1. Database Indexing:
- I analyzed our MongoDB query patterns and added appropriate indexes to speed up frequent read and write operations. This reduced query response times significantly, particularly for the most commonly accessed endpoints.
2. Horizontal Scaling:
- I set up a load balancer to distribute incoming requests across multiple instances of our Node.js application. This ensured that our API could handle increased traffic without becoming a bottleneck.
3. Caching Layer:
- I introduced a Redis-based caching layer to store frequently accessed data, such as configuration settings and user session data. This reduced the load on our primary database and improved response times for cached requests.