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Question 11

Which Kafka metric would you monitor to identify potential leader election issues?

  • A. LeaderElectionRateAndTimeMs
  • B. RequestRate
  • C. MessageInPerSec
  • D. ISRTime

Explanation: LeaderElectionRateAndTimeMs is the Kafka metric that indicates the rate and time taken for leader elections. Monitoring this metric can help identify potential issues with leader election processes within the Kafka cluster.

  • B, C, and D are incorrect because they do not specifically measure leader election-related metrics.

Answer: A

Question 12

What is the purpose of the ActiveControllerCount metric in Kafka?

  • A. To count the number of active consumers
  • B. To indicate the number of active brokers
  • C. To show the number of active controller nodes
  • D. To measure the rate of message production

Explanation: The ActiveControllerCount metric indicates the number of active controller nodes in a Kafka cluster. There should be exactly one active controller in a healthy Kafka cluster.

  • A, B, and D are incorrect because they measure different aspects of Kafka performance and health.

Answer: C

Question 13

Which Kafka metric helps in monitoring the health of consumer groups?

  • A. ConsumerLag
  • B. ProducerRequestRate
  • C. BrokerTopicBytesOutPerSec
  • D. FetchLatency

Explanation: The ConsumerLag metric helps in monitoring the health of consumer groups by indicating how far behind a consumer group is in processing messages. This metric is crucial for ensuring timely message consumption.

  • B, C, and D are incorrect because they measure different aspects of Kafka performance and health.

Answer: A

Question 14

Which tool can be used to collect JMX metrics from Kafka brokers for monitoring?

  • A. Logstash
  • B. JConsole
  • C. Metricbeat
  • D. Telegraf

Explanation: Telegraf is a tool that can be used to collect JMX metrics from Kafka brokers for monitoring. It has a JMX plugin that can be configured to scrape metrics and forward them to a monitoring system like InfluxDB or Prometheus.

  • A, B, and C are incorrect because while Logstash and Metricbeat can be used for other monitoring tasks, JConsole is typically used for viewing JMX metrics interactively, not for automated metric collection.

Answer: D

Question 15

What does the BrokerTopicBytesOutPerSec metric measure in Kafka?

  • A. The number of bytes produced to a topic per second
  • B. The number of bytes consumed from a topic per second
  • C. The number of bytes replicated per second
  • D. The number of bytes stored in a topic

Explanation: The BrokerTopicBytesOutPerSec metric measures the number of bytes consumed from a topic per second. It provides insights into the data throughput on the consumer side.

  • A, C, and D are incorrect because they describe different aspects of data flow and storage in Kafka.

Answer: B

Question 16

Which metric should be monitored to detect partition imbalance in a Kafka cluster?

  • A. PartitionCount
  • B. LeaderCount
  • C. UnderReplicatedPartitions
  • D. PartitionLoad

Explanation: PartitionLoad is the metric that should be monitored to detect partition imbalance in a Kafka cluster. It indicates how partitions are distributed and can help identify if some brokers are handling significantly more partitions than others.

  • A, B, and C are incorrect because while they measure various aspects of partition and leader count, they do not directly address partition load balance.

Answer: D

Question 17

Which Kafka metric indicates the rate of log flush operations?

  • A. LogFlushRateAndTimeMs
  • B. DiskFlushRate
  • C. LogRetentionRate
  • D. FlushTime

Explanation: LogFlushRateAndTimeMs is the Kafka metric that indicates the rate and time of log flush operations. This metric helps monitor how often logs are being flushed to disk, which is critical for data durability and performance.

  • B, C, and D are incorrect because they either do not exist or measure different aspects of Kafka performance.

Answer: A

Question 18

What is the significance of the RequestQueueSize metric in Kafka?

  • A. It measures the number of requests waiting to be processed by Kafka brokers.
  • B. It indicates the number of active consumer requests.
  • C. It shows the total number of requests handled by Kafka brokers.
  • D. It measures the size of the message queue in bytes.

Explanation: The RequestQueueSize metric measures the number of requests waiting to be processed by Kafka brokers. A high value may indicate that brokers are overloaded and unable to process requests in a timely manner.

  • B, C, and D are incorrect because they measure different aspects of request handling and message queuing.

Answer: A

Question 19

Which Kafka metric would you monitor to understand the latency experienced by producers?

  • A. ProducerRequestRate
  • B. ProducerLatency
  • C. RequestQueueSize
  • D. ProducerRequestQueueTimeMs

Explanation: ProducerRequestQueueTimeMs is the Kafka metric that measures the latency experienced by producers in the request queue. Monitoring this metric helps understand the delay producers face before their requests are processed by the broker.

  • A, B, and C are incorrect because they measure different aspects of producer requests and performance.

Answer: D

Question 20

Which metric is critical for monitoring Kafka broker heap memory usage?

  • A. BrokerHeapMemoryUsed
  • B. JvmMemoryUsage
  • C. HeapMemoryUsage
  • D. BrokerJvmHeap

Explanation: JvmMemoryUsage is the critical metric for monitoring Kafka broker heap memory usage. It provides insights into how much heap memory is used by the JVM, which is essential for identifying potential memory-related issues.

  • A and D are incorrect as they are not standard Kafka metrics. C is also not the specific metric name used in Kafka monitoring tools.

Answer: B