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Apache Kafka Review: Use Cases and Benefits of AWS Managed Apache Kafka

As digitization makes a profound presence, the need to gather, manage and process data in real-time has led many companies to count on Apache Kafka use cases and Apache Kafka reviews. Companies are now building applications based on various things that rely heavily on continuous data from a device, IOT setup, smart buildings, websites, etc.

Businesses are using events to share data with their microservices applications and for business analytics. Event streaming platforms allow companies to capture streaming data events such as clickstream events, transactions, IoT events that require real-time data analytics and data consistency.

Apache Kafka is a distributed, scalable platform that offers a high throughput and low latency and has become the de-facto event streaming platform for many businesses. More than 18 thousand companies leverage these benefits by implementing Kafka either as an open-source platform or through fully managed vendors like Amazon MSK.

This article takes a quick dig into Apache Kafka use cases and Apache Kafka review.   So,let’s start!

Apache Kafka Review
Apache Kafka Review & Use Cases

What is AWS managed Apache Kafka?

When you directly implement Kafka, it comes along with some challenges. These include: configuring the complex Kafka clusters, monitoring the server health, matching the Kafka architecture with growing data demands, and much more.

As the complexity of the use cases increases, it becomes difficult to set up, scale, and manage the event streaming application using the Apache Kafka platform.

Amazon Managed Streaming Kafka or Kafka on Amazon, a fully managed service, simplifies the implementation and configuration of Apache Kafka into an application. It enables you to seamlessly implement best practices for high productivity of event streaming applications using native Apache Kafka APIs to populate data lakes, stream data changes, etc.


Apache Kafka use cases & examples
Apache Kafka use cases and examples

AWS managed Apache Kafka-Use Cases

Here are some real-life examples where businesses leveraged Kafka on Amazon to underpin their journey towards an event-driven architecture.

  • Maintaining Uptime
    AWS managed Apache Kafka has an elite list of clientele like Delhivery, India’s leading e-commerce logistics partner. The Indian logistics giant has more than 350 applications and has to deal with an average of 1TB of data in a day to serve various analytical operations. With Amazon MSK taking care of the event-driven infrastructure, they were able to reduce the resources and time devoted to building and maintaining a suitable architecture.
  • Monitoring operational data
    Amazon MSK not only automatically configures and runs the Kafka clusters but also monitors cluster health regularly. It replaces the unhealthy nodes with no downtime. NutMeg, a digital finance managing company, adapted Amazon MSK to use Kafka to monitor the operational data and experienced an overall efficiency and low cluster maintenance time. Their successful journey is a prolific addition to amazing Apache Kafka reviews .
  • Real-time machine learning
    Real-time machine learning involves complex data processes. For this reason, companies like Poshmark and Voyage have leveraged Amazon MSK. These companies rely on real-time data-based applications to understand their customers and provide a holistic customer experience. With AWS managed Apache Kafka they can gain real-time insights faster and scale up the event streaming pipelines.



AWS managed Apache Kafka is the backbone of many companies that deal with huge chunks of data every minute of the day. From logistics to finance to the marketing industry, Amazon MSK has proved its worth by reducing the overhead maintenance in building microservices-based applications.

It helps companies configure Kafka clusters and aims to remove the complexity involved in setting up an open-source Kafka platform. This way companies enjoy the myriad of benefits of Apache Kafka on Amazon for various use cases without worrying about configuring and maintaining the infrastructure.

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