Faster and cheaper on AWS Lambda with Java

By Amin Nasiri

Table of Contents


The AWS Lambda is a popular platform for serverless development, and as a Java developer, I like to be able to use this platform, but there are some essential points that we should take care of

  • Cost of serverless functions would be expensive on the JVM platform of AWS Lambda.
  • The Cold start on AWS Lambda can be a real issue on the JVM platform of AWS Lambda.
  • Maximize Efficiency in AWS Lambda for each request is a matter that can not be very well with the JVM Platform.

I am going to show how to address them by Java on this demo application.

There are two primary purposes of this article.

  • How to use AWS service, e.g. DynamoDB by Quarkus framework.
  • Having the best performance on AWS Lambda and make a minimum cost.

The demo application

This repository contains an example of a Java application developed by JDK 11 & Quarkus, which is a simple AWS Lambda function. This simple function will accept a fruit name in a JSON format(input) and return a type of fruit.

  "name": "Apple"

The type of fruit will be.

  • Spring Season Fruit
  • Summer Season Fruit
  • Fall Season Fruit
  • Winter Season Fruit



How does the demo application work?

This demo is a simple Java application, and it will fetch the requested Fruit information, extract the type of fruit, and return it. How simple is that?!! <br/>{=html}


How can we create a Quarkus base Java application?

Quarkus has a lovely guideline to use, and the AWS Lambda project is not an exception; please follow this one on Quarkus website. In a nutshell, we can create it with a Maven command.

mvn archetype:generate \
       -DarchetypeGroupId=com.thinksky \
       -DarchetypeArtifactId=aws-lambda-handler-qaurkus \

It will generate an application using AWS Java SDK. The Quarkus framework has extensions for DynamoDB, S3, SNS and SQS and more, and I would like to use AWS Java SDK V2. So the project pom file needs to have some modification, and please follow this guideline to update it.

The project has Lambda, a dependency inside of the pom file.


And I need to add a dependency to use AWS DynamoDB to be able to connect to DynamoDB.






I will use apache client on the setting of the application and need to add apache-client.


What does Quarkus do to write a simple Java Application on AWS Lambda?

A regular AWS Lambda Java project will be a simple Java project, but Quarkus will bring Dependency Injection inside a Java project.

public class FruitService extends AbstractService {

    DynamoDbClient dynamoDB;

    public List<Fruit> findAll() {
        return dynamoDB.scanPaginator(scanRequest()).items().stream()

    public List<Fruit> add(Fruit fruit) {
        return findAll();


DynamoDbClient is a class from AWS Java SDK.v2, and Quarkus will build it and make it available in its Dependency Injection ecosystem. The FruitService is inherited from an abstract class AbstractService and this abstract class will provide basic objects of DynamoDbClient needs, e.g. ScanRequest, PutItemRequest, etc.

Reflection is using in Java frameworks, but it will be a new challenge on GraalVM native-image; please find out more information on reflection in Graalvm The second benefit of Quarkus is @RegisterForReflection annotation on classes, the easiest way to register a class for reflection in GraalVM.

public class Fruit {

    private String name;
    private Season type;

    public Fruit() {

    public Fruit(String name, Season type) { = name;
        this.type = type;
  • point: Quarkus makes much more benefits on using the AWS Lambda platform, and I will describe them in the following articles e.g. having multiple rest endpoints in one AWS Lambda and fit it with API-Gateway.

Deploy the demo application to AWS Lambda

It’s deployment time on AWS, and it will be super easy with Maven and Quarkus framework. But we should have some preparation on AWS before deploy and run our application.

1) Define table of Fruits_TBL in DynamoDB

$ aws dynamodb create-table --table-name Fruits_TBL \
                          --attribute-definitions AttributeName=fruitName,AttributeType=S \
                          AttributeName=fruitType,AttributeType=S \
                          --key-schema AttributeName=fruitName,KeyType=HASH \
                          AttributeName=fruitType,KeyType=RANGE \
                          --provisioned-throughput ReadCapacityUnits=1,WriteCapacityUnits=1

Then insert some items of fruits on the table.

