A Strimzi Kafka Quickstart for Quarkus with Strimzi CLI
Quarkus Strimzi Demo (by using Strimzi Kafka CLI)
This project illustrates how you can interact with Apache Kafka on Kubernetes (Strimzi) using MicroProfile Reactive Messaging.
Kafka cluster (on OpenShift)
First you need a Kafka cluster on your OpenShift.
Create a namespace first:
oc new-project kafka-quickstart
Then you will need Strimzi Kafka CLI by running the following command (you will need Python3 and pip):
sudo pip install strimzi-kafka-cli
See here for other details about Strimzi Kafka CLI.
After installing Strimzi Kafka CLI run the following command to install the operator on
kfk operator --install -n kafka-quickstart
When the operator is ready to serve, run the following command in order to create a Kafka cluster:
kfk clusters --create --cluster my-cluster -n kafka-quickstart
vim interface will pop-up.
If you like you can change the broker and zookeeper replicas to 1 but I suggest you to leave them as is if your Kubernetes cluster have enough resources.
Save the cluster configuration file and respond
Yes to make Strimzi CLI apply the changes.
Wait for the 3 broker and 3 zookeeper pods running in ready state in your cluster:
oc get pods -n kafka-quickstart -w
When all pods are ready, create your
prices topic to be used by the application:
kfk topics --create --topic prices --partitions 10 --replication-factor 2 -c my-cluster -n kafka-quickstart
Check your topic is created successfully by describing it natively:
kfk topics --describe --topic prices -c my-cluster -n kafka-quickstart --native
Deploy the application
The application can be deployed to OpenShift using:
./mvnw clean package -DskipTests
This will take a while since the s2i build will run before the deployment.
Be sure the application's pod is running in ready state in the end.
Run the following command to get the URL of the
echo http://$(oc get routes -n kafka-quickstart -o json | jq -r '.items.spec.host')/prices.html
Copy the URL to your browser, and you should see a fluctuating price.
In addition to the
prices.html page, the application is composed by 3 components:
We generate (random) prices in
These prices are written in
prices Kafka topic that we recently created.
PriceConverter reads from the prices Kafka topic and apply some magic conversion to the price.
The result is sent to an in-memory stream consumed by a JAX-RS resource
The data is sent to a browser using server-sent events.
The interaction with Kafka is managed by MicroProfile Reactive Messaging. The configuration is located in the application configuration.
Running and deploying in native
You can compile the application into a native binary using:
mvn clean install -Pnative
or deploy with:
./mvnw clean package -Pnative -DskipTests
This demo is based on the following resources:
Visit the following link to clone this demo: