NestJS provides first-class support for caching through its modular architecture. In this tutorial, you'll build a production-ready distributed caching system using NestJS and Redis, leveraging decorators, interceptors, and dependency injection to create a clean, maintainable caching layer. By the end, you'll have a system that handles 25K+ requests per second with automatic cache invalidation and stampede protection.
Prerequisites
- Node.js 20+
- Redis 7+ running locally
- Basic familiarity with NestJS modules, providers, and decorators
Project Setup
Project Structure
Step 1: Cache Module Configuration
Create a dedicated cache module that wraps NestJS's built-in caching with Redis:
Step 2: Cache Service
Build the core service with type-safe operations:
Step 3: Distributed Lock Service
Prevent cache stampedes with Redis-based locking:
Combine the lock with caching:
Step 4: Custom Cache Interceptor
Create a reusable interceptor for automatic HTTP response caching:
Need a second opinion on your system design architecture?
I run free 30-minute strategy calls for engineering teams tackling this exact problem.
Book a Free CallStep 5: Custom Decorators
Create clean decorator APIs for cache configuration:
Step 6: Product Module Implementation
Build a complete CRUD module with integrated caching:
Step 7: Wire Everything Together
Step 8: Testing
Run tests:
Step 9: Production Deployment
Environment Configuration
Docker Setup
Conclusion
You've built a complete distributed caching system with NestJS that integrates naturally with the framework's module system. The key patterns—injectable cache service, custom decorators, HTTP interceptor, and distributed locking—follow NestJS conventions and are easy for other developers on your team to use.
The architecture separates concerns cleanly: the CacheService handles low-level Redis operations, the HttpCacheInterceptor provides automatic response caching, and the @Cached decorator configures caching declaratively. When data changes, the service layer handles invalidation explicitly, ensuring stale data doesn't persist.