AG2 (AutoGen) Production Guide

AG2 (AutoGen) Production Guide

Version: 0.11.5 Last Updated: April 2026 Focus: Enterprise Deployment & Best Practices

Overview

This guide covers best practices for deploying AG2 agents in production environments, focusing on reliability, scalability, and security.

Deployment Strategies

Dockerization

Containerize your AG2 agents for consistent deployment.

FROM python:3.10-slim

WORKDIR /app

COPY requirements.txt .
RUN pip install -r requirements.txt

COPY . .

CMD ["python", "main.py"]

Serverless Deployment

Deploy agents as serverless functions (e.g., AWS Lambda, Azure Functions) for event-driven workloads.

Error Handling & Resilience

• Retries: Implement retry logic for LLM API calls.
• Fallbacks: Define fallback behaviors if an agent fails to generate a valid response.
• Logging: Use structured logging to track agent interactions and errors.

Security

• Sandboxing: Run code execution agents in a sandboxed environment (e.g., Docker container) to prevent malicious actions.
• Input Validation: Validate all user inputs to prevent injection attacks.
• API Key Management: Use environment variables or secrets management services to store API keys.

Monitoring & Observability

• Tracing: Trace agent conversations to understand the flow of execution.
• Metrics: Monitor token usage, latency, and error rates.
• Cost Management: Track API costs and implement budget limits.

Scaling

• Horizontal Scaling: Run multiple instances of your agent service behind a load balancer.
• State Management: Use a distributed store (e.g., Redis) to manage conversation state across instances.