Каким образом вы подходите к решению задач, связанных с ростом количества запросов в секунду (RPS)?

To address issues related to the increase in requests per second (RPS), a comprehensive approach is usually applied:

1. Analysis and Monitoring — first, understand where the requests are increasing from, which services or endpoints are overloaded.

2. Code and Database Optimization — reduce request processing time, optimize database queries, use caching.

3. Caching — implement caching at various levels (e.g., CDN, Redis, in-memory) to reduce backend load.

4. Scaling:

   • Horizontal — add more servers or containers.
   • Vertical — increase resources of existing servers.

5. Load Balancing — use load balancers to distribute requests evenly.

6. Limiting and Protection — implement rate limiting, throttling to prevent overload.

7. Asynchronous Processing — use message queues to offload synchronous requests.

8. Automation and On-Demand Scaling — use cloud solutions with auto-scaling.

Example: if your RPS on an API suddenly increases, you can add a Redis cache for frequently requested data, configure a load balancer (e.g., Nginx or AWS ELB), and increase the number of service instances.