Kafka Clients Quarkus Edition

🚀 ✨ 🚨 QUARKUS EDITION 🚨 ✨ 🚀

This repo is a fork of the original one based in Spring Boot but refactored to be a full-compliant Quarkus application.

This repo is also the base for the following blog posts:

• Lessons learned migrating Spring Boot to Quarkus
• Integrating Quarkus and Apicurio Service Registry

The following components were refactored from Spring Boot to Quarkus Extensions:

Spring Boot Dependency	Quarkus Extension
spring-boot-starter-web	REST Services
spring-boot-starter-actuator	Microprofile Health
springdoc-openapi-ui	OpenAPI and Swagger UI
spring-kafka	Kafka with Reactive Messaging
avro	Kafka, Schema Registry and Avro
apicurio-registry-utils-serde	Apicurio Registry

This new version is really fast (less than 2 seconds) ... like a 🚀

Mar 29, 2023 2:41:06 PM io.quarkus.bootstrap.runner.Timing printStartupTime
INFO: kafka-clients-quarkus-sample 2.16.5-SNAPSHOT on JVM (powered by Quarkus 2.16.5.Final) started in 2.783s. Listening on: http://0.0.0.0:8080

But in 'native' mode, then the applications is a high-fast 🚀 starting in a few milliseconds.

2023-03-29 14:56:28,357 INFO [io.quarkus] (main) kafka-clients-quarkus-sample 2.16.5-SNAPSHOT native (powered by Quarkus 2.16.5.Final) started in 0.048s. Listening on: http://0.0.0.0:8080

🚀 ✨ 🚨 QUARKUS EDITION 🚨 ✨ 🚀

This sample project demonstrates how to use Kafka Clients and SmallRye Reactive Messaging on Quarkus to send and consume messages from an Apache Kafka cluster. The Apache Kafka cluster is operated by Strimzi operator deployed on Kubernetes or OpenShift Platform. These messages will be validated by a Schema Registry or Service Registry operated by Apicurio operator.

Apache Kafka is an open-sourced distributed event streaming platform for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.

Service Registry is a datastore for sharing standard event schemas and API designs across API and event-driven architectures. You can use Service Registry to decouple the structure of your data from your client applications, and to share and manage your data types and API descriptions at runtime using a REST interface.

The example includes a simple REST API with the following operations:

• Send messages to a Topic
• Consume messages from a Topic

To deploy this application into a Kubernetes/OpenShift environment, we use the amazing JKube.

This application deployed in OpenShift looks like this:

Environment

This project requires a Kubernetes or OpenShift platform available. If you do not have one, you could use one of the following resources to deploy locally a Kubernetes or OpenShift Cluster:

• Minikube - Running Kubernetes Locally
• Red Hat CodeReady Containers - OpenShift 4 on your Laptop

This repo was tested with the following latest versions of Red Hat CodeReady Containers and Minikube:

❯ minikube version
minikube version: v1.29.0
commit: ddac20b4b34a9c8c857fc602203b6ba2679794d3
❯ crc version
CRC version: 2.19.0+a71226
OpenShift version: 4.12.13
Podman version: 4.4.4

Note: Whatever the platform you are using (Kubernetes or OpenShift), you could use the Kubernetes CLI (kubectl) or OpenShift CLI (oc) to execute the commands described in this repo. To reduce the length of this document, the commands displayed will use the Kubernetes CLI. When a specific command is only valid for Kubernetes or OpenShift it will be identified.

To deploy the resources, we will create a new amq-streams-demo namespace in the cluster in the case of Kubernetes:

kubectl create namespace amq-streams-demo

If you are using OpenShift, then we will create a project:

oc new-project amq-streams-demo

Note: All the commands should be executed in this namespace. You could permanently save the namespace for all subsequent kubectl commands in that context.

