To quickly get started using Apache Kafka, you need to deploy a Kafka instance and be able to connect and run a sample Kafka application.

While you can certainly download and install an Apache Kafka instance on your local system, the IBM Event Streams on IBM Cloud service is a fully managed Apache Kafka instance.

In this tutorial, we’ll show you just how easy it is to deploy a Kafka instance using IBM Event Streams on IBM Cloud service and then connect and run one of the sample applications.

Prerequisites

General Apache Kafka concepts
IBM Cloud account
For the sample application, you must also have installed Git, Gradle, and Java 8 or higher.

Steps

Because the IBM Event Streams Lite plan limits you to using a single partition, it is not suitable for production use. You can review the different plans in the documentation.

For this tutorial, for our Kafka instance, we use Event Streams on IBM Cloud.

To deploy a Kafka instance and connect and use a Kafka app, you’ll need to complete these steps:

To deploy a managed Kafka instance, create an Event Streams on IBM Cloud service instance.
To connect and use a Kafka app in your managed Kafka instance, you need to:
- Create a topic
- Create credentials
- Clone the Github repo for the sample app
- Run the consuming app
- Run the producing app
Delete the topic

These steps are demonstrated for you in the following video:

These steps are also detailed in the IBM Event Streams for IBM Cloud getting started tutorial.

Summary

Congratulations! You have now successfully created an instance of IBM Event Streams on Cloud and run your first sample Kafka application.

In general, for ongoing development, you will need to run at least a standard instance of IBM Event Streams on Cloud. You can upgrade the Lite instance you created in this tutorial to a Standard instance. However, for enterprise-scale deployments or a requirement for private networking, heightened privacy, and security, the Enterprise plan is required.

Deploying and using a basic Kafka instance

Deploying and using a basic Kafka instance