Deploy Spring Boot to AWS: Step by Step Guide with Code Examples

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Deploying Spring Boot applications to AWS is a strategic move for businesses looking to leverage cloud computing’s scalability, reliability, and flexibility. AWS provides a robust environment where applications can thrive, adapt, and scale according to demand. With its array of services tailored for deployment, management, and optimization, AWS stands as a premier choice for hosting Spring Boot applications.

This article aims to furnish developers with a comprehensive, step-by-step guide to deploying Spring Boot applications on AWS, complete with practical code examples. Whether you’re new to AWS or looking to refine your deployment strategy, this guide promises to equip you with the knowledge to harness the full potential of your Spring Boot applications in the cloud.

Preparing Your Spring Boot Application for AWS

Before diving into the deployment process, it’s crucial to ensure that your Spring Boot application is primed for the cloud. Preparing your application involves several key steps to ensure compatibility and optimize performance within AWS’s dynamic environment.

Firstly, create a simple Spring Boot application if you haven’t already. Utilize Spring Initializr to bootstrap your project with necessary dependencies. This tool simplifies the setup, allowing you to focus on application logic rather than configuration.

Next, integrate your application with AWS dependencies. Spring Cloud for AWS simplifies cloud-native development, allowing your application to interact seamlessly with AWS services. Add the Spring Cloud AWS dependency to your project’s pom.xml:


Finally, ensure your application is stateless to maximize scalability and resilience in the cloud. Design your application to handle requests independently, without relying on local files or in-memory data. If your application requires persistent data storage, consider leveraging AWS services like Amazon RDS or S3.

By following these steps, your Spring Boot application will be well-equipped for successful deployment to AWS.

AWS Services Overview for Spring Boot Deployment

Deploying a Spring Boot application on AWS involves leveraging various AWS services to optimize scalability, manageability, and operational efficiency. Here�s an overview of key AWS services pertinent to Spring Boot deployment.

AWS Elastic Beanstalk

AWS Elastic Beanstalk simplifies the deployment and scaling of applications and services developed with Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker on familiar servers such as Apache, Nginx, Passenger, and IIS. For Spring Boot applications, Elastic Beanstalk automatically handles the deployment, from capacity provisioning, load balancing, auto-scaling to application health monitoring. Simply upload your code, and Elastic Beanstalk automatically deploys it to the AWS cloud.

Amazon RDS

Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching, and backups. It’s fully managed and supports six commonly used database engines, including PostgreSQL, MySQL, MariaDB, Oracle Database, SQL Server, and Amazon Aurora. Integrating your Spring Boot application with RDS can significantly streamline database management and scaling.

Amazon S3

Amazon Simple Storage Service (Amazon S3) is an object storage service offering scalability, data availability, security, and performance. S3 can store and protect any amount of data for a range of use cases, such as websites, mobile applications, backup and restore, archive, enterprise applications, IoT devices, and big data analytics. Spring Boot applications can leverage S3 for storing application assets, backups, and logs securely and efficiently.

Additional Services

Beyond these core services, AWS offers a plethora of other services such as AWS Lambda for serverless computing, Amazon Simple Notification Service (SNS) for pub/sub messaging, and Amazon Simple Queue Service (SQS) for message queuing. Leveraging these services can further enhance your Spring Boot application’s functionality and scalability.

In summary, AWS provides a comprehensive suite of services that can cater to the diverse needs of Spring Boot applications, from deployment to database management, and from storage solutions to serverless computing. Understanding these services and their integration points with Spring Boot is crucial for deploying robust, scalable, and efficient applications in the AWS cloud.

Step 1: Setting Up AWS Account and Environment

The first step towards deploying your Spring Boot application to AWS is setting up your AWS account and configuring your working environment. This section will guide you through this foundational step.

Creating an AWS Account

If you don’t already have an AWS account, you’ll need to create one by visiting the AWS Management Console and selecting the ‘Create a new AWS account’ option. Follow the on-screen instructions to complete the account setup, including providing your contact information, credit card details, and selecting a support plan.

