Kafka Use Cases

Apache Kafka is a high-throughput, open source message queue used by Fortune 100 companies, government entities, and startups alike.

Part of Kafka’s appeal is its wide array of use cases.  In this post we will outline several of Kafka’s uses cases from event sourcing to tracking web activities to metrics and more.

Use Cases for Apache Kafka

#1 Kafka as a Message Broker

Kafka is one of the most popular messaging technologies because it is ideal for handling large amounts of homogeneous messages, and it is the right choice for instances with high throughput.  An additional part of its appeal is that it pairs well with big data systems such a Elasticsearch and Hadoop

#2 Kafka for Metrics

Kafka is used for monitoring operational data by producing centralized feeds of that data.  Operational data — anything from technology monitoring to security logs to supplier information to competitor tracking and more — can then be aggregated and monitored.

#3 Kafka for Event Sourcing

Because Kafka supports the collection of large amounts of log data, it can be a crucial component to any event management system, including SIEM (Security Information Event Management).

#4 Kafka for Commit Logs

Kafka can act as a pseudo commit-log, using it for replication of data between nodes and for restoring data on failed nodes.  For instance, if you are tracking device data for internet of things (IoT) sensors and discover an issue with your database not storing all data, then you can replay data to replace the missing information in the database.

#5 Kafka for Tracking Website Activity 

Because website activity creates large amounts of data, with many messages generated for each individual user page view and activity on the page, Kafka is integral to ensuring that data is sent to and received by the relevant database(s).

 

More Kafka Education

We have several articles covering a range of Kafka topics to help with your Kafka implementation.  For our full list of articles, see our Kafka page.  Here are few to get you started:

  • Kafka vs. RabbitMQ  — If you’re looking for a message broker to handle high throughput and provide access to stream history, Kafka is likely the better choice. If you have complex routing needs and want a built-in GUI to monitor the broker, then RabbitMQ might be best for your application.
  • Creating a Kafka Topic — Kafka is structured by its four primary components: topics, producers, consumers, and brokers. In this post, we discuss topics.
  • Calculating Number of Kafka Partitions — A critical component of Kafka optimization is optimizing the number of partitions in the implementation. Use our calculation to determine the number of partitions needed.
  • Kafka Security Checklist — There are six key components to securing Kafka. These best practices will help you optimize Kafka and protect your data from avoidable exposure.

Still have questions about Kafka? Contact us today to learn about our Kafka training program and Kafka consulting services.

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Dattell LLCData consulting and implementation services from Dattell provide STRATEGY, ENGINEERING, and PERSPECTIVE to support your organization’s data projects. Our services include custom Data Architecture, Business Analytics, Operational Intelligence, Centralized Reporting, Automation, and Machine Learning. Dattell specializes in Apache Kafka and the Elastic Stack for reliable data collection, storage, and real-time display.

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