# Using Apache Kafka with Schema Registry and Avro

This guide shows how your Quarkus application can use Apache Kafka, Avro serialized records, and connect to a schema registry (such as the Confluent Schema Registry or Apicurio Registry).

If you are not familiar with Kafka and Kafka in Quarkus in particular, consider first going through the Using Apache Kafka with Reactive Messaging guide.

## Prerequisites

To complete this guide, you need:

- Roughly 30 minutes

- An IDE

- JDK 17+ installed with `JAVA_HOME` configured appropriately

- Apache Maven 3.9.9

- Docker and Docker Compose or Podman, and Docker Compose

- Optionally the Quarkus CLI if you want to use it

- Optionally Mandrel or GraalVM installed and configured appropriately if you want to build a native executable (or Docker if you use a native container build)

## Architecture

In this guide we are going to implement a REST resource, namely `MovieResource`, that will consume movie DTOs and put them in a Kafka topic.

Then, we will implement a consumer that will consume and collect messages from the same topic. The collected messages will be then exposed by another resource, `ConsumedMovieResource`, via Server-Sent Events.

The Movies will be serialized and deserialized using Avro. The schema, describing the Movie, is stored in Apicurio Registry. The same concept applies if you are using the Confluent Avro serde and Confluent Schema Registry.

## Solution

We recommend that you follow the instructions in the next sections and create the application step by step. However, you can go right to the completed example.

Clone the Git repository: `git clone https://github.com/quarkusio/quarkus-quickstarts.git`, or download an archive.

The solution is located in the `kafka-avro-schema-quickstart` directory.

## Creating the Maven Project

First, we need a new project. Create a new project with the following command:

CLI

    quarkus create app org.acme:kafka-avro-schema-quickstart \
        --extension='rest-jackson,messaging-kafka,apicurio-registry-avro' \
        --no-code
    cd kafka-avro-schema-quickstart

To create a Gradle project, add the `--gradle` or `--gradle-kotlin-dsl` option.

For more information about how to install and use the Quarkus CLI, see the Quarkus CLI guide.

Maven

    mvn io.quarkus.platform:quarkus-maven-plugin:3.20.2.1:create \
        -DprojectGroupId=org.acme \
        -DprojectArtifactId=kafka-avro-schema-quickstart \
        -Dextensions='rest-jackson,messaging-kafka,apicurio-registry-avro' \
        -DnoCode
    cd kafka-avro-schema-quickstart

To create a Gradle project, add the `-DbuildTool=gradle` or `-DbuildTool=gradle-kotlin-dsl` option.

For Windows users:

- If using cmd, (don’t use backward slash `\` and put everything on the same line)

- If using Powershell, wrap `-D` parameters in double quotes e.g. `"-DprojectArtifactId=kafka-avro-schema-quickstart"`

| If you use Confluent Schema Registry, you don’t need the `quarkus-apicurio-registry-avro` extension. Instead, you need the `quarkus-confluent-registry-avro` extension and a few more dependencies. See Using the Confluent Schema Registry for details.

## Avro schema

Apache Avro is a data serialization system. Data structures are described using schemas. The first thing we need to do is to create a schema describing the `Movie` structure. Create a file called `src/main/avro/movie.avsc` with the schema for our record (Kafka message):

    {
      "namespace": "org.acme.kafka.quarkus",
      "type": "record",
      "name": "Movie",
      "fields": [
        {
          "name": "title",
          "type": "string"
        },
        {
          "name": "year",
          "type": "int"
        }
      ]
    }

If you build the project with:

CLI

    quarkus build

Maven

    ./mvnw install

Gradle

    ./gradlew build

the `movies.avsc` will get compiled to a `Movie.java` file placed in the `target/generated-sources/avsc` directory.

Take a look at the Avro specification to learn more about the Avro syntax and supported types.

| With Quarkus, there’s no need to use a specific Maven plugin to process the Avro schema, this is all done for you by the `quarkus-avro` extension!

If you run the project with:

CLI

    quarkus dev

Maven

    ./mvnw quarkus:dev

Gradle

    ./gradlew --console=plain quarkusDev

the changes you do to the schema file will be automatically applied to the generated Java files.