Installing AWS CLI

The AWS Command Line Interface (CLI) is a powerful tool that enables you to interact with AWS services using commands in your command-line shell. To install the AWS CLI, download the installer from the official AWS CLI website and follow the installation instructions for your operating system. Once installed, configure the CLI with your access key, secret key, and default region using the aws configure command.

aws configure

Enter your AWS Access Key ID, Secret Access Key, and the Default region name when prompted. These credentials are essential for deploying and managing your Spring Boot application on AWS.

Setting Up IAM Roles and Policies

Identity and Access Management (IAM) roles and policies define permissions for accessing AWS services. Create an IAM role with the necessary permissions for your Spring Boot application to interact with AWS services like Elastic Beanstalk, RDS, and S3.

  1. Go to the IAM console.
  2. Choose ‘Roles’ from the navigation pane and click ‘Create role’.
  3. Select ‘AWS service’ as the type of trusted entity and choose the service that requires access to your AWS resources, for example, Elastic Beanstalk.
  4. Attach policies that grant the necessary permissions for the services your application will use.

Setting up your AWS account, installing the AWS CLI, and configuring IAM roles and policies are crucial steps that lay the foundation for deploying your Spring Boot application to AWS. Ensuring these steps are correctly completed will streamline the subsequent deployment process.

Step 2: Deploying Spring Boot Application Using AWS Elastic Beanstalk

Deploying a Spring Boot application to AWS Elastic Beanstalk provides a seamless way to manage application environments, including auto-scaling, load balancing, and health monitoring capabilities.

Elastic Beanstalk supports a variety of standard programming languages and frameworks, making it a versatile choice for developers. For Spring Boot applications, Elastic Beanstalk automates the deployment process, from capacity provisioning, load balancing, auto-scaling to application health monitoring. The process involves packaging the application into a deployable ‘war’ or ‘jar’ file, creating an Elastic Beanstalk environment, and then deploying the application.

Creating Elastic Beanstalk Environment

To set up an Elastic Beanstalk environment for a Spring Boot application, follow these steps:

  1. Log in to the AWS Management Console and navigate to the Elastic Beanstalk dashboard.
  2. Choose ‘Create New Application’ and provide a name and description for your application.
  3. Select ‘Web Server Environment’ and proceed to configure your environment settings. Choose a pre-configured platform compatible with Java applications.
  4. Specify the application version by uploading the packaged ‘war’ or ‘jar’ file of your Spring Boot application.

AWS Elastic Beanstalk will provision an environment with the necessary AWS resources configured to run your Spring Boot application, including an EC2 instance, an autoscaling group, and an Elastic Load Balancer.

Deploying Application and Configuring Environment

After creating your Elastic Beanstalk environment, deploy your Spring Boot application following these steps:

  1. From your application’s Elastic Beanstalk dashboard, choose ‘Upload and Deploy’ to upload the new version of your application. Specify the version label and upload your ‘war’ or ‘jar’ file.
  2. Click ‘Deploy’ to start the deployment process. AWS Elastic Beanstalk automatically deploys the application to the environment’s instances and handles the load balancing and scaling settings based on the predefined configurations.

Configuring Environment Properties

To ensure your Spring Boot application runs smoothly on AWS Elastic Beanstalk, you might need to configure environment properties such as database connection strings, AWS service access keys, and other application-specific settings.

  1. Navigate to your environment’s configuration settings within the Elastic Beanstalk console.
  2. Under the ‘Software’ configuration section, you can specify environment properties. These key-value pairs will be set as environment variables accessible by your Spring Boot application.

By correctly configuring these properties, your Spring Boot application can seamlessly integrate with AWS services and external resources, ensuring a robust and scalable web application environment.

Step 3: Integrating AWS Services with Spring Boot

Integrating AWS services like Amazon RDS (Relational Database Service) and S3 (Simple Storage Service) with your Spring Boot application can significantly enhance its functionality and scalability. In this section, we will walk through how to configure your Spring Boot application to interact with these services, providing practical code examples.