$ aws dynamodb put-item --table-name Fruits_TBL \
        --item file://item.json \
        --return-consumed-capacity TOTAL \
        --return-item-collection-metrics SIZE

the content of item.json

  "fruitName": {
    "S": "Apple"
  "fruitType": {
    "S": "Fall"

Query from Dynamodb to make sure we have items.

$ aws dynamodb query \
     --table-name  Fruits_TBL \ 
     --key-condition-expression "fruitName = :name" \
     --expression-attribute-values '{":name":{"S":"Watermelon"}}'

2) Define a role in IAM to have access to DynamoBD and assign it to our Lambda application.

$ aws iam create-role --role-name fruits_service_role --assume-role-policy-document file://policy.json

and this is json policy.json

  "Version": "2012-10-17",
  "Statement": {
    "Effect": "Allow",
    "Principal": {
      "Service": [
    "Action": "sts:AssumeRole"

and then assign the DynamoDB permission to this role

$ aws iam attach-role-policy --role-name fruits_service_role --policy-arn "arn:aws:iam::aws:policy/AmazonDynamoDBFullAccess"

$ aws iam attach-role-policy --role-name fruits_service_role --policy-arn "arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole"

and might be this permission as well

$ aws iam attach-role-policy --role-name fruits_service_role --policy-arn "arn:aws:iam::aws:policy/AWSLambda_FullAccess"

AWS platform is ready to deploy our application now.

$  mvn clean install

Quarkus framework will take care of creating a JAR artifact file and zip this JAR file, and SAM template of AWS for us, and we can deploy it by sam CLI now. We should use the JVM version this time, and I would like to add minor modifications.

  1. Add a defined role to Lambda to have proper access
  Role: arn:aws:iam::{Your-Account-Number-On-AWS}:role/fruits_service_role
  1. Increase timeout
  Timeout: 120

So SAM template is ready to deploy on AWS Lambda now.

$  sam deploy -t target/sam.jvm.yaml -g

This command will upload the jar file as a zip format to AWS and deploy it as Lambda Function. The next step will be to test it by invoking a request.


Watching performance of the demo application on AWS Lambda + JVM platform

It’s time to run the deployed Lambda function, test it, and see how it performs well.

$ aws lambda invoke response.txt --cli-binary-format raw-in-base64-out --function-name {"FUNCTION_NAME":fruitApp} --payload file://payload.json --log-type Tail --query LogResult --output text | base64 --decode

FUNCTION_NAME will be figuring out with this simple command

$ aws lambda list-functions --query 'Functions[?starts_with(FunctionName, `fruitAppJVM`) == `true`].FunctionName'

fruitAppJVM is the name of Lambda I gave to SAM CLI in the deployment process.

Then we can go to the AWS web console to see the result of invoking the function.

Numbers are talking, and it is a terrifying performance for a simple application. Why?! mostly it’s because of AWS Lambda cold-start features.

What is an AWS Lambda cold start?

When running a Lambda function, it stays active as long as you’re running it. It means that your container stays alive and ready for execution. AWS will drop the container after a period of inactivity (will be too short), and your function becomes inactive or cold. A cold start occurs when a request comes to the idle lambda function; then, will be initialized the application to be able to the server to the request (initialize mode of Java framework).
On the other hand, a worm start happens when there are available lambda containers, for more information see

<br/>{=html} So the cold start is most the main reason we have this terrifying performance, because each time the cold start occurs, AWS will be initialized our Java application, it’s obvious, will take a long time for each request.

What solution do we have for the AWS Lambda cold-start?

There are two approaches to this fundamental issue.

  • Using Provisioned Concurrency It’s not the scope of this article, and please visit Predictable start-up times with Provisioned Concurrency
  • Having better performance on initialize time and response time of the Java application. The main question is how do we can make better performance in our Java application? My answer is to create a native binary executable from our Java application and deploy it on AWS Lambda. Oracle GraalVM possible.

What is GraalVM?

GraalVM is a high-performance JDK distribution designed to accelerate the execution of applications written in Java and other JVM languages along with support for JavaScript, Ruby, Python, and a number of other popular languages. Native Image is a technology to ahead-of-time compile Java code to a standalone executable, called a native image. This executable includes the application classes, classes from its dependencies, runtime library classes, and statically linked native code from JDK. It does not run on the Java VM, but includes necessary components like memory management, thread scheduling, and so on from a different runtime system, called “Substrate VM”.

