Serverless computing is transforming how we build scalable applications. It abstracts away infrastructure management, allowing developers to focus on code and business logic, not provisioning servers.

While Java has traditionally been associated with monolithic apps or microservices, it’s perfectly suited for serverless architectures — especially with the latest optimizations in JVM startup times, GraalVM, and function-as-a-service (FaaS) platforms.

In this guide, you’ll learn how to write, deploy, and optimize serverless functions in Java across AWS Lambda, Azure Functions, and Google Cloud Functions.

Why Use Java for Serverless?

Java brings several advantages to serverless computing:

  • Strong typing and IDE support
  • Mature ecosystem of libraries
  • Efficient multi-threading and concurrency
  • Easy testing and tooling
  • Framework support (Spring Cloud Function, Micronaut, Quarkus)

However, Java’s traditionally longer cold start times can be a concern. We’ll tackle how to minimize that too.

Serverless Concepts Recap

A serverless function:

  • Is event-driven
  • Has no persistent server
  • Scales automatically
  • Runs in isolated environments
  • Should be stateless

Supported triggers include:

  • HTTP requests
  • Message queues (SQS, Pub/Sub)
  • File uploads (S3, Blob)
  • Scheduled events (cron)

Writing a Java Function for AWS Lambda

To get started with AWS Lambda:

  1. Add the Maven dependency:
<dependency>
<groupId>com.amazonaws</groupId>
<artifactId>aws-lambda-java-core</artifactId>
<version>1.2.1</version>
</dependency>
  1. Implement the RequestHandler interface:
public class HelloLambda implements RequestHandler<Map<String, String>, String> {
@Override
public String handleRequest(Map<String, String> input, Context context) {
return "Hello " + input.get("name");
}
}
  1. Package with Maven:
mvn clean package shade:shade
  1. Upload the jar to AWS Lambda with a runtime of java11 or java17.

Cold Start Optimization Strategies

To reduce latency and cold start impact:

  • Use lightweight frameworks like Micronaut, Quarkus, or Spring Cloud Function
  • Keep your deployment small (< 10MB)
  • Avoid excessive static initializers
  • Prefer GraalVM native images (Quarkus supports this out of the box)

Java Function with Spring Cloud Function

Spring Cloud Function lets you write a single function and deploy it to multiple platforms.

@Bean
public Function<String, String> uppercase() {
return input -> input.toUpperCase();
}

Deploy it to AWS Lambda or Azure Functions with appropriate adapters.

Add the dependency:

<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-function-adapter-aws</artifactId>
</dependency>

Azure Functions with Java

  1. Install the Azure Functions Core Tools and Java SDK.
  2. Use the Maven plugin to bootstrap:
mvn archetype:generate \
-DgroupId=com.example \
-DartifactId=azure-functions-java \
-DarchetypeGroupId=com.microsoft.azure \
-DarchetypeArtifactId=azure-functions-archetype
  1. Example HTTP trigger:
@FunctionName("helloAzure")
public HttpResponseMessage run(
@HttpTrigger(name = "req", methods = {HttpMethod.GET}) HttpRequestMessage<Optional<String>> request,
ExecutionContext context) {

    String name = request.getQueryParameters().get("name");
    return request.createResponseBuilder(HttpStatus.OK).body("Hello " + name).build();
}

Google Cloud Functions with Java

  1. Install the Google Cloud SDK
  2. Write a function that implements HttpFunction:
public class HelloHttp implements HttpFunction {
@Override
public void service(HttpRequest request, HttpResponse response) throws IOException {
response.getWriter().write("Hello from GCP!");
}
}
  1. Deploy with:
gcloud functions deploy helloFunction \
--entry-point com.example.HelloHttp \
--runtime java11 \
--trigger-http \
--allow-unauthenticated

Logging and Monitoring

Use platform-native monitoring tools:

  • AWS CloudWatch Logs
  • Azure Application Insights
  • GCP Cloud Logging

Add structured logging to your handlers for better observability.

context.getLogger().log("Processing request for user: " + name);

Best Practices

  • Keep functions short and focused
  • Externalize configuration (env vars, secrets manager)
  • Use dependency injection for testability
  • Handle exceptions gracefully and return appropriate status codes
  • Monitor cold start latency and optimize memory allocation

Conclusion

Java is a powerful, production-ready option for building scalable serverless applications. With lightweight runtimes, native image support, and modern frameworks, you can deploy Java functions with fast startup, minimal cost, and excellent developer experience.

Whether you’re building microservices, event pipelines, or automation scripts — serverless Java is ready for the job.