Azure Functions Java developer guide

This guide contains detailed information to help you succeed developing Azure Functions using Java.

As a Java developer, if you're new to Azure Functions, consider first reading one of the following articles:

Java function basics

A Java function is a public method, decorated with the annotation @FunctionName. This method defines the entry for a Java function, and must be unique in a particular package. The package can have multiple classes with multiple public methods annotated with @FunctionName. A single package is deployed to a function app in Azure. In Azure, the function app provides the deployment, execution, and management context for your individual Java functions.

Programming model

The concepts of triggers and bindings are fundamental to Azure Functions. Triggers start the execution of your code. Bindings give you a way to pass data to and return data from a function, without having to write custom data access code.

Create Java functions

To make it easier to create Java functions, there are Maven-based tooling and archetypes that use predefined Java templates to help you create projects with a specific function trigger.

Maven-based tooling

The following developer environments have Azure Functions tooling that lets you create Java function projects:

• Visual Studio Code
• Eclipse
• IntelliJ

These articles show you how to create your first functions using your IDE of choice.

Project scaffolding

If you prefer command line development from the Terminal, the simplest way to scaffold Java-based function projects is to use Apache Maven archetypes. The Java Maven archetype for Azure Functions is published under the following groupId:artifactId: com.microsoft.azure:azure-functions-archetype.

The following command generates a new Java function project using this archetype:

mvn archetype:generate \
    -DarchetypeGroupId=com.microsoft.azure \
    -DarchetypeArtifactId=azure-functions-archetype

mvn archetype:generate ^
    -DarchetypeGroupId=com.microsoft.azure ^
    -DarchetypeArtifactId=azure-functions-archetype

To get started using this archetype, see the Java quickstart.

Folder structure

Here's the folder structure of an Azure Functions Java project:

FunctionsProject
 | - src
 | | - main
 | | | - java
 | | | | - FunctionApp
 | | | | | - MyFirstFunction.java
 | | | | | - MySecondFunction.java
 | - target
 | | - azure-functions
 | | | - FunctionApp
 | | | | - FunctionApp.jar
 | | | | - host.json
 | | | | - MyFirstFunction
 | | | | | - function.json
 | | | | - MySecondFunction
 | | | | | - function.json
 | | | | - bin
 | | | | - lib
 | - pom.xml

You can use a shared host.json file to configure the function app. Each function has its own code file (.java) and binding configuration file (function.json).

You can put more than one function in a project. Avoid putting your functions into separate jars. The FunctionApp in the target directory is what gets deployed to your function app in Azure.

Triggers and annotations

Functions are invoked by a trigger, such as an HTTP request, a timer, or an update to data. Your function needs to process that trigger, and any other inputs, to produce one or more outputs.

Use the Java annotations included in the com.microsoft.azure.functions.annotation.* package to bind input and outputs to your methods. For more information, see the Java reference docs.

Example:

public class Function {
    public String echo(@HttpTrigger(name = "req", 
      methods = {HttpMethod.POST},  authLevel = AuthorizationLevel.ANONYMOUS) 
        String req, ExecutionContext context) {
        return String.format(req);
    }
}

Here's the generated corresponding function.json by the azure-functions-maven-plugin:

{
  "scriptFile": "azure-functions-example.jar",
  "entryPoint": "com.example.Function.echo",
  "bindings": [
    {
      "type": "httpTrigger",
      "name": "req",
      "direction": "in",
      "authLevel": "anonymous",
      "methods": [ "GET","POST" ]
    },
    {
      "type": "http",
      "name": "$return",
      "direction": "out"
    }
  ]
}

Java versions

The version of Java on which your app runs in Azure is specified in the pom.xml file. The Maven archetype currently generates a pom.xml for Java 8, which you can change before publishing. The Java version in pom.xml should match the version on which you've locally developed and tested your app.

