name: O2_AI_API_KEY
          valueFrom:
            secretKeyRef:
              name: o2-sre-agent-secrets
              key: ai-api-key

        # MCP Tool Server URL (points to OpenObserve)
        - name: O2_TOOL_API_URL
          value: "http://openobserve-router.openobserve.svc.cluster.local:5080/api/default/mcp"

        # MCP Validation
        - name: O2_MCP_VALIDATION_ENABLED
          value: "true"
        - name: O2_MCP_CONTENT_VALIDATION_ENABLED
          value: "true"

        # Optional: MCP Authentication
        - name: O2_MCP_USERNAME
          valueFrom:
            secretKeyRef:
              name: o2-sre-agent-secrets
              key: mcp-username
              optional: true
        - name: O2_MCP_PASSWORD
          valueFrom:
            secretKeyRef:
              name: o2-sre-agent-secrets
              key: mcp-password
              optional: true

        resources:
          requests:
            memory: "256Mi"
            cpu: "250m"
          limits:
            memory: "512Mi"
            cpu: "500m"

---
apiVersion: v1
kind: Service
metadata:
  name: o2-sre-agent
  namespace: openobserve
spec:
  type: ClusterIP
  ports:
  - port: 8000
    targetPort: http
    name: http
  selector:
    app: o2-sre-agent

kubectl apply -f deployment.yaml

Step 3: Configure OpenObserve

Update your OpenObserve deployment configuration:

# OpenObserve configuration
enterprise:
  enabled: true
  parameters:
    # AI Features
    O2_AI_ENABLED: "true"
    O2_AGENT_URL: "http://o2-sre-agent.openobserve.svc.cluster.local:8000"
    O2_TOOL_API_URL: "http://openobserve-router.openobserve.svc.cluster.local:5080/api/default/mcp"

    # Optional: Incident Management
    O2_INCIDENTS_ENABLED: "true"
    O2_INCIDENTS_RCA_ENABLED: "true"
    O2_INCIDENTS_ALERT_GRAPH_ENABLED: "true"

Restart OpenObserve services to apply changes.

Environment Variables Reference

For detailed information about all available environment variables and their configurations, refer to the official documentation:

AI Provider Selection

Provider	Model	Use Case
Anthropic	`claude-3-5-sonnet-20241022`	Best reasoning, complex analysis (Recommended)
OpenAI	`gpt-4-turbo`, `gpt-4o`	Wide compatibility, strong performance
Google Gemini	`gemini-1.5-pro`	Cost-effective option

Configuration:

O2_AI_PROVIDER: "anthropic"  # or "openai", "gemini"
O2_AI_MODEL: "claude-3-5-sonnet-20241022"
O2_AI_API_KEY: "your-api-key"

AI Gateway Configuration

An AI Gateway provides rate limiting, response caching, load balancing, and usage tracking. Use it for production deployments, high query volumes (>100/day), or cost-sensitive environments. Development/testing can skip the gateway for simplicity.

Configuration Flows

Flow 1: OpenObserve Built-in Gateway (Recommended)

Uses the O2 Envoy Gateway for AI request management.

aiGateway:
  enabled: true
  gatewayServiceName: "ai-gateway"
  port: 80

enterprise:
  sreagent:
    enabled: true
    # O2_AI_PROVIDER not needed
    # Gateway settings auto-configured

Flow 2: External/Self-hosted Gateway

enterprise:
  sreagent:
    enabled: true
    config:
      O2_AI_GATEWAY_ENABLED: "true"
      O2_AI_GATEWAY_URL: "http://my-gateway.custom.svc.cluster.local:80"
      # O2_AI_PROVIDER not needed

Flow 3: Direct API (No Gateway)

enterprise:
  sreagent:
    enabled: true
    config:
      O2_AI_PROVIDER: "anthropic"
      O2_AI_MODEL: "claude-sonnet-4-5-20250929"
      # No gateway configuration

MCP Validation & Security

Model Context Protocol (MCP) handles communication between the SRE Agent and OpenObserve. Validation ensures secure and reliable AI tool execution.

Recommended for Production:

Enable all validation settings (O2_MCP_VALIDATION_ENABLED: "true")
Use hybrid validation mode for balanced security and flexibility
Configure MCP authentication for multi-tenant environments

Development: Can disable validation (O2_MCP_VALIDATION_ENABLED: "false") for faster iteration.

