Content

1. Designing a serverless web backend on AWS
2. Designing a serverless data analytics solution on AWS
3. Designing a hybrid solution for container based workloads on AWS
4. Designing a solution following account governance and management best practices

Designing solutions on AWS is about choosing the right managed services, reducing operational work, and building scalable and secure systems. In this blog, we will walk through four real-world use cases and design AWS architectures step by step.

Designing a serverless web backend on AWS

The first section follows a customer use case where an ecommerce company needs to migrate a backend web service to AWS. Design the solution for this use case, step by step, by using services such as Amazon API Gateway, AWS Lambda, Amazon Simple Queue Service (Amazon SQS), Amazon Simple Notification Service (Amazon SNS), and Amazon DynamoDB.

Use Case

An ecommerce company wants to migrate its backend web service to AWS.

The goal is:

• No server management
• Automatic scaling
• High availability
• Low operational cost

Key AWS Services Used

• Amazon API Gateway – Entry point for APIs
• AWS Lambda – Backend business logic
• Amazon DynamoDB – NoSQL database
• Amazon SQS – Queue for background tasks
• Amazon SNS – Notifications (email, SMS, alerts)

Step-by-Step Architecture Design

A. Client Request

• Web or mobile client sends a request (e.g., place order)

B. API Layer

• API Gateway receives and validates requests

C. Compute Layer

• Lambda processes the request (create order, validate user)

D. Data Layer

• DynamoDB stores order and customer data

E. Async Processing

• SQS handles background jobs (order processing, invoice generation)

F. Notifications

• SNS sends order confirmation emails or alerts

Architecture Diagram

Why This Design?

• Fully serverless
• Automatically scales
• Pay only for usage
• Fault-tolerant by default

 

Designing a serverless data analytics solution on AWS

The second section follows a customer use case where a software company needs a data analytics solution in AWS so that they can derive insights from clickstream data. Design the solution for this use case, step by step, by using services such as Amazon Simple Storage Service (Amazon S3), Amazon Kinesis Data Firehose, Amazon Athena, Amazon QuickSight, and more.

Use Case

A software company wants insights from clickstream data (user clicks, page views).

Goals:

• Real-time ingestion
• Low-cost analytics
• No data warehouse management

Key AWS Services Used

• Amazon Kinesis Data Firehose – Data ingestion
• Amazon S3 – Data lake storage
• Amazon Athena – SQL queries on S3
• Amazon QuickSight – Visualization and dashboards

Step-by-Step Architecture Design

A. Data Generation

• Web apps generate clickstream events

B. Data Ingestion

• Kinesis Firehose collects and delivers data

C. Data Storage

• Raw data stored in Amazon S3

D. Data Query

• Athena runs SQL queries directly on S3 data

E. Visualization

• QuickSight creates dashboards and reports

Architecture Diagram

Why This Design?

• No servers to manage
• Cheap storage using S3
• Query data using SQL
• Fast insights with dashboards

 

Designing a hybrid solution for container based workloads on AWS

The third section follows a customer use case where an enterprise insurance company needs to migrate some of their container workloads to AWS by using a hybrid model. Design the solution for this use case, step by step, by using services such as AWS Direct Connect, Amazon Elastic Container Service (Amazon ECS), Amazon ECS Anywhere, Amazon Relational Database Service (Amazon RDS), AWS Systems Manager, and more.

Use Case

An insurance company wants to move container workloads to AWS but still keep some workloads on-premises.

Goals:

• Hybrid model
• Centralized management
• Secure connectivity

Key AWS Services Used

• AWS Direct Connect – Private network connection
• Amazon ECS – Container orchestration
• Amazon ECS Anywhere – Run ECS on on-prem servers
• Amazon RDS – Managed database
• AWS Systems Manager – Server and container management

Step-by-Step Architecture Design

A. Network Connectivity

• Direct Connect links on-premises to AWS

B. Container Management

• ECS runs containers in AWS
• ECS Anywhere runs containers on on-prem servers

C. Database Layer

• RDS hosts application database

D. Operations

• Systems Manager handles patching and monitoring

Architecture Diagram

Why This Design?

• Gradual cloud migration
• Same tools for cloud and on-prem
• Secure and low-latency connectivity

 

Designing a solution following account governance and management best practices

The fourth section follows a customer use case where a startup company needs guidance about how to set up an account-management strategy that follows best practices for account governance and standards. Design the solution for this use case, step by step, by using services such as AWS Organizations, AWS IAM Identity Center (successor to AWS Single Sign-On), AWS CloudTrail, and more.

Use Case

A startup needs a secure AWS account setup following best practices.

Goals:

• Centralized billing
• Strong security
• Easy user management
• Audit and compliance

Key AWS Services Used

• AWS Organizations – Multi-account management
• AWS IAM Identity Center – Centralized access (SSO)
• AWS CloudTrail – Audit logging
• AWS Config – Resource compliance

Step-by-Step Architecture Design

A. Account Structure

• Create separate accounts (Dev, Test, Prod)

B. User Access

• IAM Identity Center manages user login

C. Security Monitoring

• CloudTrail records all API calls

D. Compliance

• AWS Config tracks resource changes

Architecture Diagram

Why This Design?

• Strong isolation between environments
• Centralized security and access
• Easy audits and compliance

Final Thoughts

Architecting on AWS is about:

• Choosing managed services
• Designing for scalability and security
• Reducing operational overhead

These architectures follow AWS best practices and can be adapted for real-world production systems.