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Building scalable microservices with Java Spring Boot, Confluent Kafka, and AWS ECS CloudFormation

In the ever-evolving world of software development, building scalable and resilient microservices has become essential. Java Spring Boot, Confluent Kafka, and Amazon Web Services (AWS) Elastic Container Service (ECS) are powerful technologies that, when combined, enable you to create a robust and flexible infrastructure for your microservices. In this blog article, we’ll explore how to set up a system that integrates Java Spring Boot with Confluent Kafka on AWS ECS using CloudFormation.

The technology stack

Before we dive into the details, let’s take a closer look at the technologies we’ll be using:

1. Java Spring Boot

Spring Boot is a popular framework for building microservices and creating stand-alone Spring applications. It simplifies the development process and provides a range of features to help you create robust and scalable applications.

2. Confluent Kafka

Kafka is a distributed streaming platform that allows you to build real-time data pipelines and streaming applications. Confluent Kafka is a popular distribution of Kafka that simplifies its deployment and management.


Amazon Elastic Container Service (ECS) is a fully managed container orchestration service. It makes it easy to run, stop, and manage Docker containers on a cluster of Amazon Elastic Compute Cloud (Amazon EC2) instances.

4. AWS CloudFormation

CloudFormation is an AWS service that helps you model and set up your AWS resources. It allows you to define your infrastructure as code, making it easy to provision and manage your resources.

Integration architecture

Confluent Kafka Spring Boot AWS ECS integration

Setting up Java Spring Boot microservices

1. Developing a Spring Boot application

Begin by developing your Java Spring Boot microservices. This could be a simple RESTful service, or a more complex application, depending on your requirements. Ensure that your application is designed to be containerised using Docker, as you will be deploying it to ECS.

2. Containerizing the application

Create a Docker image for your Spring Boot application. You can use tools like Dockerfile to define the image and package your application along with its dependencies.

2.1 Below is a sample Dockerfile to package an application with dependencies

RUN mkdir -p /usr/app/$APPLICATION_NAME 
   USER root
   COPY ./target/*.jar $APPLICATION_NAME
   EXPOSE 8080
   ENTRYPOINT ["java", "", "-jar", $APPLICATION_NAME"] 

3. Pushing the Docker Image to a Container Registry

Once your Docker image is ready, push it to a container registry like Amazon Elastic Container Registry (ECR). ECR provides a secure and scalable container image registry for your applications.

3.1 Build a docker image and push it to ECS

Check ECR account

ECR_REPO=$(aws sts get-caller-identity --query Account --output text)

Docker login

aws ecr get-login-password --region ap-southeast-2 | docker login --username AWS --password-stdin $ECR_REPO

Build Docker Image

docker buildx build --platform linux/amd64 -t ${IMAGE_NAME}

Push Docker Image


Setting up a Confluent Kafka cluster

Using Confluent Kafka, set up a Kafka cluster on AWS or another cloud provider of your choice [Eg: Confluent cloud]. Configure the necessary topics, partitions, and replication factors based on your application’s needs.

Note: As a Confluent Elite Partner, LimePoint excels in assisting clients to establish cloud-based solutions using Confluent Kafka. Reach out to us for specialised guidance.

Deploying on AWS ECS with CloudFormation

Now that you have your Spring Boot microservices and Confluent Kafka cluster set up, it’s time to deploy them on AWS ECS using CloudFormation.

1. Define your infrastructure as code

Create a CloudFormation template that defines your ECS cluster, tasks, services, and any other resources you need. Be sure to specify the necessary parameters, such as the Docker image locations, Kafka broker endpoints, and security settings.

Note: As a Confluent Premier Partner, LimePoint excels in assisting clients to establish cloud-based solutions using Confluent Kafka. Reach out to us for specialised guidance.

2. Deploy the stack

Use the AWS CloudFormation console or the AWS Command Line Interface (CLI) to deploy your CloudFormation stack. This will provision your ECS cluster and deploy your Spring Boot microservices.

Sample CloudFormation stack deployment via AWS CLI

Check the Docker image version on ECR

IMAGE_VERSION=$(aws ecr describe-images --repository-name $ECR-REPO/${STACK_NAME} --query 'sort_by(imageDetails,& imagePushedAt)[-1].imageTags[0]')

Update CloudFormation stack

docker run --rm \
  -v `pwd`:/cwd \    
  -e AWS_ACCESS_KEY_ID -e AWS_SECRET_ACCESS_KEY -e AWS_SESSION_TOKEN \ -e AWS_REGION \ realestate/stackup:1.4.6 $STACK_NAME up \ -t fargate.yml \ -o ImageVersion=$IMAGE_VERSION

3. Monitor and scale

Once your services are up and running, use AWS services like Amazon CloudWatch and AWS Auto Scaling to monitor and scale your microservices based on metrics like CPU usage or message queue backlog.


Integrating Java Spring Boot with Confluent Kafka on AWS ECS using CloudFormation provides a scalable and reliable architecture for building microservices. It allows you to process real-time data efficiently, handle heavy workloads, and adapt to changing demands. By following the steps outlined in this blog, you can build a powerful infrastructure that’s capable of handling modern, data-driven applications.

Discover how we’ve aided our clients in seamlessly integrating AWS ECS, Confluent Kafka, and Java microservices. Connect with us for details

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