How Instagram Works at Scale🔥 | System Design of Instagram | #systemdesign #aws #instagram #coding

How would you design Instagram to handle billions of users, millions of uploads, and millions of requests per second? In this video, we design Instagram from scratch and explore the distributed-system concepts required to build a social-media platform at massive scale. We'll start with the basic requirements and gradually build the architecture while solving some of the most interesting system-design problems. 🚀 What you'll learn Instagram functional & non-functional requirements Scale and capacity estimation Millions of requests per second High-level Instagram architecture Load balancers Application servers PostgreSQL database design Database sharding Redis caching Object storage for photos and videos CDN for media delivery Unique 64-bit ID generation Time-sortable IDs Instagram feed generation Pull-based feed generation Push-based feed generation The celebrity problem Hybrid feed generation Likes, views and counters Media storage and bandwidth optimization High availability and fault tolerance 🏗️ Architecture discussed Client → Load Balancer → Application Servers → PostgreSQL + Redis + Object Storage + CDN We'll also see how a hybrid push/pull architecture can be used to generate Instagram's home feed efficiently. 📊 Important system-design concepts One of the most interesting parts of this design is the feed-generation problem. If a normal user publishes a post, pushing that post to all followers can work well. But imagine a celebrity with hundreds of millions of followers. Pushing one post to every follower would create an enormous number of write operations. So we explore how a hybrid feed architecture can combine push-based and pull-based approaches to handle this problem. 👍 Like the video if you found it useful. 💬 Comment which system you want me to design next. 🔔 Subscribe for more system design and distributed systems content. #SystemDesign #Instagram #SoftwareArchitecture #DistributedSystems #SystemDesignInterview #BackendDevelopment #Redis #PostgreSQL #DatabaseSharding #DevOps #CloudComputing