Supported versions

The following table shows current supported Java versions for each major version of the Functions runtime, by operating system:

Unless you specify a Java version for your deployment, the Maven archetype defaults to Java 8 during deployment to Azure.

Specify the deployment version

You can control the version of Java targeted by the Maven archetype by using the -DjavaVersion parameter. The value of this parameter can be either 8, 11, 17 or 21.

The Maven archetype generates a pom.xml that targets the specified Java version. The following elements in pom.xml indicate the Java version to use:

The following examples show the settings for Java 8 in the relevant sections of the pom.xml file:

Java.version

<properties>
    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    <java.version>1.8</java.version>
    <azure.functions.maven.plugin.version>1.6.0</azure.functions.maven.plugin.version>
    <azure.functions.java.library.version>1.3.1</azure.functions.java.library.version>
    <functionAppName>fabrikam-functions-20200718015742191</functionAppName>
    <stagingDirectory>${project.build.directory}/azure-functions/${functionAppName}</stagingDirectory>
</properties>

JavaVersion

<runtime>
    <!-- runtime os, could be windows, linux or docker-->
    <os>windows</os>
    <javaVersion>8</javaVersion>
    <!-- for docker function, please set the following parameters -->
    <!-- <image>[hub-user/]repo-name[:tag]</image> -->
    <!-- <serverId></serverId> -->
    <!-- <registryUrl></registryUrl>  -->
</runtime>

Specify the deployment OS

Maven also lets you specify the operating system on which your function app runs in Azure. Use the os element to choose the operating system.

The following example shows the operating system setting in the runtime section of the pom.xml file:

<runtime>
    <!-- runtime os, could be windows, linux or docker-->
    <os>windows</os>
    <javaVersion>8</javaVersion>
    <!-- for docker function, please set the following parameters -->
    <!-- <image>[hub-user/]repo-name[:tag]</image> -->
    <!-- <serverId></serverId> -->
    <!-- <registryUrl></registryUrl>  -->
</runtime>

JDK runtime availability and support

Microsoft and Adoptium builds of OpenJDK are provided and supported on Functions for Java 8 (Adoptium), Java 11, 17 and 21 (MSFT). These binaries are provided as a no-cost, multi-platform, production-ready distribution of the OpenJDK for Azure. They contain all the components for building and running Java SE applications.

For local development or testing, you can download the Microsoft build of OpenJDK or Adoptium Temurin binaries for free. Azure support for issues with the JDKs and function apps is available with a qualified support plan.

If you would like to continue using the Zulu for Azure binaries on your Function app, configure your app accordingly. You can continue to use the Azul binaries for your site. However, any security patches or improvements are only available in new versions of the OpenJDK. Because of this, you should eventually remove this configuration so that your apps use the latest available version of Java.

Customize JVM

Functions lets you customize the Java virtual machine (JVM) used to run your Java functions. The following JVM options are used by default:

• -XX:+TieredCompilation
• -XX:TieredStopAtLevel=1
• -noverify
• -Djava.net.preferIPv4Stack=true
• -jar

You can provide other arguments to the JVM by using one of the following application settings, depending on the plan type:

The following sections show you how to add these settings. To learn more about working with application settings, see the Work with application settings section.

Azure portal

In the Azure portal, use the Application Settings tab to add either the languageWorkers__java__arguments or the JAVA_OPTS setting.

Azure CLI

You can use the az functionapp config appsettings set command to add these settings, as shown in the following example for the -Djava.awt.headless=true option:

az functionapp config appsettings set \
    --settings "languageWorkers__java__arguments=-Djava.awt.headless=true" \
    --name <APP_NAME> --resource-group <RESOURCE_GROUP>

az functionapp config appsettings set ^
    --settings "languageWorkers__java__arguments=-Djava.awt.headless=true" ^
    --name <APP_NAME> --resource-group <RESOURCE_GROUP>

az functionapp config appsettings set \
    --settings "JAVA_OPTS=-Djava.awt.headless=true" \
    --name <APP_NAME> --resource-group <RESOURCE_GROUP>

az functionapp config appsettings set ^
    --settings "JAVA_OPTS=-Djava.awt.headless=true" ^
    --name <APP_NAME> --resource-group <RESOURCE_GROUP>

This example enables headless mode. Replace <APP_NAME> with the name of your function app, and <RESOURCE_GROUP> with the resource group.

