Observability Agent

A distributed observability system that uses AI agents to analyze and respond to system events.

Architecture

The system consists of several specialized agents:

• Log Agent: Analyzes log data to identify patterns and anomalies
• Metric Agent: Processes metrics to detect performance issues
• Tracing Agent: Analyzes distributed traces to identify bottlenecks
• Root Cause Agent: Determines the root cause of issues
• Postmortem Agent: Generates postmortem reports
• Notification Agent: Handles alerting and notifications
• Deployment Agent: Manages deployments and rollbacks

Setup

1. Install dependencies:

pip install -r requirements.txt

2. Set up environment variables:

cp .env.example .env
# Edit .env with your configuration

3. Run the agents:

python main.py

Development

Testing

pytest tests/

Adding New Tools

1. Create a new tool class in common/tools/
2. Implement the tool using crewai's BaseTool
3. Add the tool to the appropriate agent
4. Update tests

Adding New Agents

1. Create a new agent class in agents/
2. Implement the agent using crewai's Agent
3. Add the agent to main.py
4. Create tests

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests
5. Submit a pull request

License

MIT