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Kafka Interview Questions for Developers
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Top Kafka Interview Questions for Freshers and Experienced
40 Questions
Easy · Medium · Hard
Try answering from memory, then check the reference answer and rate yourself. Your notes are optional and are not automatically graded.
1 How does Kafka ensure message ordering within a partition? medium
partitioningordering
Reference answer
Kafka maintains strict ordering within a partition. Messages with the same key are routed to the same partition, ensuring order is preserved during production and consumption.
Mention key-based routing and partition-level ordering
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2 What happens if a Kafka producer sends messages without a key? medium
producerpartitioning
Reference answer
Messages are distributed across partitions using a round-robin or sticky partitioning strategy. This can lead to loss of ordering across messages.
Highlight impact on ordering
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3 Explain the role of partitions in Kafka scalability. medium
partitioningscalability
Reference answer
Partitions allow Kafka topics to be distributed across brokers, enabling parallel consumption and higher throughput. More partitions increase scalability but add management overhead.
Mention parallelism
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4 What is ISR (In-Sync Replica) in Kafka? hard
replicationisr
Reference answer
ISR is the set of replicas that are fully caught up with the leader. Only ISR members are eligible for leader election, ensuring data consistency.
Explain leader and follower relationship
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5 How does Kafka handle consumer offset management? medium
consumeroffsets
Reference answer
Kafka stores offsets in an internal topic (__consumer_offsets). Consumers commit offsets manually or automatically to track progress.
Mention auto vs manual commit
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6 What issue occurs if multiple consumers read from the same partition? medium
consumer-grouppartitioning
Reference answer
Kafka ensures only one consumer per partition in a consumer group. Multiple consumers cannot read the same partition simultaneously within a group.
Mention consumer group balancing
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7 How would you debug consumer lag in Kafka? hard
debuggingconsumer-lag
Reference answer
Check consumer offsets vs latest offsets, analyze processing speed, inspect broker health, and verify partition assignment and rebalancing issues.
Mention monitoring tools
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8 What is the purpose of Kafka retention policy? medium
retentionstorage
Reference answer
Retention policy defines how long messages are stored based on time or size. It allows Kafka to act as a log-based storage system.
Mention time vs size-based retention
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9 Explain leader election in Kafka. hard
replicationleader-election
Reference answer
Kafka elects a leader from ISR replicas for each partition. If the leader fails, a new leader is chosen from ISR to maintain availability.
Mention ISR importance
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10 What happens when ISR shrinks? hard
isrreplication
Reference answer
If replicas fall behind, they are removed from ISR. This reduces fault tolerance and increases risk if leader fails.
Discuss impact on durability
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11 How does Kafka ensure durability of messages? medium
durabilityreplication
Reference answer
Kafka uses replication and acknowledgments (acks). With acks=all, messages are written to all ISR replicas before acknowledgment.
Mention acks config
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12 What is the difference between at-least-once and exactly-once delivery? hard
delivery-semanticstransactions
Reference answer
At-least-once may produce duplicates, while exactly-once ensures no duplicates using idempotent producers and transactions.
Mention idempotence
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13 How does Kafka handle high throughput? medium
performancethroughput
Reference answer
Kafka uses batching, sequential disk writes, partitioning, and zero-copy transfer to achieve high throughput.
Mention batching and disk I/O
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14 What is idempotent producer in Kafka? hard
produceridempotence
Reference answer
An idempotent producer ensures messages are not duplicated during retries by assigning unique sequence numbers.
Mention retries
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15 What happens if a consumer crashes before committing offset? medium
consumeroffsets
Reference answer
The consumer will reprocess messages from the last committed offset, potentially causing duplicate processing.
Explain reprocessing
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16 How does Kafka achieve fault tolerance? medium
fault-tolerancereplication
Reference answer
Kafka replicates partitions across brokers and uses ISR for leader election, ensuring availability during failures.
Mention replication factor
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17 What is a Kafka broker? easy
brokerarchitecture
Reference answer
A broker is a server that stores data and serves client requests. A Kafka cluster consists of multiple brokers.
Keep it simple
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18 Explain the role of ZooKeeper in Kafka (legacy setup). medium
zookeeperarchitecture
Reference answer
ZooKeeper manages metadata, leader election, and cluster coordination. Newer Kafka versions use KRaft mode instead.