Third-party libraries

Azure Functions supports the use of third-party libraries. By default, all dependencies specified in your project pom.xml file are automatically bundled during the mvn package goal. For libraries not specified as dependencies in the pom.xml file, place them in a lib directory in the function's root directory. Dependencies placed in the lib directory are added to the system class loader at runtime.

The com.microsoft.azure.functions:azure-functions-java-library dependency is provided on the classpath by default, and doesn't need to be included in the lib directory. Also, azure-functions-java-worker adds dependencies listed here to the classpath.

Data type support

You can use Plain old Java objects (POJOs), types defined in azure-functions-java-library, or primitive data types such as String and Integer to bind to input or output bindings.

POJOs

For converting input data to POJO, azure-functions-java-worker uses the gson library. POJO types used as inputs to functions should be public.

Binary data

Bind binary inputs or outputs to byte[], by setting the dataType field in your function.json to binary:

   @FunctionName("BlobTrigger")
    @StorageAccount("AzureWebJobsStorage")
     public void blobTrigger(
        @BlobTrigger(name = "content", path = "myblob/{fileName}", dataType = "binary") byte[] content,
        @BindingName("fileName") String fileName,
        final ExecutionContext context
    ) {
        context.getLogger().info("Java Blob trigger function processed a blob.\n Name: " + fileName + "\n Size: " + content.length + " Bytes");
    }

If you expect null values, use Optional<T>.

Bindings

Input and output bindings provide a declarative way to connect to data from within your code. A function can have multiple input and output bindings.

Input binding example

package com.example;

import com.microsoft.azure.functions.annotation.*;

public class Function {
    @FunctionName("echo")
    public static String echo(
        @HttpTrigger(name = "req", methods = { HttpMethod.PUT }, authLevel = AuthorizationLevel.ANONYMOUS, route = "items/{id}") String inputReq,
        @TableInput(name = "item", tableName = "items", partitionKey = "Example", rowKey = "{id}", connection = "AzureWebJobsStorage") TestInputData inputData,
        @TableOutput(name = "myOutputTable", tableName = "Person", connection = "AzureWebJobsStorage") OutputBinding<Person> testOutputData
    ) {
        testOutputData.setValue(new Person(httpbody + "Partition", httpbody + "Row", httpbody + "Name"));
        return "Hello, " + inputReq + " and " + inputData.getKey() + ".";
    }

    public static class TestInputData {
        public String getKey() { return this.rowKey; }
        private String rowKey;
    }
    public static class Person {
        public String partitionKey;
        public String rowKey;
        public String name;

        public Person(String p, String r, String n) {
            this.partitionKey = p;
            this.rowKey = r;
            this.name = n;
        }
    }
}

You invoke this function with an HTTP request.

• HTTP request payload is passed as a String for the argument inputReq.
• One entry is retrieved from Table storage, and is passed as TestInputData to the argument inputData.

To receive a batch of inputs, you can bind to String[], POJO[], List<String>, or List<POJO>.

@FunctionName("ProcessIotMessages")
    public void processIotMessages(
        @EventHubTrigger(name = "message", eventHubName = "%AzureWebJobsEventHubPath%", connection = "AzureWebJobsEventHubSender", cardinality = Cardinality.MANY) List<TestEventData> messages,
        final ExecutionContext context)
    {
        context.getLogger().info("Java Event Hub trigger received messages. Batch size: " + messages.size());
    }
    
    public class TestEventData {
    public String id;
}

This function gets triggered whenever there's new data in the configured event hub. Because the cardinality is set to MANY, the function receives a batch of messages from the event hub. EventData from event hub gets converted to TestEventData for the function execution.

