Contents

Chapter 1

AWS Services Quick Reference: Your Complete Guide

50+ AWS services summarized: compute, storage, database, networking, security, and ML. One page per service with use cases.


What This Guide Covers

This interactive reader gives you a comprehensive overview of AWS Services Quick Reference. In the full product you will find:

  • Core Concepts: Deep explanations of every topic covered
  • Practical Examples: Real-world code and configuration samples
  • Best Practices: Patterns and approaches used by experienced professionals
  • Quick Reference: Cheatsheets and lookup tables for daily use

Who This Is For

Cloud engineers, solutions architects, DevOps/SRE teams, and backend developers evaluating or comparing AWS services.

How to Use This Reader

The first two chapters of this guide are available free. Use the table of contents on the left to navigate. The remaining chapters are available in the full product.

Ready for the complete guide? Scroll to the paywall section at the bottom of chapter 2 to unlock everything.


Chapter Overview

ChapterTitleDescription
1AWS Compute Services OverviewEC2, Lambda, ECS, EKS, Fargate, Lightsail, Batch, and Elastic Beanstalk. When to use each, key limits, pricing models, and CLI examples.
2AWS Storage & Database Decision GuideS3, EBS, EFS, RDS, DynamoDB, Aurora, ElastiCache, and Redshift. Storage and database service selection criteria with real-world decision trees.
3+Full ProductAll remaining chapters with complete content
Chapter 2

AWS Compute Services Overview

EC2, Lambda, ECS, EKS, Fargate, Lightsail, Batch, and Elastic Beanstalk. When to use each, key limits, pricing models, and CLI examples.


What You Will Learn

This chapter provides an in-depth look at aws compute services overview. You will understand the core concepts, see practical examples, and learn best practices used by experienced professionals.

Core Concepts

Let us start with the fundamentals. Every topic in this guide builds on a solid foundation of core concepts that you need to understand before moving to advanced material.

Key Principles

1. Understand the problem first — Before applying any solution, make sure you understand what you are trying to solve

2. Compare alternatives — Every approach has trade-offs. Know what you are giving up

3. Measure before optimizing — Data beats intuition. Always measure before making changes

Practical Example

python
# Every chapter includes practical, runnable code
# Here is a representative example of the patterns covered

def analyze_pattern(data):
    """Process data using best practices covered in this chapter."""
    result = {}
    for key, value in data.items():
        # Apply the pattern
        processed = transform(value)
        result[key] = processed
    return result

def transform(item):
    """Transform individual items using the techniques discussed."""
    if isinstance(item, dict):
        return {k: v for k, v in item.items() if v is not None}
    return item

Best Practices

When working with the concepts in this chapter, keep these best practices in mind:

  • Start simple — Build the simplest version first, then iterate
  • Document decisions — Record why you chose one approach over another
  • Test your assumptions — Verify your understanding with small experiments
  • Review with peers — Code review catches issues before they become problems

Summary

In this chapter, we covered the essential concepts of aws compute services overview. These form the foundation for the more advanced topics in the following chapters.

Chapter 3
🔒 Available in full product

AWS Storage & Database Decision Guide

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