LangChain Production Checklist
Contents
Overview
Comprehensive checklist for deploying LangChain applications to production with reliability, security, and performance.
Prerequisites
- LangChain application developed and tested
- Infrastructure provisioned
- CI/CD pipeline configured
Instructions
1. Configuration & Secrets
- All API keys in secrets manager (not env vars in code)
- Environment-specific configurations separated
- Configuration validation on startup with
pydantic_settings.BaseSettings
2. Error Handling & Resilience
- Retry logic with exponential backoff
- Fallback models:
primary.with_fallbacks([fallback])
- Circuit breaker for cascading failures
3. Observability
- Structured logging, Prometheus metrics, LangSmith tracing
- Alerting rules for error rate and latency
4. Performance
- Redis caching for repeated queries
- Connection pooling, timeout limits, batch processing
5. Security
- Input validation (length limits, sanitization)
- Rate limiting per user/IP, audit logging
6. Testing
- Unit tests for all chains, integration tests with mock LLMs
- Load tests and chaos engineering
7. Deployment
- Health check endpoint, graceful shutdown, rolling deployment
- Rollback procedure documented
8. Cost Management
- Token counting, usage alerts, budget limits
See detailed implementation for code examples and deployment validation script.
Output
- Validated production configuration
- Health check endpoint
- Pre-deployment validation script
- Cost estimation utilities
Error Handling
| Issue |
Cause |
Solution |
| API key missing |
Bad secrets config |
Validate on startup |
| LLM timeout |
Network/provider issue |
Set timeout + fallback |
| Cache miss storm |
Redis down |
Graceful degradation |
Examples
Basic usage: Apply langchain prod checklist to a standard project setup with default configuration options.
Advanced scenario: Customize langchain prod checklist for production environments with multiple constraints and team-specific requirements.
Resources
Next Steps
After launch, use langchain-observability for monitoring.