Output binding example

You can bind an output binding to the return value by using $return.

package com.example;

import com.microsoft.azure.functions.annotation.*;

public class Function {
    @FunctionName("copy")
    @StorageAccount("AzureWebJobsStorage")
    @BlobOutput(name = "$return", path = "samples-output-java/{name}")
    public static String copy(@BlobTrigger(name = "blob", path = "samples-input-java/{name}") String content) {
        return content;
    }
}

If there are multiple output bindings, use the return value for only one of them.

To send multiple output values, use OutputBinding<T> defined in the azure-functions-java-library package.

@FunctionName("QueueOutputPOJOList")
    public HttpResponseMessage QueueOutputPOJOList(@HttpTrigger(name = "req", methods = { HttpMethod.GET,
            HttpMethod.POST }, authLevel = AuthorizationLevel.ANONYMOUS) HttpRequestMessage<Optional<String>> request,
            @QueueOutput(name = "itemsOut", queueName = "test-output-java-pojo", connection = "AzureWebJobsStorage") OutputBinding<List<TestData>> itemsOut, 
            final ExecutionContext context) {
        context.getLogger().info("Java HTTP trigger processed a request.");
       
        String query = request.getQueryParameters().get("queueMessageId");
        String queueMessageId = request.getBody().orElse(query);
        itemsOut.setValue(new ArrayList<TestData>());
        if (queueMessageId != null) {
            TestData testData1 = new TestData();
            testData1.id = "msg1"+queueMessageId;
            TestData testData2 = new TestData();
            testData2.id = "msg2"+queueMessageId;

            itemsOut.getValue().add(testData1);
            itemsOut.getValue().add(testData2);

            return request.createResponseBuilder(HttpStatus.OK).body("Hello, " + queueMessageId).build();
        } else {
            return request.createResponseBuilder(HttpStatus.INTERNAL_SERVER_ERROR)
                    .body("Did not find expected items in CosmosDB input list").build();
        }
    }

     public static class TestData {
        public String id;
    }

You invoke this function on an HttpRequest object. It writes multiple values to Queue storage.

HttpRequestMessage and HttpResponseMessage

These are defined in azure-functions-java-library. They're helper types to work with HttpTrigger functions.

Metadata

Few triggers send trigger metadata along with input data. You can use annotation @BindingName to bind to trigger metadata.

package com.example;

import java.util.Optional;
import com.microsoft.azure.functions.annotation.*;


public class Function {
    @FunctionName("metadata")
    public static String metadata(
        @HttpTrigger(name = "req", methods = { HttpMethod.GET, HttpMethod.POST }, authLevel = AuthorizationLevel.ANONYMOUS) Optional<String> body,
        @BindingName("name") String queryValue
    ) {
        return body.orElse(queryValue);
    }
}

In the preceding example, the queryValue is bound to the query string parameter name in the HTTP request URL, http://{example.host}/api/metadata?name=test. Here's another example, showing how to bind to Id from queue trigger metadata.

 @FunctionName("QueueTriggerMetadata")
    public void QueueTriggerMetadata(
        @QueueTrigger(name = "message", queueName = "test-input-java-metadata", connection = "AzureWebJobsStorage") String message,@BindingName("Id") String metadataId,
        @QueueOutput(name = "output", queueName = "test-output-java-metadata", connection = "AzureWebJobsStorage") OutputBinding<TestData> output,
        final ExecutionContext context
    ) {
        context.getLogger().info("Java Queue trigger function processed a message: " + message + " with metadaId:" + metadataId );
        TestData testData = new TestData();
        testData.id = metadataId;
        output.setValue(testData);
    }

Execution context

ExecutionContext, defined in the azure-functions-java-library, contains helper methods to communicate with the functions runtime. For more information, see the ExecutionContext reference article.

Logger

Use getLogger, defined in ExecutionContext, to write logs from function code.