Mention KRaft replacement
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19 What is KRaft mode in Kafka? hard
kraftarchitecture
Reference answer
KRaft removes ZooKeeper dependency by integrating metadata management within Kafka using a Raft-based quorum.
Mention Raft protocol
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20 How does Kafka handle backpressure? hard
performancebackpressure
Reference answer
Kafka handles backpressure through consumer lag, batching, and controlling fetch sizes and producer rates.
Mention throttling
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21 What is a consumer group in Kafka? easy
consumer-groupbasics
Reference answer
A consumer group is a set of consumers sharing a group ID. Each partition is consumed by one consumer within the group.
Mention load balancing
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22 How does Kafka rebalance consumers? medium
rebalanceconsumer
Reference answer
When consumers join/leave, Kafka redistributes partitions among them. This ensures balanced workload.
Mention impact on latency
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23 What causes frequent rebalancing? hard
rebalancedebugging
Reference answer
Frequent consumer joins/leaves, session timeouts, or slow processing can trigger rebalances.
Mention session timeout
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24 How would you improve Kafka consumer performance? medium
performanceconsumer
Reference answer
Increase partitions, optimize batch size, tune fetch settings, and ensure efficient processing logic.
Mention parallelism
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25 What is log compaction? medium
log-compactionstorage
Reference answer
Log compaction retains only the latest record per key, reducing storage while preserving latest state.
Mention use cases
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26 How does Kafka guarantee high availability? medium
availabilityreplication
Reference answer
Through replication, ISR, and automatic leader election, Kafka ensures minimal downtime.
Mention replication factor
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27 What is the role of acknowledgments in Kafka producer? medium
produceracks
Reference answer
Acks determine durability guarantees. acks=0,1,all control how many replicas must confirm write.
Compare all values
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28 How does batching improve Kafka performance? medium
performancebatching
Reference answer
Batching groups multiple messages into a single request, reducing network overhead and increasing throughput.
Mention linger.ms
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29 What happens when a Kafka broker goes down? medium
brokerfailure
Reference answer
Partitions hosted on that broker become unavailable until a new leader is elected from ISR.
Mention leader election
Did you know it?
30 What is producer retry mechanism? medium
producerretries
Reference answer
Producer retries sending messages on failure, which may cause duplicates unless idempotence is enabled.
Mention idempotent producer
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31 How would you secure a Kafka cluster? hard
securityauthentication
Reference answer
Use SSL/TLS for encryption, SASL for authentication, and ACLs for authorization.
Mention ACLs
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32 What is the difference between Kafka and traditional message queues? medium
architecturecomparison
Reference answer
Kafka is distributed, log-based, and retains messages, while traditional queues delete messages after consumption.
Mention persistence
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33 How does Kafka handle large messages? hard
performancemessages
Reference answer
Kafka allows large messages but recommends external storage and sending references due to performance impact.
Mention max.message.bytes
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34 What is a Kafka topic? easy
topicbasics
Reference answer
A topic is a logical channel where messages are published and consumed, divided into partitions.
Keep definition clear
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35 How does Kafka handle message compression? medium
compressionperformance
Reference answer
Kafka supports compression (gzip, snappy, lz4) to reduce network usage and improve throughput.
Mention trade-offs
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36 What is the role of fetch.min.bytes in consumers? hard
consumerperformance
Reference answer
It controls minimum data fetched per request, improving efficiency by reducing small fetches.
Mention batching effect
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37 How does Kafka handle duplicate messages? medium
duplicatesidempotence
Reference answer
Duplicates may occur due to retries. Idempotent producers and transactions help avoid duplicates.
Mention exactly-once
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38 What is transactional messaging in Kafka? hard
transactionsexactly-once
Reference answer
Kafka transactions ensure atomic writes across partitions, enabling exactly-once semantics.
Mention producer config
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39 How does Kafka ensure data consistency? medium
consistencyreplication
Reference answer
Through replication, ISR, and controlled leader election, Kafka maintains consistency across replicas.
Mention ISR
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40 What are common causes of Kafka performance degradation? hard
performancedebugging
Reference answer
High disk I/O, insufficient partitions, large messages, and inefficient consumers can degrade performance.
Mention monitoring metrics
Did you know it?
0 / 0 answered