## The `Movie` producer

Having defined the schema, we can now jump to implementing the `MovieResource`.

Let’s open the `MovieResource`, inject an `Emitter` of `Movie` DTO and implement a `@POST` method that consumes `Movie` and sends it through the `Emitter`:

    package org.acme.kafka;

    import org.acme.kafka.quarkus.Movie;
    import org.eclipse.microprofile.reactive.messaging.Channel;
    import org.eclipse.microprofile.reactive.messaging.Emitter;
    import org.jboss.logging.Logger;

    import jakarta.ws.rs.POST;
    import jakarta.ws.rs.Path;
    import jakarta.ws.rs.core.Response;

    @Path("/movies")
    public class MovieResource {
        private static final Logger LOGGER = Logger.getLogger(MovieResource.class);

        @Channel("movies")
        Emitter<Movie> emitter;

        @POST
        public Response enqueueMovie(Movie movie) {
            LOGGER.infof("Sending movie %s to Kafka", movie.getTitle());
            emitter.send(movie);
            return Response.accepted().build();
        }

    }

Now, we need to map the `movies` channel (the `Emitter` emits to this channel) to a Kafka topic. To achieve this, edit the `application.properties` file, and add the following content:

    # set the connector for the outgoing channel to `smallrye-kafka`
    mp.messaging.outgoing.movies.connector=smallrye-kafka

    # set the topic name for the channel to `movies`
    mp.messaging.outgoing.movies.topic=movies

    # automatically register the schema with the registry, if not present
    mp.messaging.outgoing.movies.apicurio.registry.auto-register=true

| You might have noticed that we didn’t define the `value.serializer`. That’s because Quarkus can autodetect that `io.apicurio.registry.serde.avro.AvroKafkaSerializer` is appropriate here, based on the `@Channel` declaration, structure of the `Movie` type, and presence of the Apicurio Registry libraries. We still have to define the `apicurio.registry.auto-register` property. If you use Confluent Schema Registry, you don’t have to configure `value.serializer` either. It is also detected automatically. The Confluent Schema Registry analogue of `apicurio.registry.auto-register` is called `auto.register.schemas`. It defaults to `true`, so it doesn’t have to be configured in this example. It can be explicitly set to `false` if you want to disable automatic schema registration.

## The `Movie` consumer

So, we can write records into Kafka containing our `Movie` data. That data is serialized using Avro. Now, it’s time to implement a consumer for them.

Let’s create `ConsumedMovieResource` that will consume `Movie` messages from the `movies-from-kafka` channel and will expose it via Server-Sent Events:

    package org.acme.kafka;

    import jakarta.enterprise.context.ApplicationScoped;
    import jakarta.ws.rs.GET;
    import jakarta.ws.rs.Path;
    import jakarta.ws.rs.Produces;
    import jakarta.ws.rs.core.MediaType;

    import org.acme.kafka.quarkus.Movie;
    import org.eclipse.microprofile.reactive.messaging.Channel;
    import org.jboss.resteasy.reactive.RestStreamElementType;

    import io.smallrye.mutiny.Multi;

    @ApplicationScoped
    @Path("/consumed-movies")
    public class ConsumedMovieResource {

        @Channel("movies-from-kafka")
        Multi<Movie> movies;

        @GET
        @Produces(MediaType.SERVER_SENT_EVENTS)
        @RestStreamElementType(MediaType.TEXT_PLAIN)
        public Multi<String> stream() {
            return movies.map(movie -> String.format("'%s' from %s", movie.getTitle(), movie.getYear()));
        }
    }

The last bit of the application’s code is the configuration of the `movies-from-kafka` channel in `application.properties`:

    # set the connector for the incoming channel to `smallrye-kafka`
    mp.messaging.incoming.movies-from-kafka.connector=smallrye-kafka

