Here is a set of questions and answers for a Kafka developer:
Table of Contents
- What is Apache Kafka? Apache Kafka is an open-source distributed event streaming platform used for building real-time data pipelines and streaming applications.
- Explain Kafka’s architecture. Kafka consists of topics, producers, consumers, brokers, and Zookeeper. Producers publish messages to topics, consumers subscribe to topics to read messages, brokers manage the storage and replication of the message logs, and Zookeeper manages and coordinates Kafka brokers.
- What are the key components of a Kafka cluster? Kafka cluster consists of topics, brokers, Zookeeper, producers, and consumers.
- What is a Kafka topic? A topic is a category or feed name to which messages are published by producers and consumed by consumers.
- What is a Kafka broker? A Kafka broker is a server that stores and manages the Kafka topics. It is responsible for receiving messages from producers, storing them on disk, and serving them to consumers.
- What is a Kafka consumer group? A consumer group is a set of consumers that jointly consume a topic. Each message in a topic is consumed by only one consumer from the group.
Kafka Producer and Consumer
- How does Kafka guarantee message delivery? Kafka uses replication and distributed commit logs to ensure fault tolerance and durability, which helps guarantee message delivery.
- What are Kafka Producers? Producers are applications that publish messages to Kafka topics.
- Explain Kafka Consumers. Consumers are applications that subscribe to topics and read messages published to those topics.
- What is Kafka Consumer Offset? Kafka Consumer Offset is a pointer to the position in a partition where a consumer group has last read.
- How does Kafka handle consumer offset management? Kafka manages consumer offsets by storing them in a Kafka internal topic called “__consumer_offsets”.
Kafka Streams and Connect
- What is Kafka Streams? Kafka Streams is a library for building real-time stream processing applications on top of Apache Kafka.
- Explain Kafka Connect. Kafka Connect is a framework for scalable and reliable streaming data between Apache Kafka and other systems.
- What are the key components of Kafka Streams? Key components include StreamsBuilder, KStream, KTable, and Kafka Streams API.
- What are connectors in Kafka Connect? Connectors are plugins that provide reusable components to connect Kafka with external systems.
Kafka Configuration and Performance
- How can you optimize Kafka’s performance? Performance can be optimized by configuring parameters like batch size, message compression, tuning Kafka broker and producer/consumer configurations, and optimizing hardware resources.
- What is the role of Zookeeper in Kafka? Zookeeper in Kafka manages and coordinates the Kafka brokers, maintains broker membership, and helps with leader election.
- Explain Kafka’s message retention policy. Kafka’s message retention policy determines how long Kafka will retain messages in a topic before they are discarded.
Kafka Scalability and Fault Tolerance
- How does Kafka achieve fault tolerance? Kafka achieves fault tolerance through message replication across multiple brokers.
- What is Kafka partitioning? Partitioning is the way Kafka distributes messages across multiple brokers, allowing parallel processing and scalability.
- Explain Kafka replication. Kafka replication ensures that copies of the same data are maintained on multiple brokers to provide fault tolerance.
- How can you secure Kafka clusters? Kafka clusters can be secured using SSL encryption, SASL authentication, ACLs (Access Control Lists), and securing Zookeeper.
- Explain SSL in Kafka. SSL (Secure Sockets Layer) is used in Kafka to encrypt data transmitted between clients and brokers.
Kafka Monitoring and Troubleshooting
- What are some key metrics to monitor Kafka? Key metrics include message throughput, latency, disk utilization, network utilization, and consumer lag.
- How do you troubleshoot Kafka performance issues? Troubleshooting involves monitoring key metrics, checking logs, reviewing configurations, and analyzing resource utilization.
Kafka Use Cases and Best Practices
- What are some common use cases for Kafka? Use cases include log aggregation, stream processing, event sourcing, real-time analytics, and data integration.
- What are some best practices for designing Kafka applications? Best practices include choosing appropriate partitioning strategies, configuring proper retention policies, setting up appropriate replication factors, and optimizing consumer group management.
- Name some popular tools in the Kafka ecosystem. Some popular tools include Confluent Platform, Kafka Streams API, Kafka Connect, and MirrorMaker.
Real-time Streaming and Integration
- How does Kafka support real-time data streaming? Kafka’s distributed architecture and message persistence capabilities enable real-time data streaming.
- How can Kafka integrate with other systems? Kafka Connect provides connectors that allow seamless integration with various systems like databases, file systems, and messaging systems.