Build a native binary executable from the Java application

We need to install GraalVM and its Native-Image from this guideline first. After install GraalVM, we can convert a Java application to a native binary executable with GraalVM. Quarkus makes it easy for us, and it has a Maven/Gradle plugin for it, so in a typical Quarkus based application, we will have a profile called native.

$  mvn clean install -Pnative

Maven will build a native binary executable file, and it will be executable base on your local machine if you are on. Windows, this file will be only runnable on Windows machines. But AWS Lambda will deploy on AWS Linux(v1 or v2). This binary file should be runnable on Linux. In this case, the Quarkus framework will cover this requirement by a simple parameter on its plugin.

$  mvn clean install -Pnative \
        -Dquarkus.native.container-build=true \

As mention on the command -Dquarkus.native.builder-image, we can specify what version of GraalVm we want to use to create a native binary file.

AWS Lambda Environment

AWS Lambda has a couple of different deployable environments.

Runtime Amazon Linux Amazon Linux 2 (AL2)

Node.js nodejs12.x nodejs10.x Python python3.7, python3.6 python3.8 Ruby ruby2.5 ruby2.7 Java java java11 (Corretto 11), java8.al2 (Corretto 8) Go go1.x provided.al2 .NET dotnetcore2.1 dotnetcore3.1 Custom provided provided.al2

So previously deployed the Java Application on Lambda on java11 (Corretto 11), and it doesn’t have good performance. We have two options for the pure Linux platform on Lambda now, which are provided and provided.al2.

  • point: provided will use Amazon Linux and provided.al2 will use Amazon Linux 2, so because of long-term support of version 2, I I would like to suggest use version 2.

Deploy built binary executable on AWS Lambda

As we saw, Quarkus will produce two sam templates for us; one is for JVM base Lambda and the second one is the native binary executable. We should use a native one this time, and I would like to have some slight modifications on it as well.

  1. Change to AWS Linux V2
  Runtime: provided.al2
  1. Add the defined role to Lambda to have proper access
  Role: arn:aws:iam::{Your-Account-Number-On-AWS}:role/fruits_service_role
  1. Increase timeout
  Timeout: 30

The final version of the native SAM template will be like this file; it is ready to deploy on AWS.

$ sam deploy -t target/sam.native.yaml -g

This command will upload the binary file as a zip format to AWS and deploy it as Lambda Function exactly like the JVM version, and now we can jump to the exciting part of monitoring performance.

Watching performance of the demo application on AWS Lambda + Custom platform

It’s time to run the deployed Lambda function, test it, and see how it performs well.

$ aws lambda invoke response.txt --cli-binary-format raw-in-base64-out --function-name {"FUNCTION_NAME":fruitApp} --payload file://payload.json --log-type Tail --query LogResult --output text | base64 --decode

FUNCTION_NAME will be figured out with this simple command

$ aws lambda list-functions --query 'Functions[?starts_with(FunctionName, `fruitAppNative`) == `true`].FunctionName'

fruitAppNative is the name of Lambda I gave to SAM CLI in the deployment process.

Then we can go to the AWS web console to see the result of invoking the function. Wow, what great numbers are showing up.

Analyzing the performance numbers of JVM & Native Binary on AWS Lambda

We can analyze and compare both versions of the application on the AWS Lambda platform, and it can be comparable in two categories.

  • Initialize time The first call or invoke of the Lambda function is Initialize time, and it will be almost the most extended duration of invoking an application because our Java application will start from scratch in this phase.

    It is a super big difference between JVM and Binary version, and it means an initial time of the native binary version almost is 8 times faster than the JVM version.


  • Invoke times I invoke the Lambda function nine times after initialized step, and this is the performance result. As we see the result, there is a significant difference in the performance between the JVM version and Native. Binary.



Quarkus framework will help us have clear and structured code on Java application by having some good features like Dependency. Injection, as well, will help us to convert our Java application to a native-binary file with getting the help of GraalVM. The native binary version has a significantly better performance than the JVM version. - The binary uses just 128 MB of ram, and the JVM version uses 512 MB of ram, which it means has saved money on AWS Lambda costs. - AWS Lambda will charge us based on the duration of usage of the Lambda function, which means better performance will make less cost.