Suggest an editImprove this articleRefine the answer for “How does EDA improve scalability?”. Your changes go to moderation before they’re published.Approval requiredContentWhat you’re changing🇺🇸EN🇺🇦UAPreviewTitle (EN)Short answer (EN)Event-driven architecture (**EDA**) improves scalability through asynchrony, loose coupling, and distributed event processing: services do not wait for each other and process events in parallel. **Key point:** the more load there is, the more subscribers can be added without changing the architecture.Shown above the full answer for quick recall.Answer (EN)ImageEvent-driven architecture (**EDA**) improves scalability through **asynchrony**, **loose coupling**, and **distributed event processing**. ### 1. **Asynchrony** Services do not wait for a response from each other: they simply publish events ("order created") and keep working. This removes bottlenecks and allows thousands of events to be processed in parallel. ### 2. **Loose coupling** The publisher does not know who will receive the event. New subscribers (for example, notifications, analytics) can be added without changing the source service. This lets the system scale horizontally by adding new consumers as the load grows. ### 3. **Distributed processing** A broker (Kafka, RabbitMQ, and so on) distributes events among many subscribers running on different nodes. As traffic grows, new consumers are simply added, without stopping the system. ### 4. **Load buffering** The event broker temporarily stores events in a queue. If one service is overloaded, it processes them later without blocking the others. **Summary:** > **EDA scales naturally** because events are processed **in parallel, independently, and without rigid connections** between components. > The more load there is, the more subscribers can be added without changing the architecture.For the reviewerNote to the moderator (optional)Visible only to the moderator. Helps review go faster.