From On-Premises to AWS: Architecting a Spring Boot Microservices Ecosystem in the Cloud

In today’s rapidly evolving tech landscape, moving from on-premises infrastructure to the cloud can significantly boost scalability, flexibility, and cost-efficiency. This guide walks you through deploying a Spring Boot microservices-based application in AWS, covering everything from user authentication to storage, service discovery, and continuous integration/deployment. Leveraging AWS’s comprehensive suite of services allows you to build a robust, scalable, and secure microservices architecture.

We begin by routing traffic through AWS Route 53, which efficiently manages DNS. For global content delivery, Amazon CloudFront speeds up access to static and dynamic content. AWS Cognito takes care of user authentication and authorization, ensuring secure access to your APIs. The AWS API Gateway serves as the entry point for all requests, while the Elastic Load Balancer (ELB) distributes traffic evenly across microservices hosted in Amazon ECS or EC2 instances.

To manage service discovery, we either use Eureka or AWS-native solutions like App Mesh. Your microservices are containerized and orchestrated with ECS or EKS, while compute needs are fulfilled by EC2 or AWS Lambda for specific tasks. Data is stored in Amazon RDS for relational needs and DynamoDB for NoSQL. ElastiCache handles in-memory caching.

For storage, Amazon S3 is a go-to for static files. To keep things automated and agile, the CI/CD pipeline is powered by CodeCommit, CodeBuild, CodeDeploy, and CodePipeline. Lastly, we ensure continuous monitoring with CloudWatch, distributed tracing with X-Ray, and secure audit logging with CloudTrail.

Gateway/EntryPoint :-

-> DNS Management: AWS Route 53

• Route 53 is the starting point of the architecture. It handles DNS management and routes incoming user traffic to the appropriate endpoints (e.g., API Gateway or Load Balancer).

-> API Gateway: AWS API Gateway

• Amazon API Gateway is ideal for exposing your microservices via APIs.
• It acts as a single entry point for your Eureka-based microservices and helps manage traffic, throttle requests, and offer caching.

-> Load Balancer: AWS Elastic Load Balancer (ELB)

• Elastic Load Balancer (ELB) distributes incoming requests evenly across your microservices running in ECS, EC2, or EKS containers, ensuring high availability and fault tolerance.

Authentication/Authorization :-

-> Authentication & Authorization: AWS Cognito

• Amazon Cognito can handle user authentication and authorization.
• It provides secure access to your services by managing user sign-ups, sign-ins, and access control.

Content Delivery Network (CDN) :-

-> Content Delivery: AWS CloudFront

• Amazon CloudFront is a content delivery network (CDN) used to distribute static and dynamic content (HTML, CSS, JS, images, etc.) to users with low latency.
• It caches content close to users globally, improving performance for static assets and API responses.

Application Layer :-

-> Compute: AWS EC2, AWS Lambda (Optional for Some Microservices)

• Amazon EC2 instances run your microservices, or you can use AWS Lambda for serverless microservices if they are stateless or event-driven.
• Elastic Beanstalk is also an option if you want AWS to manage infrastructure deployment for your microservices automatically.

-> Service Discovery: Eureka or AWS-native Service Discovery

• Eureka (deployed on EC2 or ECS) is responsible for service discovery, allowing microservices to find and communicate with each other dynamically.
• Alternatively, you can leverage AWS App Mesh or ECS Service Discovery for AWS-native service discovery.

-> Containerization & Orchestration: AWS ECS / EKS

• Amazon ECS or EKS manages the deployment and scaling of your containerized Spring Boot microservices. This is where your microservices run in isolated environments.

Storage :-

-> Storage: Amazon S3

• Amazon S3 for storing any static files, logs, or other media assets needed by your microservices.

Database :-

-> Databases: RDS, DynamoDB

• Amazon RDS for relational databases if your microservices require SQL databases (e.g., MySQL, PostgreSQL).
• Amazon DynamoDB for NoSQL databases, useful for high-speed, scalable, and key-value store scenarios.

Caching :-

-> Caching: Amazon ElastiCache

• ElastiCache (Redis or Memcached) provides in-memory data caching, reducing the load on your databases and improving the performance of your microservices.

Deployment :-

-> CI/CD Pipeline: AWS CodeCommit, CodeBuild, CodeDeploy, CodePipeline

• AWS CodeCommit: A version control service for storing your microservices' source code.
• AWS CodeBuild: Automatically builds and tests your application code.
• AWS CodeDeploy: Deploys the built application to the desired target (EC2, ECS, Lambda).
• AWS CodePipeline: Orchestrates the CI/CD workflow, integrating CodeCommit, CodeBuild, and CodeDeploy to automate the release process.

Monitoring :-

-> Monitoring & Logging: Amazon CloudWatch, X-Ray

• Amazon CloudWatch for monitoring and logging system metrics, logs, and application performance.
• AWS X-Ray for tracing requests as they travel across different microservices, allowing you to identify bottlenecks or issues.

Security/Access Control :-

-> Security: AWS IAM, AWS Secrets Manager

• AWS IAM manages roles and permissions for your microservices to interact with other AWS services.
• AWS Secrets Manager or Parameter Store stores sensitive data like API keys, database credentials, and configuration secrets securely.