Deploying Agents to Production
From prototype to production—what changes when your agent goes live? Here's the deployment checklist.
Production vs Prototype
| Aspect | Prototype | Production |
|---|---|---|
| Uptime | When you're watching | 24/7 |
| Errors | Debug manually | Auto-recovery |
| Scale | 1 user | 1000s of users |
| Cost | Don't care | Optimize ruthlessly |
Infrastructure Requirements
- Compute — Server or serverless functions
- Database — User data, conversation history
- Queue — Handle async tasks
- Monitoring — Logs, metrics, alerts
Deployment Checklist
Before Launch
- ✅ Rate limiting implemented
- ✅ Error handling comprehensive
- ✅ Logging in place
- ✅ Fallback behaviors defined
- ✅ Cost monitoring set up
Day of Launch
- ✅ Gradual rollout (10% → 50% → 100%)
- ✅ Monitor error rates closely
- ✅ Have rollback plan ready
- ✅ Team on standby for issues
Monitoring Essentials
- Response time — Alert if >10s average
- Error rate — Alert if >5%
- Token usage — Track daily costs
- User satisfaction — Feedback collection
Scaling Strategies
- Horizontal — Multiple agent instances
- Async — Queue non-urgent tasks
- Cache — Store common responses
- Tier — Different models for different users