AWS for Java Developers

The most direct path from a Spring Boot JAR to a running production instance — launching EC2, installing a JDK, running the JAR as a systemd service, and fronting it with a load balancer.

Containerizing a Spring Boot application and running it on ECS Fargate — no EC2 instances to patch, automated rolling deployments, and integrated health checks and auto-scaling.

Running a containerized Spring Boot application on Kubernetes via EKS — Deployments, Services, Ingress, and the Kubernetes-native health-check model, for teams that need the broader Kubernetes ecosystem.

Running Spring Boot on Lambda instead of a server — the cold-start problem specific to the JVM, and the tools (Spring Cloud Function, SnapStart, GraalVM native images) that address it.

Connecting a Spring Data JPA application to Amazon RDS securely and reliably — connection strings, IAM database authentication, connection pooling, and Secrets Manager-based credential rotation.

Using the AWS SDK for Java from a Spring Boot application to upload, download, and generate pre-signed URLs for S3 objects — the correct, IAM-role-based way to grant an application S3 access.

Publishing and consuming messages from SNS/SQS in a Spring Boot application using Spring Cloud AWS — the fan-out pattern, listener configuration, and dead-letter queue handling.

Externalizing Spring Boot configuration and secrets to AWS Secrets Manager and Systems Manager Parameter Store, instead of properties files or environment variables baked into an image.

Wiring together CodePipeline, CodeBuild, ECR, and ECS (or CodeDeploy) into a full build-test-containerize-deploy pipeline for a Spring Boot application, triggered automatically on every commit.