AWS Engineering Building Production Systems on Amazon Web Services

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AWS Engineering Building Production Systems on Amazon Web Services

Author: Elliot Grayson

Description: Most cloud engineers know how to spin up an EC2 instance or create an S3 bucket. But when it comes to designing a system that survives a regional outage, scales to millions of users, and stays within budget—the gaps in that knowledge surface quickly. This book exists to close those gaps. "AWS Engineering: Building Production Systems on Amazon Web Services" by Elliot Grayson is not a collection of service tutorials. It is a rigorous, architecture-first guide that teaches you how to think about AWS as a complete operating environment. You will learn to weigh trade-offs, compose primitives into cohesive platforms, and operate them with the same discipline as teams at Netflix, Stripe, and Amazon. • Master the AWS Well-Architected Framework to evaluate every design decision. • Compare virtual machines, containers, and serverless to choose the right compute model. • Explore real-world case studies including multi-tenant SaaS, AI platforms, and global active-active architectures. Organized into six progressive parts, the book starts with the physical and philosophical foundations of AWS, then builds through networking, data, operations, and finally synthesis. Each chapter follows a consistent pattern: a production problem, an AWS primitive, an architectural composition, and a trade-off analysis. You will walk away with the ability to justify—not just implement—your architecture choices. This book is written for software engineers, cloud engineers, DevOps practitioners, and technical architects who have basic programming and networking experience. If you are ready to move beyond solving individual service challenges to designing whole systems that are scalable, secure, and reliable, this is your guide. AWS Engineering does not teach certification trivia or click-by-click console navigation. Instead, it gives you the mental models and operational patterns that turn cloud familiarity into architectural mastery.

AI summary: This book provides an architecture-first approach to building production systems on Amazon Web Services. It covers compute, networking, data, and operations, using the AWS Well-Architected Framework and real-world case studies from companies like Netflix and Amazon. Designed for software engineers and cloud practitioners, it teaches how to compose AWS services into scalable, secure, and reliable platforms.

Best for

Software engineers, cloud engineers, DevOps practitioners, and technical architects

Reader persona

A cloud engineer with basic AWS knowledge who wants to move from service-level tasks to designing production architectures.

Search intent

To learn how to design and operate production-grade systems on AWS using architectural patterns and best practices.

Unique angle

Unlike certification guides, this book takes an architecture-first approach, teaching how to compose AWS primitives into production systems with trade-off analyses and real-world case studies.

Content type

developer guide

Quick summary

• AWS Engineering teaches you to design production systems on AWS, focusing on architecture rather than service tutorials.
• The book covers compute options including EC2, containers, and serverless, with trade-off analyses.
• Real-world case studies include SaaS platforms, AI workloads, and global multi-region architectures.
• It is written for software engineers, cloud engineers, DevOps practitioners, and technical architects with basic AWS experience.

Key topics: AWS Well-Architected Framework, Compute (EC2, Containers, Serverless), Networking (VPC, Load Balancers, DNS), Data Storage (S3, RDS, DynamoDB), Security (IAM, Encryption), Observability (CloudWatch, X-Ray), Infrastructure as Code, CI/CD, Multi-Region Architecture, Case Studies (Netflix, Amazon)

Entities: Amazon Web Services, EC2, Lambda, S3, VPC, IAM, CloudFormation, Terraform, Kubernetes, DynamoDB, Well-Architected Framework, Microservices

Needs addressed

• Transition from basic AWS knowledge to production architecture design
• Understand how to compose AWS services into cohesive platforms
• Apply security and reliability best practices
• Design for scalability and cost optimization
• Implement continuous delivery and infrastructure as code
• Build multi-region and disaster recovery strategies

Read if

• Software engineers moving into cloud roles
• Cloud engineers seeking to deepen architecture skills
• DevOps engineers automating AWS deployments
• Technical architects designing cloud-native systems
• Computer science students studying cloud computing
• Engineering managers leading cloud teams

May not fit if

• Beginners with no cloud or programming experience
• Professionals seeking AWS certification exam prep only
• Developers looking for step-by-step console tutorials
• Those wanting deep dives into a single service like Lambda or DynamoDB

Table of contents

1. How to Use This Book (introduction)
2. Understanding the AWS Ecosystem (part)
3. Why AWS Changed Infrastructure (chapter)
4. The End of Traditional Data Centers (section)
5. Infrastructure as a Service (section)
6. The Rise of Cloud Computing (section)
7. The AWS Philosophy (section)
8. The Building Blocks of AWS (chapter)
9. Regions (section)
10. Availability Zones (section)
11. Edge Locations (section)
12. Global Infrastructure (section)
13. Thinking Like a Cloud Architect (chapter)
14. Scalability (section)
15. Reliability (section)
16. Security (section)
17. Cost Optimization (section)
18. Compute and Application Platforms (part)
19. Virtual Machines in the Cloud (chapter)
20. EC2 (section)
21. Auto Scaling (section)
22. Launch Templates (section)
23. Spot Instances (section)
24. Containers and Kubernetes (chapter)
25. ECS (section)
26. Fargate (section)
27. EKS (section)
28. Choosing the Right Platform (section)
29. Serverless Computing (chapter)
30. Lambda (section)
31. Event-Driven Systems (section)
32. Step Functions (section)
33. Serverless Trade-Offs (section)
34. Networking in AWS (part)
35. Building Private Networks (chapter)
36. VPC (section)
37. Subnets (section)
38. Route Tables (section)
39. NAT Gateways (section)
40. Traffic and Connectivity (chapter)
41. Load Balancers (section)
42. Route53 (section)
43. CloudFront (section)
44. API Gateway (section)
45. Designing Secure Architectures (chapter)
46. Security Groups (section)
47. Network ACLs (section)
48. Private Connectivity (section)
49. Zero Trust Concepts (section)
50. Data and Storage (part)
51. Object Storage at Scale (chapter)
52. S3 (section)
53. Lifecycle Policies (section)
54. Replication (section)
55. Storage Classes (section)
56. Databases in AWS (chapter)
57. RDS (section)
58. Aurora (section)
59. DynamoDB (section)
60. ElastiCache (section)
61. Data Reliability and Recovery (chapter)
62. Backup Strategies (section)
63. Multi-AZ (section)
64. Cross-Region Replication (section)
65. Disaster Recovery (section)
66. Operating Production Systems (part)
67. Identity and Access Management (chapter)
68. IAM (section)
69. Roles (section)
70. Policies (section)
71. Federation (section)
72. Observability and Operations (chapter)
73. CloudWatch (section)
74. X-Ray (section)
75. Logging (section)
76. Monitoring (section)
77. Infrastructure as Code (chapter)
78. CloudFormation (section)
79. Terraform (section)
80. Automated Provisioning (section)

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