System Design - Caching, Message Brokers, Latency, Load Balancer | Part 2 | Developer Coder

Welcome to Part 2 of our System Design Essentials series on the Developer Coder channel! 🚀 In this episode, we dive deep into some of the most critical concepts used in large-scale distributed systems: 🔹 Caching – Reduce latency and improve performance using tools like Redis and Memcached. 🔹 Queues & Message Brokers – Decouple services and handle asynchronous communication with RabbitMQ, Kafka, and more. 🔹 Rate Limiting & Throttling – Protect your systems from abuse, spamming, or overload with smart control mechanisms. 🔹 Latency – Understand types of latency and how to reduce it for better user experience. 🔹 Load Balancers – Efficiently distribute traffic across servers to handle scale and improve fault tolerance. 💡 These are foundational topics for interviews at top tech companies and essential for backend engineers, architects, and SDEs. 📚 Whether you're preparing for system design interviews or aiming to build scalable software systems, this video is a must-watch! 🛠️ Stay tuned and subscribe to Developer Coder for more hands-on explanations, whiteboard-style visual breakdowns, and real-world system architecture walkthroughs. Part 1: https://youtu.be/pwDqgKjlwLY #SystemDesign #Caching #Redis #Kafka #RabbitMQ #RateLimiting #Throttling #Latency #LoadBalancer #Scalability #Microservices #DistributedSystems #BackendEngineering #HighAvailability #TechInterview #DeveloperCoder #ScalableArchitecture #APIGateway #QueueSystem #MessageBrokers #Google #Microsoft #Apple #Amazon #Facebook #IBM #Oracle #Cisco #Intel #Dell #HP #Adobe #Salesforce #SAP #NVIDIA #Tencent #Alibaba #Sony #Netflix #Baidu #Xiaomi #Qualcomm #VMware #Twitter #Fujitsu #Lenovo #Infosys #Capgemini #Accenture system design caching what is caching in system design caching in distributed systems message brokers in microservices difference between kafka and rabbitmq queues in backend how load balancer works load balancing system design rate limiting vs throttling api rate limiting latency in distributed systems reduce latency in backend developer coder system design system design video caching queue and message broker system design kafka explained simply rabbitmq for beginners load balancer tutorial difference between reverse proxy and load balancer latency vs throughput cache hit and cache miss explained how to scale backend systems message queue vs event bus synchronous vs asynchronous communication kafka vs redis pub sub redis caching tutorial in-memory caching system design lru cache algorithm how to use kafka in microservices event-driven architecture system design rate limiting with token bucket throttling logic backend best practices for caching high availability system design backend scaling strategies latency measurement tools redis vs memcached distributed queue system real time system design api gateway and load balancer system design for interviews cloud architecture system design microservices communication async processing in backend designing scalable systems api throttling implementation rate limit headers in api event queue microservices retry logic in queues latency optimization techniques failover and load balancing message broker overview idempotent queues design distributed cache architecture system performance engineering developer coder backend system design load balancer vs round robin kafka partitions and topics system design roadmap understanding caching layers designing fault tolerant systems designing for high concurrency latency vs response time enterprise system architecture circuit breaker vs rate limiter backend engineering tutorial throttling strategy microservices rate limiting architecture developer coder message queue scaling read heavy systems load balancer types explained microservice communication queue handling spike in traffic rate limit burst control reducing latency with caching message broker pub/sub distributed logging with kafka message brokers interview question event driven microservices caching layers in system distributed architecture youtube load balancing algorithm system design developer coder kafka what is rabbitmq used for rabbitmq dead letter queue microservices message queue example caching best practices how throttling works in backend api gateway with throttling developer coder queue tutorial queue vs stream in backend message broker visualization rabbitmq fanout vs direct kafka vs rabbitmq vs activemq system design caching queue latency developer coder load balancer kafka message delivery guarantees what is producer and consumer in kafka event processing pipeline microservices architecture queue why use load balancer load balancer caching example redis performance optimization