    # set the topic name for the channel to `movies`
    mp.messaging.incoming.movies-from-kafka.topic=movies

    # disable auto-commit, Reactive Messaging handles it itself
    mp.messaging.incoming.movies-from-kafka.enable.auto.commit=false

    mp.messaging.incoming.movies-from-kafka.auto.offset.reset=earliest

| You might have noticed that we didn’t define the `value.deserializer`. That’s because Quarkus can autodetect that `io.apicurio.registry.serde.avro.AvroKafkaDeserializer` is appropriate here, based on the `@Channel` declaration, structure of the `Movie` type, and presence of the Apicurio Registry libraries. We don’t have to define the `apicurio.registry.use-specific-avro-reader` property either, that is also configured automatically. If you use Confluent Schema Registry, you don’t have to configure `value.deserializer` or `specific.avro.reader` either. They are both detected automatically.

## Running the application

Start the application in dev mode:

CLI

    quarkus dev

Maven

    ./mvnw quarkus:dev

Gradle

    ./gradlew --console=plain quarkusDev

Kafka broker and Apicurio Registry instance are started automatically thanks to Dev Services. See Dev Services for Kafka and Dev Services for Apicurio Registry for more details.

| You might have noticed that we didn’t configure the schema registry URL anywhere. This is because Dev Services for Apicurio Registry configures all Kafka channels in Quarkus Messaging to use the automatically started registry instance. Apicurio Registry, in addition to its native API, also exposes an endpoint that is API-compatible with Confluent Schema Registry. Therefore, this automatic configuration works both for Apicurio Registry serde and Confluent Schema Registry serde. However, note that there’s no Dev Services support for running Confluent Schema Registry itself. If you want to use a running instance of Confluent Schema Registry, configure its URL, together with the URL of a Kafka broker:
    kafka.bootstrap.servers=PLAINTEXT://localhost:9092
    mp.messaging.connector.smallrye-kafka.schema.registry.url=http://localhost:8081

In the second terminal, query the `ConsumedMovieResource` resource with `curl`:

    curl -N http://localhost:8080/consumed-movies

In the third one, post a few movies:

    curl --header "Content-Type: application/json" \
      --request POST \
      --data '{"title":"The Shawshank Redemption","year":1994}' \
      http://localhost:8080/movies

    curl --header "Content-Type: application/json" \
      --request POST \
      --data '{"title":"The Godfather","year":1972}' \
      http://localhost:8080/movies

    curl --header "Content-Type: application/json" \
      --request POST \
      --data '{"title":"The Dark Knight","year":2008}' \
      http://localhost:8080/movies

    curl --header "Content-Type: application/json" \
      --request POST \
      --data '{"title":"12 Angry Men","year":1957}' \
      http://localhost:8080/movies

Observe what is printed in the second terminal. You should see something along the lines of:

    data:'The Shawshank Redemption' from 1994

    data:'The Godfather' from 1972

    data:'The Dark Knight' from 2008

    data:'12 Angry Men' from 1957

## Running in JVM or Native mode

When not running in dev or test mode, you will need to start your own Kafka broker and Apicurio Registry. The easiest way to get them running is to use `docker-compose` to start the appropriate containers.

| If you use Confluent Schema Registry, you already have a Kafka broker and Confluent Schema Registry instance running and configured. You can ignore the `docker-compose` instructions here, as well as the Apicurio Registry configuration.

Create a `docker-compose.yaml` file at the root of the project with the following content:

    version: '2'

    services:

      zookeeper:
        image: quay.io/strimzi/kafka:0.41.0-kafka-3.7.0
        command: [
            "sh", "-c",
            "bin/zookeeper-server-start.sh config/zookeeper.properties"
        ]
        ports:
          - "2181:2181"
        environment:
          LOG_DIR: /tmp/logs

      kafka:
        image: quay.io/strimzi/kafka:0.41.0-kafka-3.7.0
        command: [
            "sh", "-c",
            "bin/kafka-server-start.sh config/server.properties --override listeners=$${KAFKA_LISTENERS} --override advertised.listeners=$${KAFKA_ADVERTISED_LISTENERS} --override zookeeper.connect=$${KAFKA_ZOOKEEPER_CONNECT}"
        ]
        depends_on:
          - zookeeper
        ports:
          - "9092:9092"
        environment:
          LOG_DIR: "/tmp/logs"
          KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://localhost:9092
          KAFKA_LISTENERS: PLAINTEXT://0.0.0.0:9092
          KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181

      schema-registry:
        image: apicurio/apicurio-registry-mem:2.4.2.Final
        ports:
          - 8081:8080
        depends_on:
          - kafka
        environment:
          QUARKUS_PROFILE: prod

