Apache Kafka is a well-known distributed streaming platform.

Ever wondered when to use Kafka? The importance of a distributed streaming platform is subjective. Let’s assume you have multiple applications, including web applications, mobile applications, and web server logs running in your organization. This means there is an ‘n’ number of applications that write logs or embed data – thus, we need to store this data efficiently.

When to Use Kafka?

Apache Kafka has many use cases;

Metrics – Kafka is mostly used for operational data monitoring, involving aggregating statistics from the distributed applications for producing centralized feeds of such operational data.

Log Aggregation − Kafka is used across the organization to collect logs from varying services and produce them in a standard format for multiple consumer bases.

Stream Processing – Frameworks like Spark and Storm read data from a particular topic, process it, and then write this processed data to new topics where it is then available for applications and users alike. Apache Kafka is a star performer when it comes to stream processing.

Manifold Uses of Kafka

Due to its scalability and fault tolerance, Kafka has big applications in big data – shining as a reliable way for quickly ingesting and moving massive data lakes. Let’s dig deep into some use cases where Kafka is the supreme choice.

  1. Stream Processing

Kafka streams can build a streaming platform that can transform input topics into output Kafka topics. All the while ensuring the application is fault-tolerant and distributed.

  1. Website Activity Tracking

This is the original use case of Kafka with LinkedIn, which gave birth to Kafka as we know it. LinkedIn still uses it for activity data tracking and operational metrics – all in real time.

  1. Metrics Monitoring and Collection

Apache Kafka can facilitate further by combining real-time monitoring applications that read from the Kafka topics.

  1. Log Aggregation

With Kafka, we can publish logs in Kafka topics and store them in a Kafka cluster. This enables the logs to be easily processed and aggregated.

  1. Analytics in Real-time

Perfect for real-time analytics – Kafka processes data instantly as it becomes available. It also transmits data from the producers to data handlers, furthering to data storage.

  1. Micro Services

Kafka has applications in microservices as well.

Microservices make the most out of Kafka by using it as a centric intermediary – facilitating communication by taking advantage of the publish-subscribe model. The receiver then decides asynchronously which events are to be received. This makes Kafka-based services reliable and scalable compared to other architectures.

Who needs and benefits from Kafka?

The decision of when to use Kafka depends on the offered benefits.

Kafka is easy to understand how it works; it is reliable, scales best, and is fault tolerant. Let’s go into detail and see who can benefit from Kafka the most.

Clustering Fault Tolerance and Scaling

The Kafka fault tolerance is important for any application, and you might have to scale it up in the future – thus, Kafka clustered design becomes the obvious choice. It is completely able to automatically process load and rebalance between consumers. When the message load increases too high, you are safe as you can introduce more nodes and consumers, given that you had it in mind and defined enough partitions.

Importance in Open Source Ecosystem

Apache Kafka is a known open-source stream processing platform designed for easier connectivity with other open-source systems like Kafka Connect. Owing to this, your architecture benefits from the entire ecosystem of ready-made connectors.


Kafka facilitates almost all types of content, granted the messages are not very big – you can easily add varying producers and consumers. Even when your business grows/changes, you won’t have to rewrite the entire architecture.

Handy Access

Kafka offers a built-in authentication structure. In Kafka, producers and consumers write to and read from the specific queues, this way, you can easily manage data access with a single centralized mechanism.

Real-Life Application? 

Call of Duty – does that ring a bell?

Activision is the name of the company that built call of duty. They have talked on multiple platforms about their problems and how Kafka helped them overcome them.

Final Word

Apache Kafka is a star component for many companies – mostly beneficial in business processes that involve massive amounts of data. Kafka can be scaled to linearly handle billions and even trillions of messages. Also, you will see Kafka Stream or Schema Registry being used together it Apache Kafka.

This brings us to the end of this article – if you found this helpful and want to learn more – feel free to explore the Apache Kafka data repository at Memphis. Learn about Kafka and discuss solutions to your problems in the public forum or with our representatives.