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AWS Cloud Learning Path for Java Developers and Solution Architects

A clean AWS roadmap for Java and Spring Boot developers covering foundations, compute, storage, data stores, networking, security, DevOps, observability, messaging, serverless, analytics, AI/ML, migration, and business services.

This AWS learning path is designed for Java developers, Spring Boot engineers, DevOps engineers, and solution architects who want a practical route from cloud fundamentals to production architecture.

Module Order

Order Module Articles Focus
1 AWS Foundations 4 AWS accounts, IAM, billing, CLI, SDKs, global infrastructure, and Well-Architected principles.
2 AWS Compute 5 Deploy Spring Boot workloads with EC2, Elastic Beanstalk, ECS Fargate, EKS, and App Runner.
3 AWS Storage and CDN 4 Use S3, presigned URLs, S3 events, and CloudFront for storage-backed application designs.
4 AWS Data Stores 6 Use RDS, Aurora, DynamoDB, ElastiCache, OpenSearch, and Neptune in Spring Boot architectures.
5 AWS Networking 5 Design VPC networking, load balancing, DNS, API Gateway, PrivateLink, and VPC endpoints.
6 AWS Security 5 Secure AWS workloads with IAM, Secrets Manager, KMS, Cognito, WAF, Shield, and security groups.
7 AWS DevOps and IaC 5 Automate builds, deployments, containers, infrastructure, and release workflows on AWS.
8 AWS Observability 5 Operate Spring Boot systems with CloudWatch logs, metrics, alarms, X-Ray, OpenTelemetry, and alerting.
9 AWS Messaging and Integration 5 Build event-driven integrations with SQS, SNS, EventBridge, Step Functions, Amazon MQ, and MSK.
10 AWS Serverless 5 Build Java and Spring serverless workloads with Lambda, Spring Cloud Function, API Gateway, DynamoDB, and file processing.
11 AWS Analytics and Data Engineering 6 Process and analyze data with Kinesis, Firehose, Glue, Athena, Redshift, and QuickSight.
12 AWS AI and Machine Learning 6 Integrate Bedrock, RAG, Textract, Comprehend, Rekognition, and SageMaker with Spring Boot applications.
13 AWS Migration and Hybrid Cloud 5 Plan migrations, database moves, modernization, hybrid connectivity, and enterprise migration readiness.
14 AWS Business Services 5 Build business workflows with SES, Pinpoint, Amazon Connect, WorkSpaces, AppStream, and notification platforms.

Path Map

flowchart LR
  A["AWS Foundations"]
  B["AWS Compute"]
  C["AWS Storage and CDN"]
  D["AWS Data Stores"]
  E["AWS Networking"]
  F["AWS Security"]
  G["AWS DevOps and IaC"]
  H["AWS Observability"]
  I["AWS Messaging and Integration"]
  J["AWS Serverless"]
  K["AWS Analytics and Data Engineering"]
  L["AWS AI and Machine Learning"]
  M["AWS Migration and Hybrid Cloud"]
  N["AWS Business Services"]

  A --> B --> C --> D --> E --> F --> G --> H --> I --> J --> K --> L --> M --> N

AWS Foundations

AWS accounts, IAM, billing, CLI, SDKs, global infrastructure, and Well-Architected principles.

  1. AWS Cloud Fundamentals
  2. IAM, Billing & Security Basics in AWS
  3. AWS CLI, AWS SDK & Spring Boot Integration
  4. AWS Well-Architected Framework

AWS Compute

Deploy Spring Boot workloads with EC2, Elastic Beanstalk, ECS Fargate, EKS, and App Runner.

  1. Deploy Spring Boot Application on AWS EC2
  2. Spring Boot with AWS Elastic Beanstalk
  3. Spring Boot with AWS ECS Fargate
  4. Spring Boot with AWS EKS
  5. Spring Boot with AWS App Runner

AWS Storage and CDN

Use S3, presigned URLs, S3 events, and CloudFront for storage-backed application designs.

  1. Spring Boot with Amazon S3
  2. S3 Presigned URLs with Spring Boot
  3. S3 Event Notifications
  4. CloudFront with Amazon S3

AWS Data Stores

Use RDS, Aurora, DynamoDB, ElastiCache, OpenSearch, and Neptune in Spring Boot architectures.

