Resource Sizing and Selection Optimization

This guide focuses on the critical skill of matching AWS resource types and sizes (EC2, Lambda, RDS) to specific business requirements to balance performance, scalability, and cost.

Learning Objectives

After studying this guide, you should be able to:

• Identify the appropriate EC2 instance family (Compute, Memory, Storage optimized) based on workload characteristics.
• Optimize AWS Lambda performance by adjusting memory allocation.
• Distinguish between vertical and horizontal scaling strategies and when to apply each.
• Leverage AWS tools like Compute Optimizer to right-size existing infrastructure.
• Select cost-effective compute options including Spot Instances, Reserved Instances, and Savings Plans.

Key Terms & Glossary

• ECU (EC2 Compute Unit): A relative measure of integer processing power used to compare different EC2 instance types.
• Horizontal Scaling: Increasing capacity by adding more instances of a resource (e.g., adding more EC2 instances to an Auto Scaling Group).
• Vertical Scaling (Scaling Up): Increasing capacity by increasing the specifications (CPU, RAM) of an existing resource (e.g., changing a t3.medium to a t3.large).
• Server Density: The practice of packing as many virtual applications or microservices as possible into a single host to maximize hardware utilization.
• AMI (Amazon Machine Image): A template that contains the software configuration (OS, application server, and applications) required to launch an instance.

The "Big Idea"

The fundamental goal of resource selection is Performance Efficiency. In AWS, you are not locked into hardware. The