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NEW QUESTION # 13
Which use cases would benefit most from continuous event stream processing? (Choose three.)
- A. Fraud detection
- B. End-of-day financial settlement processing
- C. Historical dashboards
- D. Log monitoring/application fault detection
- E. Context-aware product recommendations for e-commerce
Answer: A,D,E
Explanation:
Real-time analysis of transactions helps detect suspicious activity instantly.
Context-aware product recommendations for e-commerce requires real-time user behavior tracking to serve personalized recommendations.
Log monitoring/application fault detection needs immediate processing to alert on system issues or failures.
NEW QUESTION # 14
A customer has a use case for a ksqlDB persistent query. You need to make sure that duplicate messages are not processed and messages are not skipped.
Which property should you use?
- A. ksql.streams auto.offset.reset=latest
- B. ksql.fail.on.production.error=false
- C. ksql.streams auto offset.reset=earliest
- D. processing.guarantee=exactly_once
Answer: D
Explanation:
processing.guarantee=exactly_once ensures that messages are processed exactly once by ksqlDB, preventing both duplicates and message loss.
NEW QUESTION # 15
What is the correct permission check sequence for Kafka ACLs?
What is the correct permission check sequence for Kafka ACLs?
- A. Allow ACL -> Deny ACL -> Super Users -> Deny
- B. Super Users -> Allow ACL -> Deny ACL-> Deny
- C. Super Users -> Deny ACL -> Allow ACL -> Deny
- D. Deny ACL -> Deny -> Allow ACL -> Super Users
Answer: B
Explanation:
Kafka checks permissions in the following sequence:
1. Super Users: If the user is a super user (defined via super.users), access is granted immediately.
2. Allow ACL: If there is a matching Allow ACL, Kafka proceeds to the next step.
3. Deny ACL: If there is a matching Deny ACL, access is denied (even if an Allow exists).
4. Deny: If no matching ACLs are found, access is denied by default.
This order ensures that super users bypass ACLs, denials override allows, and default is deny.
NEW QUESTION # 16
Your Kafka cluster has four brokers. The topic t1 on the cluster has two partitions, and it has a replication factor of three. You create a Consumer Group with four consumers, which subscribes to t1.
In the scenario above, how many Controllers are in the Kafka cluster?
- A. One
- B. Four
- C. two
- D. three
Answer: A
Explanation:
In a Kafka cluster, only one broker acts as the Controller at any given time. The Controller is responsible for managing cluster metadata, such as partition leadership and broker status. Even if the cluster has multiple brokers (in this case, four), only one is elected as the Controller, and others serve as regular brokers. If the current Controller fails, another broker is automatically elected to take its place.
NEW QUESTION # 17
Which tool is used for scalably and reliably streaming data between Kafka and other data systems?
- A. Kafka Streams
- B. Kafka Connect
- C. Kafka Schema Registry
- D. Kafka REST Proxy
Answer: B
Explanation:
Kafka Connect is the tool designed for scalable and reliable integration between Kafka and external data systems (e.g., databases, cloud storage, key-value stores). It supports source connectors (to pull data into Kafka) and sink connectors (to push data from Kafka).
NEW QUESTION # 18
Which valid security protocols are included for broker listeners? (Choose three.)
- A. SASL_SSL
- B. SSL
- C. PLAINTEXT
- D. SASL
- E. GSSAPI
Answer: A,B,C
NEW QUESTION # 19
When a broker goes down, what will the Controller do?
- A. Trigger a leader election among the remaining followers to distribute leadership.
- B. Become the leader for the topic/partition that needs a leader, pending the broker return in the cluster.
- C. Automatically elect the least loaded broker to become the leader for every orphan's partitions.
- D. Wait for a follower to take the lead.
Answer: A
Explanation:
When a broker goes down, the Controller detects the failure and triggers a leader election for all partitions that had their leader on the failed broker. The leader is chosen from the in-sync replicas (ISRs) of each partition.
NEW QUESTION # 20
A company is setting up a log ingestion use case where they will consume logs from numerous systems. The company wants to tune Kafka for the utmost throughput.
In this scenario, what acknowledgment setting makes the most sense?
- A. acks=all
- B. acks=0
- C. acks=1
- D. acks=undefined
Answer: B
Explanation:
acks=0 provides the highest throughput because the producer does not wait for any acknowledgment from the broker. This minimizes latency and maximizes performance.
However, it comes at the cost of no durability guarantees - messages may be lost if the broker fails before writing them. This setting is suitable when throughput is critical and occasional data loss is acceptable, such as in some log ingestion use cases where logs are also stored elsewhere.
NEW QUESTION # 21
What is the atomic unit of data in Kafka?
- A. Offset
- B. Partition
- C. Topic
- D. Message
Answer: D
Explanation:
The message (also called a record) is the atomic unit of data in Kafka. It consists of a key, value, and optional headers and metadata. Messages are written to partitions and read by consumers.