  1. Spring Boot with Amazon RDS
  2. Spring Boot with Amazon Aurora
  3. Spring Boot with Amazon DynamoDB
  4. Spring Boot with Amazon ElastiCache Redis
  5. Spring Boot with Amazon OpenSearch
  6. Spring Boot with Amazon Neptune

AWS Networking

Design VPC networking, load balancing, DNS, API Gateway, PrivateLink, and VPC endpoints.

  1. VPC Networking for Developers
  2. Load Balancer & Auto Scaling with Spring Boot
  3. Route 53 & Custom Domain for Spring Boot Applications
  4. API Gateway with Spring Boot
  5. AWS PrivateLink and VPC Endpoints with Spring Boot

AWS Security

Secure AWS workloads with IAM, Secrets Manager, KMS, Cognito, WAF, Shield, and security groups.

  1. IAM Roles and Policies for Spring Boot Applications
  2. AWS Secrets Manager with Spring Boot
  3. AWS KMS Encryption with Spring Boot
  4. Amazon Cognito with Spring Boot JWT Authentication
  5. AWS WAF, Shield & Security Groups for Spring Boot Applications

AWS DevOps and IaC

Automate builds, deployments, containers, infrastructure, and release workflows on AWS.

  1. Dockerize Spring Boot Applications for AWS
  2. AWS CodePipeline, CodeBuild & CodeDeploy with Spring Boot
  3. GitHub Actions with Amazon ECR & ECS for Spring Boot
  4. Terraform for Spring Boot Applications on AWS
  5. AWS CloudFormation and AWS CDK for Spring Boot Applications

AWS Observability

Operate Spring Boot systems with CloudWatch logs, metrics, alarms, X-Ray, OpenTelemetry, and alerting.

  1. CloudWatch Logs Spring Boot
  2. CloudWatch Metrics and Alarms
  3. X-Ray Spring Boot Tracing
  4. Open Telemetry Prometheus Grafana
  5. Alerting with SNS and CloudWatch

AWS Messaging and Integration

Build event-driven integrations with SQS, SNS, EventBridge, Step Functions, Amazon MQ, and MSK.

  1. SQS Spring Boot
  2. SNS Spring Boot
  3. EventBridge Spring Boot
  4. Step Functions Spring Boot
  5. Amazon MQ and MSK Kafka

AWS Serverless

Build Java and Spring serverless workloads with Lambda, Spring Cloud Function, API Gateway, DynamoDB, and file processing.

  1. AWS Lambda Java
  2. SpringCloudFunction Lambda
  3. API Gateway Lambda DynamoDB
  4. Serverless File Processing
  5. Serverless vs Containers vs EC2

AWS Analytics and Data Engineering

Process and analyze data with Kinesis, Firehose, Glue, Athena, Redshift, and QuickSight.

  1. Kinesis Data Streams
  2. Kinesis Firehose
  3. AWS Glue ETL
  4. Athena with S3
  5. Redshift Analytics
  6. QuickSight Dashboards

AWS AI and Machine Learning

Integrate Bedrock, RAG, Textract, Comprehend, Rekognition, and SageMaker with Spring Boot applications.

  1. Bedrock Spring Boot
  2. RAG with Bedrock, S3, and OpenSearch
  3. Textract Spring Boot
  4. Comprehend Spring Boot
  5. Rekognition Spring Boot
  6. SageMaker Endpoint Integration

AWS Migration and Hybrid Cloud

Plan migrations, database moves, modernization, hybrid connectivity, and enterprise migration readiness.

  1. OnPrem to AWS Migration
  2. Database Migration Service
  3. Monolith to Microservices AWS
  4. Hybrid Connectivity VPN Direct Connect
  5. Enterprise Migration Checklist

AWS Business Services

Build business workflows with SES, Pinpoint, Amazon Connect, WorkSpaces, AppStream, and notification platforms.

  1. SES Spring Boot
  2. Pinpoint Spring Boot
  3. Amazon Connect Integration
  4. WorkSpaces and AppStream
  5. Enterprise Notification Service

Completion Path

  1. Complete the modules in the order shown above.
  2. Use each module page as the source of truth for article order and Previous/Next navigation.
  3. Build small Spring Boot examples for compute, data, security, messaging, and observability services.
  4. Finish by reviewing production architecture, cost optimization, disaster recovery, and migration planning.

What Makes This Path Practical

  • It focuses on real application architecture, not only certification vocabulary.
  • It connects AWS services to Spring Boot implementation patterns.
  • It keeps security, monitoring, cost, and operations visible throughout the path.
  • It builds toward enterprise-scale design decisions rather than isolated service usage.