Quick Learn | FAQ's | Technical Solutions

Key steps to improving Rest API performance: Optimize Database Queries Use indexing effectively Implement query caching Optimize SQL statements Use database connection pooling Implement Caching Strategies Use in-memory caching (e.g. Redis, Memcached) Implement HTTP caching headers Use content delivery networks (CDN) for static contents Compress API Responses Use GZip compression Implement Brotli compression for modern browsers Use Efficient Data Formats Use JSON for most of use-cases Consider protocol buffers or message pack for binary data Implement Pagination Limit the amount of data returned in a single request Use cursor based pagination for large datasets using limit, offset etc. Asynchronous Processing Use message queue for time consuming tasks Implement WebHooks for long-running operations Rate Limiting Implement rate limiting to prevent abuse Use token bucket or leaky bucket algorithms Optimize Network Settings Use HTTP/2 or HTTP/3 Enable Keep-Alive connections Optimize TCP set...

Apache Kafka - Zookeeper Tutorial Topics covered in this article as below: Need of Messaging System What is Kafka? Kafka Features Kafka Components Kafka Architecture Installing Kafka Working with Single Node Broker Cluster 1. Need of Messaging System Data pipelines - Communication is required between different systems in the real-time scenario, which is done by using data pipelines Chat Server -----------Data Pipeline---------------> Database server Many services are communicating with various internal systems like front-end, back-end Api, database server, security system, real-time monitoring, chat server etc. Messaging systems helps managing complexity of above pipelines. so Kafka helps here to decouples data pipelines Key entity involved in Kafka Producer (Publisher) Consumer (Subscriber) 2. What is Kafka? (High throughput distributed messaging system) Apache Kafka is a distributed publish-subscribe messaging system It was originally developed at Linked-In and later became part ...

Caching is a powerful optimization methods that improves the efficiency, scalability and performance of Rest APIs. It helps reduce the load on database, minimizes redundant computations and speed up response times by storing frequently request data closer to the client or server. 1. Application Layer Caching - Using Redis for Fast data retrieval Store frequently used data at in memory database (Redis) for faster retrieval of data or Quick access Maintain the unique key value identified pair for uniqueness data e.g. : Sample Java program import redis.clients.jedis.Jedis; public class UserService { private Jedis redisClient = new Jedis("localhost"); public String getUserProfile(String userId) { //Check if the user profile exist in the cache String cachedProfile = redisClient.get(userId);      if(cachedProfile != null) {          System.out.println("Cache found!");           return cachedProfile;   ...