In Kubernetes:

kubectl config set-context --current --namespace=amq-streams-demo

In OpenShift:

oc project amq-streams-demo

Start Minikube

To start up your local Kubernetes cluster:

❯ minikube start
❯ minikube addons enable ingress
❯ minikube addons enable registry
❯ minikube addons enable olm --images "UpstreamCommunityOperators=operator-framework/upstream-community-operators:latest"

Start Red Hat CodeReady Containers

To start up your OpenShift Local cluster:

❯ crc setup
❯ crc start -p /PATH/TO/your-pull-secret-file.json

You could promote developer user as cluster-admin with the following command:

❯ oc adm policy add-cluster-role-to-user cluster-admin developer
clusterrole.rbac.authorization.k8s.io/cluster-admin added: "developer"

Deploying 🚀 quickly 🏃 with Helm Charts 🚀

If you want to move fast and deploy all this repository, you have a set of Helm Charts to do it easily without executing a large set of commands. Follow the instructions here

Deploying Strimzi and Apicurio Operators

NOTE: Only cluster-admin users could deploy Kubernetes Operators. This section must be executed with one of them.

To deploy the Strimzi and Apicurio Operators only to inspect our namespace, we need to use an OperatorGroup. An OperatorGroup is an OLM resource that provides multitenant configuration to OLM-installed Operators. For more information about this object, please review the official documentation here.

❯ kubectl apply -f src/main/olm/operator-group.yml
operatorgroup.operators.coreos.com/amq-streams-demo-og created

Now we are ready to deploy the Strimzi and Apicurio Operators:

For Kubernetes use the following subscriptions:

❯ kubectl apply -f src/main/strimzi/operator/subscription-k8s.yml
subscription.operators.coreos.com/strimzi-kafka-operator created
❯ kubectl apply -f src/main/apicurio/operator/subscription-k8s.yml
subscription.operators.coreos.com/apicurio-registry created

For OpenShift use the following subscriptions:

❯ oc apply -f src/main/strimzi/operator/subscription.yml
subscription.operators.coreos.com/strimzi-kafka-operator created
❯ oc apply -f src/main/apicurio/operator/subscription.yml
subscription.operators.coreos.com/apicurio-registry created

You could check that operators are successfully registered with the following command:

❯ kubectl get csv
NAME                                             DISPLAY                      VERSION              REPLACES                           PHASE
apicurio-registry-operator.v1.0.0-v2.0.0.final   Apicurio Registry Operator   1.0.0-v2.0.0.final                                      Succeeded
strimzi-cluster-operator.v0.34.0                 Strimzi                      0.34.0               strimzi-cluster-operator.v0.33.2   Succeeded

or verify the pods are running (in case of minikube add -n operators to the command):

❯ kubectl get pod
NAME                                                READY   STATUS    RESTARTS   AGE
apicurio-registry-operator-85cb6db7d5-2d7lp         1/1     Running   0          50m
strimzi-cluster-operator-v0.28.0-575c7494c5-x2prm   1/1     Running   0          50m

For more information about how to install Operators using the CLI command, please review this article

Deploying Kafka

src/main/strimzi folder includes a set of custom resource definitions to deploy a Kafka Cluster and some Kafka Topics using the Strimzi Operators.

To deploy the Kafka Cluster:

❯ kubectl apply -f src/main/strimzi/kafka/kafka.yml
kafka.kafka.strimzi.io/my-kafka created

If you want to deploy a Kafka Cluster with HA capabilities, there is a definition in kafka-ha.yml file.

To deploy the Kafka Topics:

❯ kubectl apply -f src/main/strimzi/topics/kafkatopic-messages.yml
kafkatopic.kafka.strimzi.io/messages created

If you want to use a Kafka Topic with HA capabilities, there is a definition in kafkatopic-messages-ha.yml file.

There is a set of different users to connect to Kafka Cluster. We will deploy here to be used later.