Before starting the application, let’s first start the Kafka broker and Apicurio Registry:

    docker-compose up

| To stop the containers, use `docker-compose down`. You can also clean up the containers with `docker-compose rm`

You can build the application with:

CLI

    quarkus build

Maven

    ./mvnw install

Gradle

    ./gradlew build

And run it in JVM mode with:

    java -Dmp.messaging.connector.smallrye-kafka.apicurio.registry.url=http://localhost:8081/apis/registry/v2 -jar target/quarkus-app/quarkus-run.jar

| By default, the application tries to connect to a Kafka broker listening at `localhost:9092`. You can configure the bootstrap server using: `java -Dkafka.bootstrap.servers=... -jar target/quarkus-app/quarkus-run.jar`

Specifying the registry URL on the command line is not very convenient, so you can add a configuration property only for the `prod` profile:

    %prod.mp.messaging.connector.smallrye-kafka.apicurio.registry.url=http://localhost:8081/apis/registry/v2

You can build a native executable with:

CLI

    quarkus build --native

Maven

    ./mvnw install -Dnative

Gradle

    ./gradlew build -Dquarkus.native.enabled=true

and run it with:

    ./target/kafka-avro-schema-quickstart-1.0.0-SNAPSHOT-runner -Dkafka.bootstrap.servers=localhost:9092

## Testing the application

As mentioned above, Dev Services for Kafka and Apicurio Registry automatically start and configure a Kafka broker and Apicurio Registry instance in dev mode and for tests. Hence, we don’t have to set up Kafka and Apicurio Registry ourselves. We can just focus on writing the test.

First, let’s add test dependencies on REST Client and Awaitility to the build file:

pom.xml

    <!-- we'll use Jakarta REST Client for talking to the SSE endpoint -->
    <dependency>
        <groupId>io.quarkus</groupId>
        <artifactId>quarkus-rest-client</artifactId>
        <scope>test</scope>
    </dependency>
    <dependency>
        <groupId>org.awaitility</groupId>
        <artifactId>awaitility</artifactId>
        <scope>test</scope>
    </dependency>

build.gradle

    testImplementation("io.quarkus:quarkus-rest-client")
    testImplementation("org.awaitility:awaitility")

In the test, we will send movies in a loop and check if the `ConsumedMovieResource` returns what we send.

    package org.acme.kafka;

    import io.quarkus.test.common.QuarkusTestResource;
    import io.quarkus.test.common.http.TestHTTPResource;
    import io.quarkus.test.junit.QuarkusTest;
    import io.restassured.http.ContentType;
    import org.hamcrest.Matchers;
    import org.junit.jupiter.api.Test;

    import jakarta.ws.rs.client.Client;
    import jakarta.ws.rs.client.ClientBuilder;
    import jakarta.ws.rs.client.WebTarget;
    import jakarta.ws.rs.sse.SseEventSource;
    import java.net.URI;
    import java.util.List;
    import java.util.concurrent.CopyOnWriteArrayList;
    import java.util.concurrent.ExecutorService;
    import java.util.concurrent.Executors;

    import static io.restassured.RestAssured.given;
    import static java.util.concurrent.TimeUnit.MILLISECONDS;
    import static java.util.concurrent.TimeUnit.SECONDS;
    import static org.awaitility.Awaitility.await;
    import static org.hamcrest.MatcherAssert.assertThat;

    @QuarkusTest
    public class MovieResourceTest {

        @TestHTTPResource("/consumed-movies")
        URI consumedMovies;

        @Test
        public void testHelloEndpoint() throws InterruptedException {
            // create a client for `ConsumedMovieResource` and collect the consumed resources in a list
            Client client = ClientBuilder.newClient();
            WebTarget target = client.target(consumedMovies);

