Kafka Playground

Get access to the Kafka playground with one click

What is Apache Kafka?

Apache Kafka is an open-source event streaming platform. It ingests data from different sources and processes it on a real-time basis. It is used by thousands of companies in various scenarios such as creation of data pipelines, on-the-fly processing, and so on.

Kafka is generally deployed as a cluster of two or more instances across multiple servers. It can be deployed on bare-metal hardware, on virtual machines, or on containers using Docker or similar container platforms.

Apache Kafka provides three functionalities that can be used for event streaming:

  1. Publish (write) and subscribe (read) to different streams of events.
  2. Store the streams of events for an indefinite period of time.
  3. Process the events that are written on the stream, on a real-time basis.

Features of Kafka

  • Stores the streams of events/messages in a fault-tolerant manner.
  • Ability to scale the cluster for processing trillions of events per day.
  • Distributed architecture to ensure fault tolerance, high scalability, reliability, high availability, etc.
  • Processes the messages of different streams to provide real-time aggregations, transformations, filtering, etc.
  • Connects with hundreds of data sources and sinks, such as Elasticsearch, Postgres, and others, using Kafka Connect.
  • Allows connectivity using client libraries in various programming languages.

How does Kafka work?

Each instance of Kafka is interchangeably called Kafka server or Kafka broker.

  • The brokers receive messages/events from producers and store them on disk. The producers are external applications that generate data. They connect to Kafka for writing that data.
  • The messages can be fetched from consumers using the topic name. The consumers are external applications that fetch the data written by the producers.
  • The broker maintains an offset for the consumer fetching from the topic. The offset helps in tracking how many messages/events have been consumed by the consumer.
  • To differentiate the messages from multiple streams, they are written into different topics.
  • These topics are maintained as log files on disk. The topics are partitioned into multiple log files and stored across the cluster for better scalability.
  • For fault tolerance, the topics can be replicated using a suitable replication factor. These components can be configured differently for each of the topics.

The playground offers a Kafka cluster of two brokers and a Zookeeper that is used to maintain the status of the nodes, a list of topics in Kafka, and much more.