How Do I Architect a Scalable Activity Feed System That Won’t Crash Under Load?

Activity feeds are crucial features in many social platforms, such as X's home timeline, Facebook's news feed, and LinkedIn's updates, and they must balance high write and read volumes. To achieve this, feed systems generally separate event capture from feed serving, using three layers: immutable activity events, a serving view, and hydration. An important architectural decision is whether to use a "push" (Fan-Out-On-Write) or "pull" (Fan-Out-On-Read) strategy, or a hybrid of both, to manage the balance between write amplification and read latency. Performance issues, such as slower feeds with deeper scrolling, often stem from inefficient pagination strategies, which can be improved with cursor-based pagination. Aggregating activities, such as grouping notifications, presents challenges in data modeling and concurrency, which can be addressed by either read-time or pipeline aggregation strategies. While "real-time" feed updates can be achieved using technologies like Server-Sent Events or WebSockets, most feeds benefit from a balance between immediacy and user control. Graph databases are generally unsuitable for storing feed timelines, which are better managed with key-value or wide-column stores, but they are effective for managing social graph data, such as follower relationships.