Curriculum Overview: AWS Compute Services Mastery

This curriculum is designed to provide a comprehensive understanding of the AWS Compute category, a core pillar of the AWS Cloud Practitioner (CLF-C02) exam. Students will learn to distinguish between virtual machines, serverless functions, and containerized orchestration.

Prerequisites

Before beginning this module, learners should possess the following foundational knowledge:

• Basic Cloud Concepts: Understanding of the AWS Shared Responsibility Model and Cloud Deployment models (Public, Private, Hybrid).
• AWS Global Infrastructure: Familiarity with Regions and Availability Zones (AZs).
• Basic Networking: A high-level understanding of what a VPC (Virtual Private Cloud) and IP addresses are.
• Virtualization Fundamentals: General awareness of what a Virtual Machine (VM) is compared to a physical server.

Module Breakdown

Learning Objectives per Module

Module 1: Amazon EC2 (Elastic Compute Cloud)

• Identify the purpose of an Amazon Machine Image (AMI) as the template for the OS and software.
• Differentiate between instance types (e.g., Compute Optimized vs. Memory Optimized).
• Explain the benefits of root access and full administrative control over instances.

Module 2: AWS Lambda (Serverless)

• Define serverless computing and its "pay only for what you use" billing model.
• Recognize use cases for short-running, event-driven scripts (e.g., image resizing upon upload).
• Understand that AWS handles all underlying infrastructure maintenance and scaling.

Module 3: Container Orchestration (ECS & EKS)

• Distinguish between Amazon ECS (AWS-native) and Amazon EKS (Kubernetes-compatible).
• Identify AWS Fargate as the serverless compute engine for both ECS and EKS.
• Understand how containers provide application portability and environment consistency.

Module 4: High Availability & Elasticity

• Explain how Auto Scaling provides elasticity by adding/removing instances based on demand.
• Identify the role of Elastic Load Balancing (ELB) in distributing traffic across multiple targets.

Visual Anchors

Compute Selection Decision Tree

Management Effort vs. Flexibility

Success Metrics

To demonstrate mastery of this curriculum, the learner must be able to:

1. Scenario Mapping: Correctly assign a service (EC2, Lambda, or ECS) to a specific business requirement with 90% accuracy.
2. Terminology Precision: Distinguish between horizontal scaling (adding instances) and vertical scaling (making an instance bigger).
3. Cost Optimization: Identify which service minimizes costs for a task that only runs for 5 seconds once a day (Answer: Lambda).
4. Deployment Identification: Explain the difference between an AMI (for EC2) and a Container (for ECS/EKS).

Real-World Application

[!IMPORTANT] Why this matters in a career: Understanding AWS Compute is the "bread and butter" of a Cloud Architect or Developer. If you choose EC2 when Lambda would suffice, you increase your company's operational overhead and monthly bill. If you choose Lambda for a 24/7 heavy-processing task, you may face timeouts and higher costs than a reserved EC2 instance.

• Case Study: A retail website uses EC2 for its web servers, Auto Scaling to handle Black Friday traffic, and Lambda to process email receipts immediately after a purchase. This hybrid approach ensures reliability while optimizing costs for sporadic tasks.

▶Click to expand: Career Roles Using These Skills

• Cloud Practitioner: Understands the "What" and "Why" for billing and high-level planning.
• Solutions Architect: Designs the "How" by selecting the right compute mix for performance.
• DevOps Engineer: Automates the deployment of containers and scaling policies.