Aws
A comprehensive skill catalog for AI agents
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Amazon Web Services cloud platform with Lambda, EC2, S3, and RDS. Use for AWS infrastructure.
SKILL.md
1.5 KB, 342 tokens by cl100k_base, as published. Nobody here has run it
AWS
Amazon Web Services (AWS) is the dominant cloud platform. In 2025, the focus is heavily on Generative AI (Bedrock, Q, Trainium chips) and Serverless Data (Aurora Limitless).
When to Use
- Enterprise: The default choice for large-scale, compliant infrastructure.
- AI/ML: Amazon SageMaker and Bedrock provide the deepest toolset for training and inference.
- Serverless: Lambda + DynamoDB + API Gateway is the canonical serverless stack.
Core Concepts
VPC (Virtual Private Cloud)
Your isolated network. Subnets, Route Tables, Internet Gateways. Understanding networking is mandatory.
IAM (Identity and Access Management)
Global service for permissions. "Deny by default". Use Roles for services, not access keys.
Compute
- EC2: Virtual Machines.
- ECS/EKS: Containers (Docker/K8s).
- Lambda: Function-as-a-Service.
Best Practices (2025)
Do:
- Use AWS Organizations: Separate Prod, Staging, and Dev into different Accounts, not just VPCs. Limits blast radius.
- Use CDK / Terraform: Never click in the console for production resources.
- Cost Control: Enable Cost Explorer and set up Budgets/Alerts on day one.
Don't:
- Don't use Public Subnets for Apps: Put your EC2s/RDS in Private Subnets. Only Load Balancers go in Public Subnets.
References
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.