            List<String> received = new CopyOnWriteArrayList<>();

            SseEventSource source = SseEventSource.target(target).build();
            source.register(inboundSseEvent -> received.add(inboundSseEvent.readData()));

            // in a separate thread, feed the `MovieResource`
            ExecutorService movieSender = startSendingMovies();

            source.open();

            // check if, after at most 5 seconds, we have at least 2 items collected, and they are what we expect
            await().atMost(5, SECONDS).until(() -> received.size() >= 2);
            assertThat(received, Matchers.hasItems("'The Shawshank Redemption' from 1994",
                    "'12 Angry Men' from 1957"));
            source.close();

            // shutdown the executor that is feeding the `MovieResource`
            movieSender.shutdownNow();
            movieSender.awaitTermination(5, SECONDS);
        }

        private ExecutorService startSendingMovies() {
            ExecutorService executorService = Executors.newSingleThreadExecutor();
            executorService.execute(() -> {
                while (true) {
                    given()
                            .contentType(ContentType.JSON)
                            .body("{\"title\":\"The Shawshank Redemption\",\"year\":1994}")
                    .when()
                            .post("/movies")
                    .then()
                            .statusCode(202);

                    given()
                            .contentType(ContentType.JSON)
                            .body("{\"title\":\"12 Angry Men\",\"year\":1957}")
                    .when()
                            .post("/movies")
                    .then()
                            .statusCode(202);

                    try {
                        Thread.sleep(200L);
                    } catch (InterruptedException e) {
                        break;
                    }
                }
            });
            return executorService;
        }

    }

| We modified the `MovieResourceTest` that was generated together with the project. This test class has a subclass, `NativeMovieResourceIT`, that runs the same test against the native executable. To run it, execute:

CLI

    quarkus build --native

Maven

    ./mvnw install -Dnative

Gradle

    ./gradlew build -Dquarkus.native.enabled=true

### Manual setup

If we couldn’t use Dev Services and wanted to start a Kafka broker and Apicurio Registry instance manually, we would define a QuarkusTestResourceLifecycleManager.

pom.xml

    <dependency>
        <groupId>io.strimzi</groupId>
        <artifactId>strimzi-test-container</artifactId>
        <version>0.105.0</version>
        <scope>test</scope>
        <exclusions>
            <exclusion>
                <groupId>org.apache.logging.log4j</groupId>
                <artifactId>log4j-core</artifactId>
            </exclusion>
        </exclusions>
    </dependency>

build.gradle

    testImplementation("io.strimzi:strimzi-test-container:0.105.0") {
        exclude group: "org.apache.logging.log4j", module: "log4j-core"
    }

    package org.acme.kafka;

    import java.util.HashMap;
    import java.util.Map;

    import org.testcontainers.containers.GenericContainer;

    import io.quarkus.test.common.QuarkusTestResourceLifecycleManager;
    import io.strimzi.StrimziKafkaContainer;

    public class KafkaAndSchemaRegistryTestResource implements QuarkusTestResourceLifecycleManager {

        private final StrimziKafkaContainer kafka = new StrimziKafkaContainer();

        private GenericContainer<?> registry;

        @Override
        public Map<String, String> start() {
            kafka.start();
            registry = new GenericContainer<>("apicurio/apicurio-registry-mem:2.4.2.Final")
                    .withExposedPorts(8080)
                    .withEnv("QUARKUS_PROFILE", "prod");
            registry.start();
            Map<String, String> properties = new HashMap<>();
            properties.put("mp.messaging.connector.smallrye-kafka.apicurio.registry.url",
                    "http://" + registry.getHost() + ":" + registry.getMappedPort(8080) + "/apis/registry/v2");
            properties.put("kafka.bootstrap.servers", kafka.getBootstrapServers());
            return properties;
        }

        @Override
        public void stop() {
            registry.stop();
            kafka.stop();
        }
    }

    @QuarkusTest
    @QuarkusTestResource(KafkaAndSchemaRegistryTestResource.class)
    public class MovieResourceTest {
        ...
    }

## Using compatible versions of the Apicurio Registry

The `quarkus-apicurio-registry-avro` extension depends on recent versions of Apicurio Registry client, and most versions of Apicurio Registry server and client are backwards compatible. For some you need to make sure that the client used by Serdes is compatible with the server.

