A company plans to migrate a legacy on‑premises Java web application to AWS. The app runs on Apache Tomcat and uses PostgreSQL. The company cannot modify the source code but can deploy the JAR files. Traffic spikes at the end of each month. Which solution meets these needs with the LEAST operational overhead?

The correct solution leverages AWS Elastic Beanstalk for the Java application, as it supports Tomcat and automates deployment, scaling, and load balancing with minimal operational overhead. Deploying across multiple Availability Zones ensures high availability. Amazon RDS for PostgreSQL provides a managed database service, eliminating the need to manage database infrastructure. An Application Load Balancer (ALB) distributes traffic efficiently, while Amazon CloudFront acts as a content delivery network (CDN) to cache content and absorb traffic spikes, further reducing load on the application. Incorrect options: Installing Tomcat and PostgreSQL directly on EC2 instances with EFS for shared storage increases operational overhead for patching, backups, and scaling. AWS Step Functions is not designed for scaling EC2 instances for web traffic. Amazon EKS in an Auto Scaling group across multiple Regions is overly complex and expensive for this requirement, and deploying PostgreSQL inside containers on EKS adds significant management overhead compared to RDS. Refactoring the application to Python and using Lambda/DynamoDB is explicitly ruled out by the constraint that the company "cannot modify the source code.