Amazon Web Services (AWS) is the world's most comprehensive and widely adopted cloud platform, offering over 240 fully featured services from data centers globally. AWS enables organizations to move faster, lower IT costs, and scale applications through a pay-as-you-go model that eliminates upfront infrastructure investment. Understanding AWS services requires recognizing that each service solves a specific problem within a broader cloud architecture — compute services run your code, storage services persist your data, networking services connect resources securely, and managed databases eliminate operational overhead, all working together to build resilient, scalable systems. In 2025–2026, AI has become a first-class citizen across the entire AWS stack, with Bedrock, Graviton5, S3 Vectors, and Lambda Durable Functions reshaping how applications are built and operated.
What This Cheat Sheet Covers
This topic spans 15 focused tables and 144 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
Table 1: Compute Services
The compute layer is where your application logic runs. AWS offers a spectrum from fully managed serverless functions to dedicated bare-metal servers, with the right choice depending on workload predictability, latency requirements, and how much infrastructure control you need.
| Service | Example | Description |
|---|---|---|
aws ec2 run-instances --image-id ami-0c55b159cbfafe1f0 --instance-type m9g.large | • Virtual servers providing scalable compute capacity in the cloud • offers 150+ instance types optimized for compute, memory, storage, or GPU workloads; latest Graviton5-powered M9g instances deliver up to 25% better performance with per-second billing. | |
exports.handler = async (event) => { return { statusCode: 200, body: 'Hello' };}; | • Serverless compute that runs code in response to events without provisioning servers • supports up to 10GB memory, 15-minute timeout, and automatic scaling from zero to thousands of concurrent executions. | |
aws ecs run-task --launch-type FARGATE --task-definition my-task | • Serverless compute engine for containers that eliminates the need to manage EC2 instances • works with ECS and EKS, allocating right-sized compute resources per container. | |
aws autoscaling create-auto-scaling-group --auto-scaling-group-name my-asg --min-size 2 --max-size 10 | • Automatically adjusts EC2 instance count based on demand using target tracking, step, or scheduled policies • maintains application availability and optimizes costs by scaling in during low traffic | |
aws lambda put-function-concurrency --function-name MyFunc --reserved-concurrent-executions 100 | • Runs Lambda functions on managed EC2 instances with built-in routing, load balancing, and autoscaling • provides EC2 pricing models and specialized hardware access while AWS handles all instance lifecycle management; supports EventBridge Scheduler for predictable capacity scaling. |