Imagine two microservices: Service A and Service B. Service A sends an event when it finishes a task. How does this event help decouple Service A from Service B?
Think about how events allow services to work independently without waiting.
Events let Service A send messages without waiting for Service B. This means Service A and B do not depend on each otherβs availability, reducing tight coupling.
Which architecture pattern best demonstrates how events decouple services?
Think about which pattern uses events to communicate asynchronously.
Event-driven architecture uses a message broker to send events asynchronously, allowing services to operate independently and decoupled.
When microservices communicate via events, how does this improve scalability?
Consider how asynchronous processing affects service load.
Events allow services to handle messages independently and at their own pace, enabling parallel processing and better scalability.
Using events to decouple services has benefits but also tradeoffs. Which is a common tradeoff?
Think about what happens when communication is asynchronous and indirect.
Because events are asynchronous and indirect, it can be challenging to trace data flow and debug problems across services.
A system has 5 microservices communicating via events. Each service produces 100 events per second. If the message broker can handle 400 events per second, what is the maximum sustainable event throughput without delays?
Consider the total events produced and the broker's capacity.
Each of the 5 services produces 100 events per second, totaling 500 events per second. The broker can only handle 400 events per second, so the maximum sustainable throughput without delays is 400 events per second (by throttling production).