3 key aspects to have application optimization: Application scalability Application performance Application security Best Techniques to Optimize: Performance profiling and monitoring - Profiling is analyzing the app to identify bottlenecks in the code, such as slow functions or inefficient algorithms. Refactoring inefficient code - Techniques like loop unrolling, inline expansion, regular code review and pair programming can enhance. Use load balancer - Implementing this can also enhance fault tolerance by redirecting traffic away from failed servers. Asynchronous and Multithreading-Asynchronous processing is executing tasks in the background, freeing up the main thread to handle other task.Avoid issue like race condition and deadlock

Start by profiling the application to pinpoint bottlenecks, focusing on database queries, API response, and heavy processing tasks. Introduce streaming technologies like Apache Kafka or Azure Event Hubs to handle real-time data ingestion and processing efficiently. Optimize critical paths using in-memory databases like Redis for caching, asynchronous processing, and event-driven designs to reduce delays. Scale horizontally with load balancers or adopt microservices for better resource distribution. Implement efficient serialization and compression for faster data transfers. Continuously monitor metrics with APM tools and conduct stress testing to validate improvements, ensuring the system meets real-time demands even under peak loads.

Start by identifying bottlenecks with profiling tools to locate slow components and optimize database queries by indexing critical fields. Implement caching for frequently accessed data, using options like Redis or in-memory cache, and consider a CDN for static resources. Optimize code by removing redundancies and leveraging asynchronous processing for non-critical tasks. Improve network efficiency by minimizing API payloads, using HTTP/2, and enabling compression. Additionally, apply lazy loading techniques to load resources as needed, streamline frontend assets, and optimize images. Finally, scale resources by adding load balancers, considering horizontal scaling, and ensuring sufficient server capacity in terms of CPU and memory.

Before optimizing code or resources, it’s essential to first understand the root cause of the performance degradation. The development team should leverage various profiling tools, memory scans, and resource monitoring to accurately identify the underlying issue. Once the problem is clearly defined, it becomes much easier to implement targeted solutions that improve performance, rather than applying a broad, brute-force approach.