❯ kubectl apply -f src/main/strimzi/users/
kafkauser.kafka.strimzi.io/application created
kafkauser.kafka.strimzi.io/service-registry-scram created
kafkauser.kafka.strimzi.io/service-registry-tls created

After some minutes Kafka Cluster will be deployed:

❯ kubectl get pod
apicurio-registry-operator-85cb6db7d5-2d7lp         1/1     Running   0          55m
my-kafka-entity-operator-5779cb85cf-6zwrs           3/3     Running   0          59s
my-kafka-kafka-0                                    1/1     Running   0          2m7s
my-kafka-zookeeper-0                                1/1     Running   0          3m39s
strimzi-cluster-operator-v0.34.0-8488b4f766-jtzjd   1/1     Running   0          55m

Service Registry

Service Registry needs a set of Kafka Topics to store schemas and metadata of them. We need to execute the following commands to create the KafkaTopics and to deploy an instance of Service Registry:

❯ kubectl apply -f src/main/apicurio/topics/
kafkatopic.kafka.strimzi.io/kafkasql-journal created
❯ kubectl apply -f src/main/apicurio/service-registry.yml
apicurioregistry.apicur.io/service-registry created

A new Deployment/DeploymentConfig is created with the prefix service-registry-deployment- and a new route with the prefix service-registry-ingress-. We must inspect it to get the route created to expose the Service Registry API.

In Kubernetes, we will use an ingress entry based with NodePort. To get the ingress entry:

❯ kubectl get deployment | grep service-registry-deployment
service-registry-deployment
❯ kubectl expose deployment service-registry-deployment --type=NodePort --port=8080
service/service-registry-deployment exposed
❯ kubectl get service/service-registry-deployment
NAME                          TYPE       CLUSTER-IP       EXTERNAL-IP   PORT(S)          AGE
service-registry-deployment   NodePort   10.110.228.232   <none>        8080:30957/TCP   12s 
❯ minikube service service-registry-deployment --url -n amq-streams-demo
http://192.168.50.174:30957

In OpenShift, we only need to check the host attribute from the OpenShift Route:

❯ oc get route
NAME                             HOST/PORT                                                           PATH   SERVICES                       PORT    TERMINATION   WILDCARD
service-registry-ingress-pqgfv   service-registry.amq-streams-demo.router-default.apps-crc.testing   /      service-registry-service       <all>                 None

While few minutes until your Service Registry has deployed.

The Service Registry Web Console and API endpoints will be available from:

• Web Console: http://<KUBERNETES_OPENSHIFT_SR_ROUTE_SERVICE_HOST>/ui/
• API REST: http://KUBERNETES_OPENSHIFT_SR_ROUTE_SERVICE_HOST/apis/registry/v2

Set up the apicurio.registry.url property in the pom.xml file the Service Registry url before to publish the schemas used by this application:

oc get route -l app=service-registry -o jsonpath='{.items[0].spec.host}'

To register the schemas in Service Registry running in Kubernetes:

./mvnw clean generate-sources -Papicurio \
  -Dapicurio.registry.url=$(minikube service service-registry-deployment --url -n amq-streams-demo)/apis/registry/v2

To register the schemas in Service Registry running in OpenShift:

./mvnw clean generate-sources -Papicurio \
  -Dapicurio.registry.url=http://$(oc get route -l app=service-registry -o jsonpath='{.items[0].spec.host}')/apis/registry/v2

The next screenshot shows the schemas registered in the Web Console:

Build and Deploy

Before we build the application we need to set up some values in src/main/resources/application.properties file.

Review and set up the right values from your Kafka Cluster

• Kafka Bootstrap Servers: Kafka brokers are defined by a Kubernetes or OpenShift service created by Strimzi when the Kafka cluster is deployed. This service, called cluster-name-kafka-bootstrap exposes 9092 port for plain traffic and 9093 for encrypted traffic.

app.kafka.bootstrap-servers = my-kafka-kafka-bootstrap:9092

• Kafka User Credentials: Kafka Cluster requires authentication, we need to set up the Kafka User credentials in our application (app.kafka.user.* properties in application.properties file). Each KafkaUser has its own secret to store the password. This secret must be checked to extract the password for our user.