Example:

import com.microsoft.azure.functions.*;
import com.microsoft.azure.functions.annotation.*;

public class Function {
    public String echo(@HttpTrigger(name = "req", methods = {HttpMethod.POST}, authLevel = AuthorizationLevel.ANONYMOUS) String req, ExecutionContext context) {
        if (req.isEmpty()) {
            context.getLogger().warning("Empty request body received by function " + context.getFunctionName() + " with invocation " + context.getInvocationId());
        }
        return String.format(req);
    }
}

View logs and trace

You can use the Azure CLI to stream Java stdout and stderr logging, and other application logging.

Here's how to configure your function app to write application logging by using the Azure CLI:

az webapp log config --name functionname --resource-group myResourceGroup --application-logging true

az webapp log config --name functionname --resource-group myResourceGroup --application-logging true

To stream logging output for your function app by using the Azure CLI, open a new command prompt, Bash, or Terminal session, and enter the following command:

az webapp log tail --name webappname --resource-group myResourceGroup

az webapp log tail --name webappname --resource-group myResourceGroup

The az webapp log tail command has options to filter output by using the --provider option.

To download the log files as a single ZIP file by using the Azure CLI, open a new command prompt, Bash, or Terminal session, and enter the following command:

az webapp log download --resource-group resourcegroupname --name functionappname

You must have enabled file system logging in the Azure portal or the Azure CLI before running this command.

Environment variables

In Functions, app settings, such as service connection strings, are exposed as environment variables during execution. You can access these settings by using, System.getenv("AzureWebJobsStorage").

The following example gets the application setting, with the key named myAppSetting:

public class Function {
    public String echo(@HttpTrigger(name = "req", methods = {HttpMethod.POST}, authLevel = AuthorizationLevel.ANONYMOUS) String req, ExecutionContext context) {
        context.getLogger().info("My app setting value: "+ System.getenv("myAppSetting"));
        return String.format(req);
    }
}

Use dependency injection in Java Functions

Azure Functions Java supports the dependency injection (DI) software design pattern, which is a technique to achieve Inversion of Control (IoC) between classes and their dependencies. Java Azure Functions provides a hook to integrate with popular Dependency Injection frameworks in your Functions Apps. Azure Functions Java SPI contains an interface FunctionInstanceInjector. By implementing this interface, you can return an instance of your function class and your functions will be invoked on this instance. This gives frameworks like Spring, Quarkus, Google Guice, Dagger, etc. the ability to create the function instance and register it into their IOC container. This means you can use those Dependency Injection frameworks to manage your functions naturally.

Function instance injector for dependency injection

azure-function-java-spi contains an interface FunctionInstanceInjector

package com.microsoft.azure.functions.spi.inject; 

/** 

 * The instance factory used by DI framework to initialize function instance. 

 * 

 * @since 1.0.0 

 */ 

public interface FunctionInstanceInjector { 

    /** 

     * This method is used by DI framework to initialize the function instance. This method takes in the customer class and returns 

     * an instance create by the DI framework, later customer functions will be invoked on this instance. 

     * @param functionClass the class that contains customer functions 

     * @param <T> customer functions class type 

     * @return the instance that will be invoked on by azure functions java worker 

     * @throws Exception any exception that is thrown by the DI framework during instance creation 

     */ 

    <T> T getInstance(Class<T> functionClass) throws Exception; 

} 

For more examples that use FunctionInstanceInjector to integrate with Dependency injection frameworks refer to this repository.

Next steps

For more information about Azure Functions Java development, see the following resources:

• Best practices for Azure Functions
• Azure Functions developer reference
• Azure Functions triggers and bindings
• Local development and debug with Visual Studio Code, IntelliJ, and Eclipse
• Remote Debug Java functions using Visual Studio Code
• Maven plugin for Azure Functions
• Streamline function creation through the azure-functions:add goal, and prepare a staging directory for ZIP file deployment.