Amazon RDS Integration

To integrate Amazon RDS with your Spring Boot application, you’ll need to configure your data source properties to use the RDS instance. First, ensure you have an RDS instance running and note down the database URL, username, and password.

In your file, configure the data source like so:


This configuration tells Spring Boot to use the MySQL database hosted on Amazon RDS. The spring.jpa.hibernate.ddl-auto=update property automatically updates your database schema to match your entities.

Amazon S3 Integration

Amazon S3 can be used for storing application files, such as images or documents. To integrate S3 with Spring Boot, you need to add dependency for spring-cloud-starter-aws in your pom.xml file:


Then, configure your AWS credentials and S3 bucket name in

To upload files to S3, you can use the AmazonS3 client provided by AWS SDK. Here’s a simple example of a service method that uploads a file to S3:

private AmazonS3 amazonS3;

public void uploadFileToS3(MultipartFile file) {
    ObjectMetadata metadata = new ObjectMetadata();
    try {
        amazonS3.putObject(new PutObjectRequest('your-bucket-name', file.getOriginalFilename(), file.getInputStream(), metadata));
    } catch (IOException e) {
        throw new RuntimeException("Error uploading file", e);

By integrating these AWS services, your Spring Boot application can leverage the powerful, scalable infrastructure of AWS, enhancing its capabilities and performance.

Step 4: Monitoring and Scaling Your Application

Monitoring and scaling are critical aspects of managing a Spring Boot application on AWS, ensuring it remains healthy and responsive under varying loads. AWS provides several tools and services that can help you monitor your application’s performance and scale it according to demand.

Monitoring with Amazon CloudWatch

Amazon CloudWatch is a monitoring service that gives you actionable insights into your AWS resources and applications. For a Spring Boot application, you can monitor metrics like CPU utilization, request count, and response times. To start, ensure that you have the AWS SDK included in your project and that your application is running under an IAM role with CloudWatch access.

You can create custom metrics in your Spring Boot application and push them to CloudWatch for monitoring. Here’s a simple example of creating a custom metric:

MetricFilter metricFilter = new MetricFilter()
        new MetricTransformation()

PutMetricFilterRequest request = new PutMetricFilterRequest()

Scaling Your Application

AWS provides several options to scale your Spring Boot application, the most straightforward being Elastic Load Balancing and Auto Scaling. To set up Auto Scaling, navigate to the AWS Management Console, find your Elastic Beanstalk environment, and adjust the scaling settings.

Auto Scaling automatically adjusts the number of instances based on predefined rules or in response to increased demand. For example, you can scale out by adding instances when CPU utilization exceeds 70% or scale in by removing instances when CPU utilization drops below 30%.

By effectively leveraging these tools, you can ensure that your Spring Boot application remains performant and cost-efficient, regardless of traffic spikes or other changes in demand.

Performance Optimization of Spring Boot Application on AWS

Database Interaction Optimization:

Optimize your database interactions by implementing connection pooling, using query caching, and choosing appropriate database instance types. Consider using Amazon RDS Proxy for managing database connections efficiently, especially when scaling out your application instances.

Implement Caching Strategies:

Leverage caching mechanisms to reduce database load and improve response times. Use Amazon ElastiCache to implement in-memory caching for frequently accessed data. This can significantly speed up dynamic content generation by caching results of database queries or computationally intensive operations.

Utilize Amazon CloudFront:

Distribute static and dynamic content with Amazon CloudFront, a Content Delivery Network (CDN) service, to reduce latency and improve the user experience globally. CloudFront integrates seamlessly with S3, Elastic Load Balancing, and AWS Shield for DDoS protection, enhancing your Spring Boot application’s performance and security.