NEW QUESTION # 22
You have an existing topic t1 that you want to delete because there are no more producers writing to it or consumers reading from it.
What is the recommended way to delete the topic?
- A. Delete the offsets for that topic from the consumer offsets topic.
- B. Delete the log files and their corresponding index files from the leader broker.
- C. The consumer should send a message with a 'null' key.
- D. If topic deletion is enabled on the brokers, delete the topic using Kafka command line tools.
Answer: D
Explanation:
The recommended and safe method to delete a topic is to use the Kafka CLI tool kafka-topics.sh --delete command, provided that delete.topic.enable=true is set on the brokers.
NEW QUESTION # 23
You are managing a Kafka cluster with five brokers (broker id '0', '1','2','3','4') and three ZooKeepers. There are 100 topics, five partitions for each topic, and replication factor three on the cluster. Broker id '0' is currently the Controller, and this broker suddenly fails.
Which statements are correct? (Choose three.)
- A. The broker id is used as the epoch number to prevent a split brain scenario.
- B. The Controller is responsible for reassigning partitions to the consumers in a Consumer Group.
- C. The number of Controllers should always be equal to the number of brokers alive in the cluster.
- D. Kafka uses ZooKeeper's ephemeral node feature to elect a controller.
- E. The Controller uses the epoch number to prevent a split brain scenario.
- F. The Controller is responsible for electing Leaders among the partitions and replicas.
Answer: D,E,F
Explanation:
Kafka relies on ZooKeeper's ephemeral nodes to detect if a broker (controller) goes down and to elect a new controller.
The controller manages partition leadership assignments and handles leader election when a broker fails.
The epoch number ensures coordination and avoids outdated controllers acting on stale data.
NEW QUESTION # 24
Where are Apache Kafka Access Control Lists stored'?
- A. Broker
- B. Schema Registry
- C. ZooKeeper
- D. Connect
Answer: C
Explanation:
In Apache Kafka (open-source), Access Control Lists (ACLs) are stored in ZooKeeper. Kafka brokers retrieve and enforce ACLs from ZooKeeper at runtime.
NEW QUESTION # 25
You want to increase Producer throughput for the messages it sends to your Kafka cluster by tuning the batch size ('batch size') and the time the Producer waits before sending a batch ('linger.ms').
According to best practices, what should you do?
- A. Increase 'batch.size' and increase 'linger.ms'
- B. Increase 'batch.size' and decrease 'linger.ms'
- C. Decrease 'batch.size' and decrease 'linger.ms'
- D. Decrease 'batch.size' and increase 'linger.ms'
Answer: A
Explanation:
Increasing batch.size allows the producer to accumulate more messages into a single batch, improving compression and reducing the number of requests sent to the broker.
Increasing linger.ms gives the producer more time to fill up batches before sending them, which improves batching efficiency and throughput.
This combination is a best practice for maximizing throughput, especially when message volume is high or consistent latency is not a strict requirement.
NEW QUESTION # 26
What is the primary purpose of Kafka quotas?
- A. Limit the number of clients that can connect to the Kafka cluster.
- B. Limit the total number of Partitions in the Kafka cluster
- C. Throttle clients to prevent them from monopolizing Broker resources.
- D. Guarantee faster response times for some clients.
Answer: C
Explanation:
Kafka quotas are used to limit the throughput (bytes/sec) of producers and consumers to ensure fair resource usage and prevent any single client from overwhelming the brokers.
NEW QUESTION # 27
A topic 'recurring payments' is created on a Kafka cluster with three brokers (broker id '0', '1', '2') and nine partitions. The 'min.insync replicas' is set to three, and producer is set with 'acks' as 'all'. Kafka Broker with id '0' is down.
Which statement is correct?
- A. Producers can write messages to all the partitions, because new leaders for the partitions will be elected.
- B. Producers will only be able to write messages to the topic where the Leader for the partition is on Broker id T.
- C. Producers and consumers will have no impact on six of the nine partitions.
- D. Consumers can read committed messages from partitions on broker id T, "2\
Answer: C
Explanation:
With 9 partitions spread across 3 brokers, each broker typically hosts 3 leaders (assuming even distribution). When Broker 0 fails, the partitions for which it was leader will elect new leaders on brokers 1 or 2 if enough in-sync replicas (ISRs) remain. But since min.insync.replicas=3 and only 2 brokers are up, no partition can meet the minimum in-sync replica requirement, so producers with acks=all will fail to write. However, for partitions where Broker 0 is not the leader, consumers can still read committed messages. Given that only 3 partitions likely had Broker 0 as leader, six partitions remain accessible for reads, but not writes.
NEW QUESTION # 28
Which model does Kafka use for consumers?
- A. Pull
- B. Enrollment
- C. Push
- D. Publish
Answer: A
Explanation:
Kafka uses a pull model for consumers, where consumers poll the broker to retrieve messages at their own pace. This model gives consumers more control over flow and backpressure, improving scalability and reliability.
NEW QUESTION # 29
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