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Modern Cloud Security Engineering

A Practical Guide to Securing AWS, Azure, and Google Cloud

This book is 100% completeLast updated on 2026-07-17
Steve Publications

Cloud security is built, not bought. This practical guide goes beyond checklists and compliance to teach the engineering principles behind secure cloud environments. Learn how to design resilient identity systems, protect workloads, secure data, detect threats, and respond to incidents across AWS, Microsoft Azure, and Google Cloud using production-tested techniques and real-world architectures.

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About the Book

Cloud security is not a product you buy. It is an engineering discipline that requires deep understanding of identity, infrastructure, data, and process across multiple platforms. This book provides production-grade guidance for securing workloads on AWS, Microsoft Azure, and Google Cloud Platform, with equal emphasis on shared principles and platform-specific implementations. From foundational IAM design to advanced incident response, from offensive attack paths to defensive detection engineering, every chapter delivers the technical depth that cloud security engineers, DevSecOps practitioners, and security architects need to build secure systems that actually work in production.

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Cloud ComputingAmazon Web ServicesGoogle Cloud PlatformAzure DocumentDBComputer SecurityCyber Security

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About the Author

Steve Publications

Steve is a technology professional with more than 20 years of experience in software development, server infrastructure, cybersecurity, vulnerability research and reverse engineering. Throughout his career, he has designed, secured, analyzed and tested complex software and infrastructure, with a particular focus on understanding how systems fail and how they can be made more secure.

Outside of work, Steve enjoys sharing knowledge with the technology community. He collaborates with researchers, industry experts and technology professionals to write practical books covering software development, cybersecurity, cloud computing, networking, DevOps, artificial intelligence and enterprise technologies. His books focus on practical learning through clear explanations, real-world examples and hands-on exercises. With more than two decades of industry experience, his goal is to help IT professionals, students and technology enthusiasts build useful skills and stay current in a rapidly changing industry.

We believe readers deserve to know how our books are created. Most of our authors are not native English speakers, so we use AI to help translate, proofread manuscripts, fix grammar, improve sentence structure and make technical explanations easier to read. AI is used as an editing tool only. It does not replace the research, technical knowledge or hands-on experience behind our books. Some of our authors also prefer to remain anonymous for privacy or professional reasons. In those cases, we publish their work under a different name. The author's name may be different, but the quality of the content and our review process remain the same.

Every book is written, reviewed and maintained by experienced technology professionals, with contributions from our private technical community of more than 420 engineers and researchers from Ukraine, Belarus and Russia. We spend far more time validating technical accuracy and keeping our content up to date than generating text. We are always interested in working with experienced professionals who have deep expertise in a particular technology or domain. If you would like to publish a book with us or help review an existing manuscript, we'd love to hear from you. Send us a message describing your area of expertise. We are especially interested in niche technologies, specialized skills and emerging topics that are underrepresented in existing technical literature.

If you look through the contents of our books, you'll see practical examples, detailed explanations and material that is regularly updated. Our goal is to publish books that professionals can actually rely on, not low-effort AI-generated content. If you ever feel that one of our books does not meet that standard, Leanpub offers a 60-day money-back guarantee. Feel free to request a refund if you are not satisfied with your purchase.

Contents

Table of Contents

A Practical Guide to Securing AWS, Azure, and Google Cloud

Introduction: Why Cloud Security Is an Engineering Problem

  1. The Scale of the Problem
  2. What Makes Cloud Security Different
  3. How to Use This Book

Chapter 1: The Cloud Security Landscape

  1. What Is Cloud Security Engineering
  2. The Shared Responsibility Model Across Providers
  3. How Cloud Attacks Differ From Traditional Attacks
  4. The Economics of Cloud Security
  5. Common Pitfalls and Operational Trade-offs
  6. Building Your Cloud Security Mindset

Chapter 2: Identity and Access Management

  1. IAM Fundamentals and the Principle of Least Privilege
  2. AWS IAM: Policies, Roles, and Advanced Patterns
  3. Azure RBAC and Entra ID Security
  4. GCP IAM and Organization Policies
  5. Cross-Account and Cross-Cloud Identity Strategies
  6. Case Study: Capital One (2019) – SSRF, IMDSv1, and the Cost of Excessive IAM Roles
  7. Case Study: Snowflake (2024) – Credential Stuffing and the MFA Gap
  8. Case Study: Okta (2023) – Session Token Theft and MFA Bypass
  9. IAM Attack Paths: Privilege Escalation and Identity Abuse
  10. IAM Operational Trade-offs and Common Pitfalls

Chapter 3: Cloud Networking Security

  1. Cloud Networking Fundamentals
  2. AWS VPC Security and Network ACLs
  3. Azure Virtual Networks and NSGs
  4. GCP VPC and Firewall Rules
  5. Private Connectivity: VPC Peering, ExpressRoute, Interconnect
  6. DNS Security and DDoS Protection
  7. Attack Simulation: Network-Based Lateral Movement in AWS
  8. Networking Decision Framework: Security Group vs. NACL vs. Firewall
  9. Networking Operational Trade-offs and Common Pitfalls