Best Practices for Spring Boot Deployment on AWS

When deploying Spring Boot applications to AWS, following best practices can significantly enhance the security, efficiency, and manageability of your applications. Here are some of the critical best practices to keep in mind:


  • Use AWS IAM Roles and Policies: Assign IAM roles to your AWS services and define policies that grant the least privilege necessary to perform their tasks. This approach helps in securing access to AWS resources.
  • Enable Encryption: Utilize AWS’s encryption options to protect data at rest and in transit. For instance, enable SSL/TLS for your Amazon RDS databases and S3 buckets.
  • Regularly Update Dependencies: Keep your Spring Boot application and its dependencies up to date to protect against known vulnerabilities.
  • Manage Secrets Securely: Utilize AWS Secrets Manager to manage, retrieve, and store sensitive configurations securely. This service helps in automating the rotation of secrets, reducing the risk of unauthorized access and ensuring your Spring Boot application’s security. In your application, access these secrets dynamically through the AWS SDK instead of hardcoding them in your properties files.
  • Securing API Access: Implement API Gateway in front of your Spring Boot application to manage API access securely. Use API Gateway to throttle requests, authorize API calls through IAM roles or Lambda authorizers, and ensure data validation. This not only secures your application but also provides a mechanism for monitoring API usage patterns.
  • SSL/TLS with AWS Certificate Manager: For applications exposed to the internet, secure your data in transit by using SSL/TLS certificates managed by AWS Certificate Manager (ACM). ACM simplifies the process of provisioning, managing, and deploying your SSL/TLS certificates on AWS resources like Elastic Load Balancers, which front your Spring Boot applications.

Cost Optimization

Rightsize Your Instances: Regularly review and adjust the size of your EC2 instances based on actual usage and performance metrics. Utilize AWS Cost Explorer to identify underutilized resources and consider downsizing or consolidating instances to match your workload requirements more closely, optimizing costs without compromising performance.

Adopt Cost-Effective Pricing Models: Explore and adopt AWS’s cost-effective pricing models such as Reserved Instances, Savings Plans, and Spot Instances for eligible workloads. Reserved Instances and Savings Plans offer significant discounts over standard on-demand pricing in exchange for a commitment to usage, while Spot Instances can further reduce your EC2 costs by allowing you to use spare computing capacity at substantial discounts.

Leverage S3 Lifecycle Policies: Implement lifecycle policies on Amazon S3 buckets to automatically transition older and less frequently accessed data to more cost-effective storage classes like S3 Infrequent Access or S3 Glacier. Additionally, configure policies to archive or delete data that is no longer needed, reducing storage costs significantly.

Monitor and Analyze AWS Usage with AWS Budgets and Cost Explorer: Use AWS Budgets to set custom budget alerts and monitor your AWS spending and usage. AWS Cost Explorer allows for detailed analysis of your costs and usage patterns, helping identify opportunities for cost savings. Regularly reviewing these reports can help you adjust your strategy and keep costs in check.

Utilize AWS Trusted Advisor: Engage AWS Trusted Advisor to analyze your AWS environment for cost-saving opportunities. It provides recommendations on reducing costs by identifying idle and underutilized resources, optimizing EBS volumes, and more. Implementing these recommendations can lead to significant savings.

Automate Resource Lifecycle Management: Implement automation to manage the lifecycle of your resources effectively. Use AWS Lambda in conjunction with Amazon CloudWatch Events to automatically start and stop instances based on schedule or utilization, ensuring you only pay for the resources you need. Automating cleanup tasks, such as deleting unused Elastic Load Balancers, Elastic IPs, and unattached EBS volumes, can also contribute to cost reductions.

Continuous Deployment

  • Automate Deployments Using AWS CodePipeline: Setup a continuous integration and deployment pipeline with AWS CodePipeline and CodeBuild. This automation will help you deploy changes more rapidly and with fewer errors.
  • Use Infrastructure as Code (IaC): Employ IaC tools like AWS CloudFormation or Terraform to manage your AWS resources. IaC allows you to version control your infrastructure, making it easier to replicate and rollback changes if needed.

Following these best practices can significantly improve the performance, security, and cost-effectiveness of your Spring Boot applications on AWS.