For example, with Apicurio Dev Service if you set the image name to use version `2.1.5.Final`:

    quarkus.apicurio-registry.devservices.image-name=quay.io/apicurio/apicurio-registry-mem:2.1.5.Final

You need to make sure that `apicurio-registry-serdes-avro-serde` dependency and the REST client `apicurio-common-rest-client-vertx` dependency are set to compatible versions:

pom.xml

    <dependency>
        <groupId>io.quarkus</groupId>
        <artifactId>quarkus-apicurio-registry-avro</artifactId>
        <exclusions>
            <exclusion>
                <groupId>io.apicurio</groupId>
                <artifactId>apicurio-common-rest-client-vertx</artifactId>
            </exclusion>
            <exclusion>
                <groupId>io.apicurio</groupId>
                <artifactId>apicurio-registry-serdes-avro-serde</artifactId>
            </exclusion>
        </exclusions>
    </dependency>
    <dependency>
        <groupId>io.apicurio</groupId>
        <artifactId>apicurio-registry-client</artifactId>
        <version>2.1.5.Final</version>
    </dependency>
    <dependency>
        <groupId>io.apicurio</groupId>
        <artifactId>apicurio-registry-common</artifactId>
        <version>2.1.5.Final</version>
    </dependency>
    <dependency>
        <groupId>io.apicurio</groupId>
        <artifactId>apicurio-registry-serdes-avro-serde</artifactId>
        <version>2.1.5.Final</version>
        <exclusions>
            <exclusion>
                <groupId>io.apicurio</groupId>
                <artifactId>apicurio-common-rest-client-jdk</artifactId>
            </exclusion>
            <exclusion>
                <groupId>io.apicurio</groupId>
                <artifactId>apicurio-registry-client</artifactId>
            </exclusion>
            <exclusion>
                <groupId>io.apicurio</groupId>
                <artifactId>apicurio-registry-common</artifactId>
            </exclusion>
        </exclusions>
    </dependency>
    <dependency>
        <groupId>io.apicurio</groupId>
        <artifactId>apicurio-common-rest-client-vertx</artifactId>
        <version>0.1.5.Final</version>
    </dependency>

build.gradle

    dependencies {
        implementation(platform("io.quarkus.platform:quarkus-bom:2.12.3.Final"))

        ...

        implementation("io.quarkus:quarkus-apicurio-registry-avro")
        implementation("io.apicurio:apicurio-registry-serdes-avro-serde") {
            exclude group: "io.apicurio", module: "apicurio-common-rest-client-jdk"
            exclude group: "io.apicurio", module: "apicurio-registry-client"
            exclude group: "io.apicurio", module: "apicurio-registry-common"
            version {
                strictly "2.1.5.Final"
            }
        }
        implementation("io.apicurio:apicurio-registry-client") {
            version {
                strictly "2.1.5.Final"
            }
        }
        implementation("io.apicurio:apicurio-registry-common") {
            version {
                strictly "2.1.5.Final"
            }
        }
        implementation("io.apicurio:apicurio-common-rest-client-vertx") {
            version {
                strictly "0.1.5.Final"
            }
        }
    }

Known previous compatible versions for `apicurio-registry-client` and `apicurio-common-rest-client-vertx` are the following

- `apicurio-registry-client` 2.1.5.Final with `apicurio-common-rest-client-vertx` 0.1.5.Final

- `apicurio-registry-client` 2.3.1.Final with `apicurio-common-rest-client-vertx` 0.1.13.Final