To extract the password of the KafkaUser and declare as Environment Variable:

export KAFKA_USER_PASSWORD=$(kubectl get secret application -o jsonpath='{.data.password}' | base64 -d)

It is a best practice use directly the secret as variable in our deployment in Kubernetes or OpenShift. We could do it declaring the variable in the container spec as:

spec:
  template:
    spec:
      containers:
        - env:
          - name: KAFKA_USER_PASSWORD
            valueFrom:
              secretKeyRef:
                key: password
                name: application

There is a deployment definition in deployment.yml file. This file will be used by JKube to deploy our application in Kubernetes or OpenShift.

• Service Registry API Endpoint: Avro SerDe classes need to communicate with the Service Registry API to check and validate the schemas.

apicurio.registry.url = http://service-registry-service:8080/apis/registry/v2

To build the application:

./mvnw clean package

To run locally:

❯ export KAFKA_USER_PASSWORD=$(kubectl get secret application -o jsonpath='{.data.password}' | base64 -d)
❯ ./mvnw compile quarkus:dev

Or you can deploy into Kubernetes or OpenShift platform using Eclipse JKube Maven Plug-ins:

To deploy the application using the Kubernetes Maven Plug-In:

❯ eval $(minikube docker-env)
❯ kubectl create -f src/main/k8s/role.yml
❯ ./mvnw package k8s:resource k8s:build k8s:apply -Pkubernetes

If you want to deploy the native version of this project:

❯ eval $(minikube docker-env)
❯ kubectl create -f src/main/k8s/role.yml
❯ ./mvnw package k8s:resource k8s:build k8s:apply -Pnative,kubernetes -Dquarkus.native.container-build=true

To deploy the application using the OpenShift Maven Plug-In (only valid for OpenShift Platform):

./mvnw package oc:resource oc:build oc:apply -Popenshift

If you want to deploy the native version of this project:

./mvnw package oc:resource oc:build oc:apply -Pnative,openshift -Dquarkus.native.container-build=true

REST API

REST API is available from a Swagger UI at:

http://<KUBERNETES_OPENSHIFT_ROUTE_SERVICE_HOST>/swagger-ui

KUBERNETES_OPENSHIFT_ROUTE_SERVICE_HOST will be the route create on Kubernetes or OpenShift to expose outside the service.

To get the route the following command in OpenShift give you the host:

❯ oc get route kafka-clients-quarkus-sample -o jsonpath='{.spec.host}'

There are two groups to manage a topic from a Kafka Cluster.

• Producer: Send messageDTOS to a topic
• Consumer: Consume messageDTOS from a topic

Producer REST API

Sample REST API to send messages to a Kafka Topic.

• topicName: Topic Name
• messageDTO: Message content based in a custom messageDTO:

Model:

MessageDTO {
  key (integer, optional): Key to identify this message,
  timestamp (string, optional, read only): Timestamp,
  content (string): Content,
  partition (integer, optional, read only): Partition number,
  offset (integer, optional, read only): Offset in the partition
}

Simple sample producer command in minikube:

❯ curl $(minikube ip):$(kubectl get svc kafka-clients-quarkus-sample -o jsonpath='{.spec.ports[].nodePort}')/producer/kafka/messages \
-H "Content-Type:application/json" -d '{"content": "Simple message from Minikube"}' | jq
{
  "content": "Simple message from Minikube",
  "offset": 3,
  "partition": 0,
  "timestamp": 1649231563778
}

The same for OpenShift:

❯ curl -X POST http://$(oc get route kafka-clients-quarkus-sample -o jsonpath='{.spec.host}')/producer/kafka/messages \
-H "Content-Type:application/json" -d '{"content": "Simple message"}' | jq
{
  "content": "Simple message",
  "offset": 3,
  "partition": 0,
  "timestamp": 1581087543362
}

Consumer REST API

Sample REST API to consume messages from a Kafka Topic. Parameters:

• topicName: Topic Name (Required)
• partition: Number of the partition to consume (Optional)
• commit: Commit messaged consumed. Values: true|false

Simple Sample consumer command in minikube:

