Section checkpoint

Messaging and Realtime

10 questions drawn from the 5 chapters in this section. If most land on the first try, you are ready for the next section. If not, the explanation after each answer says which idea to revisit.

Checkpoint

10 questions · first-try answers earn the most XP

1. An order event needs to notify the customer, update analytics, and refresh a dashboard. Should these be three queues?

2. Your consumer group has 9 members on a topic with 3 partitions. What happens?

3. What is the main practical reason to choose Kafka over a plain work queue?

4. Why does Kafka give at-least-once delivery by default, and what must a consumer do about it?

5. What consistency problem does splitting writes from reads (CQRS) introduce?

6. When is event sourcing genuinely worth the extra machinery, according to the chapter?

7. Once a bounded queue is full, choosing to drop new items is acceptable for which kind of data?

8. When a bounded buffer is full, is it acceptable to block the producer rather than drop items?

9. According to the chapter's ladder, when should you climb from polling to SSE to WebSockets?

10. Why is polling every 5 seconds a poor choice for a page with a million fans watching live scores?

What this checkpoint covers

Put it to work in a drill

Next section: Reliability