MCP Authentication (optional):

O2_MCP_USERNAME: "root@example.com"
O2_MCP_PASSWORD: "SecurePassword123"

Using the AI Assistant

Access

Log into OpenObserve
Click the AI Assistant icon in the sidebar
Navigate to Incidents page in OpenObserve side-menu

Example Queries

Log Analysis:

Show me all error logs from the payment service in the last hour
Find authentication failures grouped by IP address

Metrics:

What's causing high CPU usage on the API pods?
Show me latency trends for the checkout endpoint

Resource Creation:

Create a dashboard for monitoring the payment service
Set up an alert for when error rate exceeds 5%

Troubleshooting:

Analyze the root cause of the recent outage
Why is the database connection pool exhausted?

Troubleshooting

Common issues and fixes

SRE Agent Pod Not Starting

Check pod status:

kubectl get pods -n openobserve | grep sreagent
kubectl logs -n openobserve deployment/openobserve-sreagent --tail=100

Common causes:

Invalid API key
Incorrect AI provider name
Network connectivity issues

Verify configuration:

# Check API key exists
kubectl get secret -n openobserve openobserve-auth -o jsonpath='{.data.O2_AI_API_KEY}' | base64 -d

# Check environment variables
kubectl exec -n openobserve deployment/openobserve-sreagent -- env | grep O2_

AI Assistant Not Responding

Check connectivity:

# Health check
kubectl exec -n openobserve deployment/openobserve-router -- \
  curl -s http://openobserve-sreagent:8000/health

# Check logs
kubectl logs -n openobserve deployment/openobserve-sreagent --tail=50

Common causes:

O2_AI_ENABLED not set to "true"
Network policy blocking communication
AI provider API rate limiting
Service misconfiguration

MCP Tool Execution Failures

Verify MCP endpoint:

# Check O2_TOOL_API_URL
kubectl exec -n openobserve deployment/openobserve-sreagent -- env | grep O2_TOOL_API_URL

# Test connectivity
kubectl exec -n openobserve deployment/openobserve-sreagent -- \
  curl -s http://openobserve-router:5080/api/default/mcp

Common causes:

Incorrect O2_TOOL_API_URL format
Wrong organization name in URL
Missing MCP credentials
Service not reachable

Correct URL format:

http://<service-name>.<namespace>.svc.cluster.local:<port>/api/<org-name>/mcp

AI Gateway Issues

Check gateway:
```
# Verify gateway service
kubectl get svc -n <gateway-namespace> | grep ai-gateway

# Test connectivity
kubectl exec -n openobserve deployment/openobserve-sreagent -- \
  curl -s http://ai-gateway:80
```
Common causes:
- Gateway not deployed
- Conflicting configuration (both O2_AI_PROVIDER and O2_AI_GATEWAY_ENABLED set)
- Wrong gateway URL or port
Fix:
- With gateway: Remove O2_AI_PROVIDER, set O2_AI_GATEWAY_ENABLED="true"
- Without gateway: Remove all O2_AI_GATEWAY_* variables, set O2_AI_PROVIDER

Incident Management Not Working

Check configuration:

kubectl get configmap -n openobserve openobserve-config -o yaml | grep O2_INCIDENTS

Required settings (in OpenObserve, not SRE Agent):

O2_AI_ENABLED: "true"
O2_INCIDENTS_ENABLED: "true"
O2_INCIDENTS_RCA_ENABLED: "true"

Best Practices

API Key Security: Store in Kubernetes Secrets; use secret managers (Vault, AWS Secrets Manager) for production; rotate every 90 days
MCP Validation: Enable in production (O2_MCP_VALIDATION_ENABLED: "true"); use MCP authentication for multi-tenant setups
Network Security: Apply network policies to restrict traffic; enable TLS for service communication
High Availability: Deploy with 2+ replicas; enable HPA for auto-scaling in production
Logging: Use INFO level for production, DEBUG only when troubleshooting
Cost Optimization: Use AI Gateway with caching to reduce API calls; choose cost-effective models for simple queries
Updates: Keep SRE Agent image updated; test in non-production environments first

Support diagnostics

# Check pod and logs
kubectl get pods -n openobserve | grep sreagent
kubectl logs -n openobserve deployment/openobserve-sreagent --tail=100

# Verify configuration (redact sensitive data)
kubectl get configmap -n openobserve openobserve-config -o yaml | grep O2_

Next steps

Model Context Protocol (MCP): connect IDEs and agents to OpenObserve through the SRE Agent.
AI Integration env vars: full reference for AI-related settings.
Incidents and RCA env vars: tune incident detection and root cause analysis.

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