Q1. Explain Kafka topics, partitions and offsets.
A topic is a named stream of records. It is split into partitions, which are the unit of ordering, parallelism and replication. Records within a partition are strictly or...
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Q2. How do message queues help and what guarantees do they provide?
Queues decouple producers from consumers, absorb traffic spikes, enable retries and fan-out, and improve resilience when a downstream service is slow or down. Delivery se...
Q3. How do Kafka consumer groups enable scaling?
A consumer group is a set of consumers that cooperatively consume a topic. Kafka assigns each partition to exactly one consumer in the group, so the group as a whole proc...
Q4. What ordering guarantees do message systems provide?
Ordering is usually per partition or per queue, not global. - Kafka orders records within a partition only. Records with the same key go to the same partition, preserving...
Q5. How do you deal with consumer lag and backpressure?
Consumer lag is the gap between the latest produced offset and the committed offset. Rising lag means producers outpace consumers, and left unchecked it grows unbounded a...
Q6. How does Kafka provide exactly-once semantics?
Kafka combines two features: - Idempotent producer: each producer gets a producer id and sequence numbers. The broker deduplicates retries within a session, so a network ...
Q7. How would you design a change data capture pipeline?
CDC captures row-level changes from a source database and streams them downstream with low latency. A typical design: - Capture: read the database transaction log with a ...