## Using the Confluent Schema Registry

If you want to use the Confluent Schema Registry, you need the `quarkus-confluent-registry-avro` extension, instead of the `quarkus-apicurio-registry-avro` extension. Also, you need to add a few dependencies and a custom Maven repository to your `pom.xml` / `build.gradle` file:

pom.xml

    <dependencies>
        ...
        <!-- the extension -->
        <dependency>
            <groupId>io.quarkus</groupId>
            <artifactId>quarkus-confluent-registry-avro</artifactId>
        </dependency>
        <!-- Confluent registry libraries use Jakarta REST client -->
        <dependency>
            <groupId>io.quarkus</groupId>
            <artifactId>quarkus-rest-client</artifactId>
        </dependency>
        <dependency>
            <groupId>io.confluent</groupId>
            <artifactId>kafka-avro-serializer</artifactId>
            <version>7.2.0</version>
            <exclusions>
                <exclusion>
                    <groupId>jakarta.ws.rs</groupId>
                    <artifactId>jakarta.ws.rs-api</artifactId>
                </exclusion>
            </exclusions>
        </dependency>
    </dependencies>

    <repositories>
        <!-- io.confluent:kafka-avro-serializer is only available from this repository: -->
        <repository>
            <id>confluent</id>
            <url>https://packages.confluent.io/maven/</url>
            <snapshots>
                <enabled>false</enabled>
            </snapshots>
        </repository>
    </repositories>

build.gradle

    repositories {
        ...

        maven {
            url "https://packages.confluent.io/maven/"
        }
    }

    dependencies {
        ...

        implementation("io.quarkus:quarkus-confluent-registry-avro")

        // Confluent registry libraries use Jakarta REST client
        implementation("io.quarkus:quarkus-rest-client")

        implementation("io.confluent:kafka-avro-serializer:7.2.0") {
            exclude group: "jakarta.ws.rs", module: "jakarta.ws.rs-api"
        }
    }

In JVM mode, any version of `io.confluent:kafka-avro-serializer` can be used. In native mode, Quarkus supports the following versions: `6.2.x`, `7.0.x`, `7.1.x`, `7.2.x`, `7.3.x`.

For version `7.4.x` and `7.5.x`, due to an issue with the Confluent Schema Serializer, you need to add another dependency:

pom.xml

    <dependency>
        <groupId>com.fasterxml.jackson.dataformat</groupId>
        <artifactId>jackson-dataformat-csv</artifactId>
    </dependency>

build.gradle

    dependencies {
        implementation("com.fasterxml.jackson.dataformat:jackson-dataformat-csv")
    }

For any other versions, the native configuration may need to be adjusted.

## Avro code generation details

In this guide we used the Quarkus code generation mechanism to generate Java files from Avro schema.

Under the hood, the mechanism uses `org.apache.avro:avro-compiler`.

You can use the following configuration properties to alter how it works:

- `avro.codegen.[avsc|avdl|avpr].imports` - a list of files or directories that should be compiled first thus making them importable by subsequently compiled schemas. Note that imported files should not reference each other. All paths should be relative to the `src/[main|test]/avro` directory, or `avro` sub-directory in any source directory configured by the build system. Passed as a comma-separated list.

- `avro.codegen.stringType` - the Java type to use for Avro strings. May be one of `CharSequence`, `String` or `Utf8`. Defaults to `String`

- `avro.codegen.createOptionalGetters` - enables generating the `getOptional…​` methods that return an Optional of the requested type. Defaults to `false`

- `avro.codegen.enableDecimalLogicalType` - determines whether to use Java classes for decimal types, defaults to `false`

- `avro.codegen.createSetters` - determines whether to create setters for the fields of the record. Defaults to `false`

- `avro.codegen.gettersReturnOptional` - enables generating `get…​` methods that return an Optional of the requested type. Defaults to `false`

- `avro.codegen.optionalGettersForNullableFieldsOnly`, works in conjunction with `gettersReturnOptional` option. If it is set, `Optional` getters will be generated only for fields that are nullable. If the field is mandatory, regular getter will be generated. Defaults to `false`

## Further reading

- SmallRye Reactive Messaging Kafka documentation

- How to Use Kafka, Schema Registry and Avro with Quarkus - a blog post on which the guide is based. It gives a good introduction to Avro and the concept of schema registry