Kafka Interview Questions and Answers Preparation Practice Test | Freshers to Experienced | Detailed Explanations
What you will learn
Deep Understanding of Kafka Architecture and Core Concepts
Proficiency in Kafka Advanced Features and Use Cases
Skills in Kafka Administration, Monitoring, and Operations
Practical Knowledge of Kafka Development Practices
Why take this course?
- Question: What is the role of partitions in a Kafka cluster?
Answer: Partitions play a critical role in distributing data across the cluster, thereby achieving load balancing. Each topic can be split into multiple partitions, allowing messages within a topic to be spread across several brokers in the cluster. This distribution not only enhances data write and read efficiency by parallelizing operations but also increases fault tolerance and scalability by ensuring that data is not bottlenecked on a single server. Unlike option A (replication), partitioning is responsible for distributing data, while replication handles duplicating data for fault tolerance. Option B is incorrect as topic organization is the role of the topic itself, not the partitions within it. Lastly, option D is inaccurate because serialization and deserialization are functions of producers and consumers, respectively, not of partitions.
- Question: Which of the following best describes the purpose of Kafka Streams?
Answer: To process data in real-time within a Kafka cluster.
Explanation: Kafka Streams is a client library for building applications and microservices where the input and output data are stored in Kafka clusters. It allows for real-time processing and analysis of data stored in Kafka, including functionalities such as filtering, grouping, and aggregating message streams. Option A describes a scenario more aligned with Kafka’s mirroring or cross-cluster replication features, not Kafka Streams. Option B inaccurately describes Kafka Connect, which is intended for integrating Kafka with external databases, systems, or applications. Option D misunderstands the purpose of log compaction in Kafka, which is aimed at reducing storage space by cleaning up old records without compromising the integrity of the data.
- Question: Which of the following metrics is crucial for monitoring Kafka’s performance?
Answer: Under-replicated partitions.
Explanation: Monitoring under-replicated partitions is crucial for Kafka administrators because it directly impacts data reliability and fault tolerance. Under-replicated partitions indicate that not all replicas of a partition have the current data, posing a risk if the leader partition fails and a follower, which might be lagging, needs to take over. While CPU usage (option A) and disk write speeds (option D) of clients and consumer applications can affect performance, they are not Kafka-specific metrics and are more related to client-side performance monitoring. The number of active connections to a database (option B) is irrelevant in the context of Kafka performance metrics, as Kafka does not directly interact with databases without using Kafka Connect.
- Question: What is the primary purpose of the Kafka Schema Registry?
Answer: To store schemas for Kafka messages and ensure compatibility.
Explanation: The Kafka Schema Registry allows for the storage of schema definitions for Kafka producers and consumers, ensuring that the schemas used to write and read messages are compatible with each other. It plays a crucial role in managing and enforcing schemas across all messages in a Kafka cluster, particularly important in data-intensive applications where data format and integrity are paramount. Option A is incorrect because managing the configuration of Kafka brokers is typically done through Kafka’s server properties files or management tools. Option C is related to consumer offsets, not the Schema Registry’s functionality. Option D misconceives the Schema Registry’s role, which is focused on schema management rather than logging configuration changes.