I apply strategies from "The DevOps Handbook" by Gene Kim, focusing on automation and Monitoring: 1. Efficient Caching: I implement strategic caching mechanisms to minimize direct API calls, which helps maintain app responsiveness and reduces load times. 2. Asynchronous Processing: I use asynchronous calls to ensure that API requests do not block user interactions, maintaining a smooth user experience. 3. Continuous Monitoring: I rigorously monitor API performance and set up alerts for anomalies affecting our app, enabling quick mitigation. These methods ensure that third-party API integrations do not compromise our web app's performance, keeping it fast and reliable.

Today almost all web applications interact with other 3rd party APIs and support others to communicate with them leading to performance bottlenecks. Following strategies have helped ensuring better response times and performance of the web application: - Adhering to Rate Limits imposed by using threads and semaphores - Ensuring the cache strategies are in place for apis that are not realtime or quick to change - Identifying most important apis for response generation and putting others on back burner (child processes) - Adding worker threads for background tasks is a plus - Using services such as pm2 have proven helpful in leveraging additional cores available in server as well

When integrating third-party APIs, We generally focus on balancing performance with functionality. Caching frequently accessed data reduces the number of direct API calls, speeding up the app. We can use asynchronous calls to keep the app responsive, preventing delays in user interactions. Rate limiting and efficient resource management help avoid overloading the system. Continuous monitoring ensures that any API slowdowns are quickly addressed. These steps keep the app fast and reliable, even with multiple API integrations.

Efficient Data Handling: Use pagination, selective data fetching, and caching mechanisms (e.g., Redis) to limit data load and reduce API calls. Concurrency & Async Processing: Leverage async/await in JavaScript and web workers to process API responses without blocking the main thread. Rate Limiting & Throttling: Implement rate limiting to avoid overloading the API and ensure smoother performance. Load Distribution: Use load balancers and message queues like Kafka to distribute traffic evenly. Monitor & Optimize: Use monitoring tools (Prometheus, Grafana) to track performance and identify bottlenecks.