Master AWS Cloud Computing From Scratch

Clear, interactive, and structured AWS lessons designed for absolute beginners.

COURSE SYLLABUS
1. AWS Introduction
Introduction to AWS What is AWS? AWS Global Infrastructure AWS Management Console AWS Account Setup Root User vs IAM User Free Tier & Billing Safety
2. Identity & Access Management
Introduction to IAM IAM Users IAM Groups IAM Policies IAM Roles Multi-Factor Authentication
3. Amazon EC2
Introduction to EC2 EC2 Basics EC2 Instance Types Launch an EC2 Instance Security Groups Key Pairs Elastic Block Store (EBS)
4. Amazon S3
Introduction to S3 S3 Concepts S3 Buckets S3 Objects & Keys Versioning Bucket Policies
5. Amazon VPC
Introduction to VPC VPC Concepts Subnets Route Tables Internet Gateway NAT Gateway VPC Security Groups
6. Amazon RDS
Introduction to RDS RDS Concepts Database Engines Create RDS Database Backups
7. AWS Lambda
Introduction to Lambda Lambda Concepts Lambda Functions Triggers Environment Variables
8. Amazon CloudWatch
Introduction to CloudWatch CloudWatch Concepts Metrics CloudWatch Logs Alarms
9. Elastic Load Balancing
Introduction to Elastic Load Balancing ELB Concepts Application Load Balancer (ALB) Network Load Balancer (NLB) Gateway Load Balancer Target Groups Health Checks Listeners & Rules

CloudWatch Core Concepts

CloudWatch commonly involves metrics, logs, alarms, dashboards and related observability features.

Why it matters

These capabilities help you detect abnormal behavior and troubleshoot failures.

How it works

Collect telemetry → visualize → define threshold or condition → alarm → investigate logs/metrics.

Real-world example: An alarm can notify an operator when an important metric crosses a defined threshold.

Core Concept

Collect metrics and logs → define useful signals → create alarms → respond to alerts.

Good monitoring connects technical signals to application impact.

ApplicationMetrics + LogsCloudWatchMetricsLogsAlarm

What you should remember

Key idea

Collect metrics and logs → define useful signals → create alarms → respond to alerts.

Key idea

Good monitoring connects technical signals to application impact.

Real-world example

Use a realistic cloud workload and focus on the responsibility of this AWS service.

User → AWS service → application → data / response

Choose the service that matches the responsibility instead of forcing every workload into one resource.

# Conceptual workflow aws-service --resource example # Verify configuration → test → monitor → clean up
Practice tip: Build the smallest possible lab, verify the result, then remove resources you no longer need.

Quick Test

1 Question

What is the main idea of this AWS lesson?

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