❯ curl $(minikube ip):$(kubectl get svc kafka-clients-quarkus-sample -o jsonpath='{.spec.ports[].nodePort}')"/consumer/kafka/messages?commit=true&partition=0" | jq
{
  "messages":[
    {
      "content": "Simple message from Minikube",
      "offset": 0,
      "partition": 0,
      "timestamp": 1649231526214
    },
    ...
    {
      "content": "Simple message from Minikube",
      "offset": 3,
      "partition": 0,
      "timestamp": 1649231563778
    }
  ]
}

The same in OpenShift:

❯ curl -v "http://$(oc get route kafka-clients-quarkus-sample -o jsonpath='{.spec.host}')/consumer/kafka/messages?commit=true&partition=0" | jq
{
  "messages": [
    {
      "content": "Simple message",
      "offset": 0,
      "partition": 0,
      "timestamp": 1581087539350
    },
    ...
    {
      "content": "Simple message",
      "offset": 3,
      "partition": 0,
      "timestamp": 1581087584266
    }
  ]
}

That's all folks! You have been deployed a full stack of components to produce and consume checked and valid messages using a schema declared. Congratulations!.

Main References

• Strimzi
• Apicurio
• OperatorHub - Strimzi
• OperatorHub - Apicurio Registry
• Quarkus - Building applications with Maven
• Quarkus - Writing JSON REST Services
• Quarkus - Using OpenAPI and Swagger UI
• Quarkus - Contexts and Dependency Injection
• Quarkus - Using Apache Kafka with Reactive Messaging
• Quarkus - How to Use Kafka, Schema Registry and Avro with Quarkus
• Quarkus - Configuring your application

Bonus Track - Monitoring Kafka Cluster with Kafka-UI

Kafka-UI is a versatile, fast and lightweight web UI for managing Apache Kafka® clusters. It is very easy to use it and this bonus track describes how to install in our sample and review the status of the Kafka cluster and Service Registry

This example will use the Helm Chart to deploy our local Kafka-UI instance, basically following the guidance from the documentation.

The first step is to install the Helm repo of this tool:

helm repo add kafka-ui https://provectus.github.io/kafka-ui

There is multiple ways to configure Kafka-UI but in our case we will use a Helm Chart Value file for the most general properties. This file will be used with the Helm CLI.

That file will use a ConfigMap and Secret to manage the Kafka and Service Registry connection details.

The ConfigMap will include the main properties to connect to the Kafka Cluster and Service Registry. This command will create it:

kubectl create configmap kafka-ui-configmap \
  --from-literal=KAFKA_CLUSTERS_0_NAME=my-cluster \
  --from-literal=KAFKA_CLUSTERS_0_BOOTSTRAPSERVERS=my-kafka-kafka-bootstrap.amq-streams-demo.svc:9092 \
  --from-literal=KAFKA_CLUSTERS_0_SCHEMAREGISTRY=http://service-registry-service:8080/apis/ccompat/v6

The Secret will manage the credentials to connect to the Kafka cluster, using the superuser defined for that activity:

kubectl create secret generic kafka-ui-sasl-jaas-config-secret \
  --from-literal=KAFKA_CLUSTERS_0_PROPERTIES_SECURITY_PROTOCOL=SASL_PLAINTEXT \
  --from-literal=KAFKA_CLUSTERS_0_PROPERTIES_SASL_MECHANISM=SCRAM-SHA-512 \
  --from-literal=KAFKA_CLUSTERS_0_PROPERTIES_SASL_JAAS_CONFIG="org.apache.kafka.common.security.scram.ScramLoginModule required username='admin' password='$(kubectl get secret admin -o jsonpath='{.data.password}' | base64 -d)';"

For further details, please review the documentation.

Finally, to deploy our instance, execute this command:

helm upgrade --install kafka-ui kafka-ui/kafka-ui -f src/main/kafka-ui/values.yaml --history-max 2

To access to that instance, basically check the ingress or route create for that:

oc get ingress kafka-ui

The next screenshot shows the dashboard of our topic: