How can I optimize a Spring Boot application for horizontal scaling with Redis caching?
I keep running into I'm wondering if anyone has experience with I'm currently developing a Spring Boot application that serves as a backend for a real-time chat service... As user traffic is increasing, I've noticed important slowdowns and timeouts, especially during peak hours. We use Redis for caching frequently accessed data like user sessions and chat history, but the application still struggles with scaling. I've set up Redis as a standalone instance and configured it in my application like this: ```java @Configuration @EnableCaching public class CacheConfig { @Bean public RedisConnectionFactory redisConnectionFactory() { return new JedisConnectionFactory(); // Using Jedis as the Redis client } @Bean public RedisTemplate<String, Object> redisTemplate() { RedisTemplate<String, Object> template = new RedisTemplate<>(); template.setConnectionFactory(redisConnectionFactory()); return template; } } ``` I also implemented caching in my service layer: ```java @Service public class ChatService { @Cacheable(value = "chatHistory", key = "#userId") public List<ChatMessage> getChatHistory(String userId) { // Simulate a time-consuming query to the database return chatRepository.findByUserId(userId); } } ``` Despite this setup, I observe frequent `org.springframework.data.redis.RedisConnectionException: Unable to connect to Redis` errors, especially when the number of concurrent users exceeds 100. I suspect that my Redis setup is not optimized for horizontal scaling. What configurations or architectural changes can I implement to better support scalability? Are there particular design patterns or best practices I should consider with Redis and Spring Boot to alleviate these performance optimization? Any advice on clustering Redis or optimizing the caching strategy would be greatly appreciated! I'd be grateful for any help. This is happening in both development and production on Debian. I'm open to any suggestions.