Monitoring Apache Kafka is essential to ensure the system’s health, reliability, and performance. Kafka exposes internal metrics through JMX, Prometheus, and other tools, which help track broker health, topic throughput, partition lag, consumer group progress, and disk usage. Whether preparing for an interview or working in a production environment, understanding Kafka metrics enables developers and DevOps professionals to maintain a resilient Kafka deployment.
These MCQs are designed to help you crack Kafka interviews and understand real-world monitoring practices from beginner to advanced levels.
1.) Which of the following tools is commonly used to collect and expose Kafka metrics for monitoring?
2.) Kafka exposes metrics using which Java technology?
3.) What is a common tool used with Prometheus to visualize Kafka metrics?
4.) Which of the following is a key metric to monitor consumer lag?
5.) What does the metric BytesInPerSec track?
6.) kafka.controller.KafkaController
7.) What Kafka metric tracks the number of incoming messages per second?
8.) What metric should be monitored to detect under-replicated partitions?
9.) In a Kafka Grafana dashboard, what does a high value in UnderReplicatedPartitions signify?
10.) How can Kafka metrics be exposed to Prometheus?