Back-End Development Message Queues and Event-Driven Architecture 3

Question 1

What is CQRS (Command Query Responsibility Segregation)?

Accepted Answer

A pattern that separates the model for writing data (commands) from reading data (queries)

Answer

A caching strategy that separates read cache from write cache layers

Answer

A database replication technique used for high availability

Answer

An API versioning strategy for maintaining backward compatibility

Question 2

What problem does 'backpressure' address in event-driven systems?

Accepted Answer

Preventing a fast producer from overwhelming a slow consumer

Answer

Preventing encryption overhead from slowing message throughput

Answer

Balancing CPU usage evenly across Kafka broker partitions

Answer

Reducing network latency between geographically distributed brokers

Question 3

What is the 'Saga pattern' used for in event-driven microservices?

Accepted Answer

Managing distributed transactions across multiple services without a global lock

Answer

Generating API documentation from service event schemas automatically

Answer

Caching results of complex multi-service data aggregation queries

Answer

Routing messages between services using different messaging protocols

Question 4

What is the primary advantage of event-driven architecture over synchronous direct service-to-service calls?

Accepted Answer

It reduces coupling between services, improving resilience and independent scalability

Answer

It eliminates the need for error handling within individual services

Answer

It guarantees zero message loss with no additional configuration required

Answer

It removes the need for writing API documentation between teams

Question 5

What does 'idempotency' mean in the context of a message consumer?

Accepted Answer

Processing the same message multiple times produces the same result as processing it once

Answer

The consumer processes messages strictly in the order they were originally sent

Answer

The consumer can read from multiple queues simultaneously without conflict

Answer

Messages are automatically deduplicated by the broker before reaching the consumer

Question 6

What is the purpose of a schema registry in an event streaming platform like Kafka?

Accepted Answer

Centrally managing and enforcing schemas so producers and consumers share a contract

Answer

Storing consumer group offsets and partition assignment metadata

Answer

Registering Kafka broker nodes with the cluster coordinator (ZooKeeper or KRaft)

Answer

Tracking per-message delivery acknowledgments across all consumer groups

Question 7

Which message delivery semantic guarantees that each message is processed exactly once with no duplicates and no losses?

Accepted Answer

Exactly-once delivery

Answer

At-most-once delivery

Answer

At-least-once delivery

Answer

Best-effort delivery