Shihab Uddin(Shihab)’s Post

Boost Spring Boot Performance with Redis Supercharge your Spring Boot apps with Redis for ultra-fast caching and efficient session management. Integrate Redis for better speed and scalability! #SpringBoot #Redis #Caching #Performance #JavaDevelopment #TechTips

Today, I learned Redis and discovered its potential in optimizing backend APIs. 🚀 Redis is incredibly powerful for caching, and when it comes to backend optimization, it really shines. 💡 I implemented Redis caching in one of my Django projects today and saw firsthand how it enhances performance by reducing database queries and speeding up response times. Some cool features of django-redis: ** Easy integration with Django’s caching framework. ** Supports a variety of Redis commands out of the box. ** Automatic cache invalidation to ensure consistency. ** Fast in-memory storage to improve load times. Redis has proven to be a game-changer for optimizing API performance! #Redis #Django #BackendDevelopment #Optimization #APIPerformance

Elevate your Laravel applications with Redis! 🚀 Unlock the full potential of Laravel by integrating Redis for enhanced performance, scalability, and real-time capabilities. Experience lightning-fast data retrieval, efficient caching, and seamless session management, ensuring a superior user experience. Embrace Redis and take your Laravel applications to new heights! 🌟📈 #Laravel #Redis #WebDevelopment #TechInnovation #PerformanceBoost

Optimizing API Performance Optimizing API performance can significantly impact user experience. One effective strategy is implementing caching for frequently requested data. Using tools like Redis for caching can reduce load times and improve response speeds. Remember to set appropriate expiration times to balance freshness and efficiency. #APIPerformance #Caching #Redis #BackendDevelopment

Rediscovering the power of Redis! 🚀 As I dive deeper into backend optimization, Redis has emerged as an essential tool in my toolkit. Its unparalleled caching capabilities and blazing speed are game-changers for handling data-intensive applications. With Redis, data retrieval becomes a breeze, minimizing delays and enhancing the overall user experience. Redis makes scaling and efficiency feel effortless—perfect for anyone looking to optimize their backend solutions. Let’s unlock new levels of performance! 🌐🔓 #Redis #BackendDevelopment #Caching #PerformanceOptimization #RedisCaching #TechJourney #DataRetrieval #BackendEngineer #WebDevelopment

🚀 Latest Update Announcement 𝗔𝗰𝗰𝗲𝘀𝘀 𝗥𝗲𝗱𝗶𝘀 𝗖𝗿𝗲𝗱𝗲𝗻𝘁𝗶𝗮𝗹𝘀 𝗼𝗻 𝗙𝗹𝘆𝗪𝗣 With the new Redis credentials access and other key fixes, you can gain full control over your Redis caching system. 𝗞𝗲𝘆 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀: 🔑 Redis Credentials Access for better caching control ⚡ Easier updates with new "Update All" dropdown 🛠 Improved data fetching and API enhancements 🔗 Full changelog: https://buff.ly/3NAHgFE #FlyWP #Redis #WordPress #Credentials

𝙍𝙚𝙙𝙞𝙨, 𝙃𝙖𝙣𝙙𝙡𝙞𝙣𝙜 𝙃𝙞𝙜𝙝 𝙑𝙤𝙡𝙪𝙢𝙚 𝙏𝙧𝙖𝙛𝙛𝙞𝙘, Part 2 of Code to Solve Problem. Redis is a popular choice for solving various caching problems, especially when handling high user base. So, Today I put it to test to demonstrate how Redis significantly enhances your project efficiency. # TL;DR Before Redis 👉 Response time of 50ms and merely 50 concurrent connections After Redis: Response time slashed to 20ms and scaled to infinite number of connections; (while true) #redis #caching #scalability #WebDevelopment

Redis multithread IO Currently, in the architecture for distributing market messages to the pricing board, I am using Redis (pub/sub). The model I use is very simple: 1 master - n slaves. Operations per second: 1.5k ops/s CPU usage: 10-15% (not even using one core) However, it is noticeable that the main wait time is related to IO, specifically the requests from clients and replication to the slaves, as well as response time. When the number of clients and slaves increases, it leads to an IO burden for the master. Expanding for future scaling is always a challenging issue for the technical team. If the load suddenly increases by 10, 100, or 1000 times, we would be unprepared. Fortunately, since version 6.0, Redis has added a multi-threading mechanism for IO. However, by default, Redis disables this feature, and we need to enable it through configuration. Regarding benchmarks, I tested with operations such as set, hset, and lpush. Server: 4vCPU, 4GB RAM Single thread: ~90k ops/s Single thread process command - 2 IO threads: ~150k ops/s, about 1.6 times higher. For pure IO pub/sub tasks, the performance improvement is even more significant. #RedisOptimize #Redis #ReactorPattern #EventDriven #wecommit100xshare

#Redis 8 Milestone 2 is here, delivering unparalleled #performance and #scalability. The Query Engine now supports both vertical and horizontal scaling, making it ideal for a wide range of workloads. Additionally, we've optimized over 20 common commands, resulting in significant latency reductions (e.g., up to 36% for ZADD). For a detailed blog by Lior Kogan and Filipe Oliveira pls, read: https://lnkd.in/dFEYQUbZ Refer to the following p50 (median) latency reduction in Redis 8.0-M02 compared to Redis 7.2.5. We can see p50 latency improvements across data types ranging from 9% to 53% latency reduction. #redis #communityedition #product #announcement #release #opensource

🚨New Roadmap Alert 🚨 The Redis Roadmap is now live 👉 https://roadmap.sh/redis If you're looking for a structured path on your Redis learning journey, this will tick that box! From an in-depth introduction to Redis Enterprise and everything in between! Let us know what you think! 🎉 #Roadmap #Developer #Redis