Common Challenges and Solutions

Deploying Spring Boot applications on AWS comes with its set of challenges. Awareness and preparation can help you navigate these issues seamlessly. Here are some common challenges and their solutions:

Database Connectivity

Challenge: Connecting your Spring Boot application to an Amazon RDS instance might encounter security or connection timeout issues.

Solution: Ensure that your RDS instance is in the same VPC as your Elastic Beanstalk environment. Use environment properties to store database credentials securely and adjust the RDS security group to allow traffic from your application.

Handling Sessions State

Challenge: Managing session state across multiple instances can be tricky, especially when scaling out.

Solution: Utilize Amazon ElastiCache or DynamoDB to manage session states externally, allowing your application to maintain consistency across instances.

Configuration Management

Challenge: Managing and applying configuration changes across all instances consistently is difficult.

Solution: Use AWS Systems Manager Parameter Store or Secrets Manager to centralize configuration management. These services allow you to securely store and manage configuration data, facilitating easy updates and access.

Cost Management

Challenge: Unanticipated AWS costs can accumulate, particularly when scaling resources to meet demand.

Solution: Implement budget alerts using AWS Budgets to monitor your spending. Regularly review your architecture and usage with AWS Trusted Advisor to identify cost-saving opportunities.

By addressing these common challenges with the suggested solutions, you can ensure a smoother deployment process and a more stable and cost-effective operation of your Spring Boot applications on AWS.


Deploying Spring Boot applications to AWS can enhance your application’s scalability, reliability, and flexibility. By following the step-by-step guide provided in this article, from preparing your application for AWS deployment to adopting best practices and resolving common challenges, you’re well-equipped to make the most of AWS services. Remember that continuous learning and adaptation to the evolving AWS ecosystem will further optimize your application’s performance and cost-efficiency. Dive deeper into AWS documentation and resources to explore more ways to leverage AWS for your Spring Boot applications.


How do I prepare my Spring Boot application for AWS deployment?

Prepare your application by ensuring it is stateless, integrating AWS dependencies using Spring Cloud for AWS, and leveraging AWS services like Amazon RDS or S3 for persistent data storage.

What AWS services are essential for deploying Spring Boot applications?

Key services include AWS Elastic Beanstalk for easy deployment and scaling, Amazon RDS for managed relational databases, and Amazon S3 for scalable storage solutions.

Can I automate the deployment of Spring Boot applications to AWS?

Yes, you can use AWS CodePipeline and CodeBuild to automate the continuous integration and deployment (CI/CD) of your Spring Boot applications, streamlining the deployment process.

How does AWS Elastic Beanstalk simplify Spring Boot application deployment?

AWS Elastic Beanstalk automates deployment tasks such as capacity provisioning, load balancing, auto-scaling, and application health monitoring, making it easier to manage Spring Boot applications.

What are the best practices for securing Spring Boot applications on AWS?

Best practices include using AWS IAM roles and policies for secure access, enabling encryption for data at rest and in transit, and regularly updating dependencies to protect against vulnerabilities.

How can I optimize the cost of running Spring Boot applications on AWS?

Optimize costs by rightsizing instances, adopting cost-effective pricing models like Reserved Instances or Spot Instances, and implementing S3 lifecycle policies to manage storage costs efficiently.

What strategies can I use to monitor and scale Spring Boot applications on AWS?

Utilize Amazon CloudWatch for monitoring application performance and AWS Auto Scaling to adjust resources automatically based on demand, ensuring efficient application scaling.

How do I integrate Amazon RDS with a Spring Boot application?

Integrate Amazon RDS by configuring your data source properties in the file of your Spring Boot application to use the RDS instance for database operations.

What are common challenges when deploying Spring Boot applications to AWS, and how can I solve them?

Common challenges include database connectivity issues and managing session state across instances. Solve these by ensuring your RDS instance is in the same VPC as your application and using Amazon ElastiCache or DynamoDB to manage session states externally.