System Design on AWS

Cloud computing platforms such as AWS now underpin modern digital systems, allowing organizations to build, scale, and innovate quickly without managing physical infrastructure. As more businesses adopt cloud-native, data-driven, and AI-powered solutions, strong cloud architecture skills are critical for designing secure, resilient, and cost-effective systems.

This book offers a practical guide to designing secure, scalable, and cost-effective AWS architecture. It connects theory to real-world implementation by focusing on how modern cloud systems are built, deployed, and governed. By covering core AWS services and architectural patterns, it helps readers understand not only what to use, but also why and when to use it. This book provides actionable insights for building production-ready systems. It covers networking, security, serverless, containers, and AI/ML integration, aligning each topic with the AWS Well-Architected Framework. Each chapter highlights trade-offs, design decisions, and best practices relevant to industry roles.

By the end of this book, readers will gain the knowledge and practical skills needed to make informed architectural decisions across networking, security, compute, and data services. They will learn to evaluate trade-offs, apply AWS best practices, implement production-ready solutions, and align their architectures with operational, security, cost, and governance requirements.

What you will learn

● Design secure, scalable, and cost-efficient AWS architectures with confidence.

● Apply best practices in networking, security, compute, and data services.

● Make informed architectural decisions by evaluating trade-offs and real-world constraints.

● Build and deploy production-ready solutions with current AWS tools and architectural patterns.

● Implement governance, monitoring, and operational best practices in cloud environments.

Who this book is for

This book is designed for students, cloud engineers, solution architects, DevOps engineers, and technical professionals working with AWS who seek to design and manage production-grade systems. It also supports developers and IT professionals transitioning to cloud roles or preparing for architect-level responsibilities.

Table of Contents

1. Getting Started with AWS

2. Core AWS Services for Scalable Architecture

3. Scaling with AWS Compute and Serverless

4. Designing Distributed Systems in AWS

5. Data Storage Strategies and Patterns on AWS

6. Load Balancing and Auto-Scaling

7. Monitoring and Observability Best Practices

8. Essential AWS AI/ML Services

9. Advanced AWS AI Services

10. Designing and Deploying AI Applications on AWS

11. Scaling and Automating AI Applications

12. Infrastructure as Code and DevOps Automation

13. Securing and Governing AWS Architectures

14. AWS Fargate, ECS, and SAM

15. Amazon Elastic Kubernetes Service Architecture

16. Service Mesh and Autoscaling for EKS

17. Security and Best Practices in EKS

18. System Design Interview Essentials

Manish Kumar Atnere is an innovative and results-driven Cloud Architect Leader with over 20 years of experience architecting, automating, and managing scalable, secure, and high-performance infrastructure. He specializes in Kubernetes, AI/ML infrastructure, cloud platforms including AWS, Azure, and GCP, and Infrastructure as Code using Terraform. With a proven track record in designing and managing AI workloads, Manish Atnere excels in optimizing hybrid cloud environments and enabling DevSecOps and GitOps in enterprise settings.Currently a Lead Cloud Architect at leading software company, Manish architects containerized AI/ML workloads using AWS EKS and bare-metal clusters, integrating advanced AI data pipelines with Kubernetes. He has built end-to-end ML pipelines and RAG architectures using technologies like LangChain, FAISS, and vector databases, and developed automation tools for performance profiling and observability. His leadership in GitOps and DevSecOps pipelines has significantly enhanced release velocity and system reliability.Manish holds multiple certifications including AWS Certified Solutions Architect - Professional, AWS Certified Solutions Architect - Associate, Certified Kubernetes Administrator (CKA), and has deep expertise in cloud-native architectures, AI/ML engineering, and secure infrastructure automation. His extensive hands-on experience and strategic insights make him uniquely qualified to guide readers in mastering system design on AWS with integrated AI capabilities.