Chapter 4: Zero Trust Architecture in the Cloud

  1. Zero Trust Principles for Cloud Environments
  2. Microsegmentation Across Platforms
  3. Identity-Aware Proxy and API Security
  4. Device and Workload Attestation
  5. Implementing Zero Trust in Multi-Cloud
  6. When Zero Trust Controls Fail
  7. Zero Trust Operational Trade-offs and Common Pitfalls

Chapter 5: Infrastructure as Code Security

  1. The Security Case for Infrastructure as Code
  2. Terraform Security Best Practices
  3. AWS CloudFormation and Native IaC Security
  4. Azure Bicep/ARM Template Security
  5. Policy as Code: OPA, Sentinel, Conftest
  6. Drift Detection and Compliance Automation
  7. Decision Framework: Choosing an IaC Tool
  8. When IaC Security Controls Fail
  9. IaC Operational Trade-offs and Common Pitfalls

Chapter 6: Container and Kubernetes Security

  1. Container Security Fundamentals
  2. EKS, AKS, and GKE Hardening
  3. Image Scanning and Signing
  4. Runtime Security and Admission Controllers
  5. Service Mesh Security: mTLS and Authorization
  6. Case Study: Kubernetes Cluster Compromise Patterns (2024)
  7. Kubernetes Attack Paths and Defense
  8. When Container Security Controls Fail
  9. Container and Kubernetes Operational Trade-offs and Common Pitfalls

Chapter 7: Serverless and Application Security

  1. Serverless Security Model
  2. AWS Lambda Security Patterns
  3. Azure Functions and GCP Cloud Functions Hardening
  4. API Gateway Security Across Platforms
  5. Application Layer Threats and WAF
  6. Function-Level Isolation and Resource Limits
  7. Attack Simulation: Serverless Exploitation Chain
  8. When Serverless Security Controls Fail
  9. Serverless Operational Trade-offs and Common Pitfalls

Chapter 8: Secrets Management and Encryption

  1. Secrets Management Fundamentals
  2. AWS Secrets Manager, Parameter Store, and KMS
  3. Azure Key Vault and Managed Identities
  4. GCP Secret Manager and Cloud KMS
  5. Encryption Architecture Patterns
  6. Key Rotation, HSMs, and Customer-Managed Keys
  7. Decision Framework: Choosing a Secrets Management Solution
  8. Secrets and Encryption Operational Trade-offs and Common Pitfalls

Chapter 9: Logging, Monitoring, and Threat Detection

  1. Cloud Logging Architecture
  2. AWS CloudTrail, GuardDuty, and Security Hub
  3. Azure Monitor, Defender for Cloud, and Sentinel
  4. GCP Cloud Audit Logs, Chronicle, and SCC
  5. Detection Engineering: SIEM Queries and Correlation Rules
  6. Threat Hunting Methodologies for Cloud
  7. Troubleshooting Logging and Detection Issues
  8. When Logging and Detection Controls Fail
  9. Logging and Detection Operational Trade-offs and Common Pitfalls

Chapter 10: Incident Response in the Cloud

  1. Why Cloud Incident Response Is Different
  2. Detection and Triage Workflows
  3. Containment Strategies: Network, Identity, and Compute
  4. Forensic Challenges in Ephemeral Environments
  5. Automated Response Playbooks
  6. Post-Incident Recovery and Lessons Learned
  7. Case Study: Cloud Credential Exposure via CI/CD Pipeline
  8. When Incident Response Controls Fail
  9. Incident Response Operational Trade-offs and Common Pitfalls

Chapter 11: DevSecOps and CI/CD Security

  1. The DevSecOps Pipeline
  2. CI/CD Pipeline Security Hardening
  3. Static Analysis: SAST, DAST, and SCA
  4. Container and Image Scanning in Pipelines
  5. Deployment Gates and Policy Enforcement
  6. Case Study: CI/CD Pipeline Compromise Patterns
  7. Secrets in Pipelines and Build Systems

Chapter 12: Supply Chain Security

  1. The Cloud Supply Chain Attack Surface
  2. Case Study: XZ Utils Backdoor (CVE-2024-3094) – The Near-Catastrophic Supply Chain Attack
  3. SBOM Generation and Management
  4. Artifact Signing and Verification
  5. Dependency Management and Vulnerability Tracking
  6. Cloud-Specific Supply Chain Attacks
  7. SLSA Framework and Provenance
  8. Supply Chain Operational Trade-offs and Common Pitfalls

Chapter 13: Governance, Compliance, and Multi-Account Architecture

  1. Multi-Account and Multi-Tenant Architecture
  2. Landing Zone Design Patterns
  3. Compliance Frameworks: NIST, CIS, SOC 2, ISO 27001
  4. Automated Compliance and Audit
  5. Cost Governance and Security Optimization
  6. Cross-Cloud Governance Challenges
  7. When Governance Controls Fail
  8. Governance and Compliance Operational Trade-offs and Common Pitfalls

Chapter 14: Advanced Topics and Emerging Threats

  1. AI and ML Workload Security
  2. Hybrid and Multi-Cloud Security Architectures
  3. Data Protection: Classification, DLP, and Tokenization
  4. Disaster Recovery and Resilience Patterns
  5. Emerging Cloud Threats: AI-Powered Attacks, Supply Chain, Zero-Day
  6. The Future of Cloud Security Engineering
  7. Advanced Topics Operational Trade-offs and Common Pitfalls

Conclusion: Engineering Security That Works

References

Glossary

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