AWS Cheatsheet

Compute Services

ECR - Elastic Container Registry, stores images (e.g. Docker)
ECS - Elastic Container Service, orchestrates/scales Docker containers
EC2 - Elastic Compute Cloud, virtual machine. Rent in cloud. Common use case is as a server for a web application. Do whatever on it though
Load Balancing - Allows traffic to be distributed among multiple EC2 instances
Cloud Watch - collects logs and metrics from EC2 instances
Auto Scaling - defines policies to create new EC2 instances based on traffic, etc
Elastic Beanstalk - More abstraction on top of EC2 and all the above services (aka PaaS - Platform as a Service)
Lightsail - Even more abstraction…
Lambda - Functions as a Service, aka Serverless. Code runs only when an event occurs. Only pay for requests and compute time, not constant uptime
Serverless Repo - more abstraction on top of a Lambda
Outposts - Runs AWS APIs on your personal server

General-Purpose Storage

Snow - mini data-centers that function without internet
ECR - Elastic Container Registry, allows you to upload images (e.g. Docker)
ECS - Elastic Container Service, starts and stops containers
Fargate - Makes containers behave like serverless functions and run on demand (not constantly), so you don’t need to run an EC2 full-time
S3 - Simple Storage Service, stores any data. Good for general purpose file storage
Glacier - lower cost version of S3, higher latency
Block Storage - higher cost version of S3, lower latency
Elastic File System - higher abstraction, higher cost

Database Services

Simple DB - General purpose NOSQL database
Dynamo DB - document-style database, more sophisticated, higher cost
Document DB - Behaves exactly like MongoDB
Elastic Search - for constructing a search engine
RDS - Relational Database Service, SQL service
Aurora - another db service, allows for serverless (runs on trigger, not constantly up)
Neptune - graph database
Elastic Cache - Redis implementation
TimeStream - time-series database

Analytics

Redshift - data warehouse, alternative to Oracle, query with SQL
Lake Formation - store large amounts of unstructured data
Kinesis - analyze real-time data
Map Reduce - operates on massive data sets in parallel
Glue - Serverless, ETL (extract transform load) service for data
Data Exchange - Purchase data from 3rd party sources

Machine Learning

Sagemaker - Connect to data to implement ML models
Rekognition - Image analysis

Dev Tools

IAM - create rules, permissions
Cognito - Handles authentication
Simple Notification Service - push notifications to users
Simple Email Service - email notifications to users