Does it support both Provisioned and On-Demand capacity?

Yes, the skill includes patterns for configuring PAY_PER_REQUEST and PROVISIONED billing modes, including auto-scaling for provisioned capacity.

Can I use this for cross-stack references?

Absolutely, the skill includes specific patterns for exporting Table ARNs and Names so they can be securely imported by application-level stacks.

How does it handle database security?

It implements AWS best practices for Server-Side Encryption (SSE), IAM role integration, and Point-in-Time Recovery (PITR) within the template logic.

Can this skill help with managing existing DynamoDB tables?

Yes, it provides patterns for managing existing tables via CloudFormation using AWS-specific parameter types and import/export logic.

AWS CloudFormation DynamoDB Patterns

Name: AWS CloudFormation DynamoDB Patterns
Author: giuseppe-trisciuoglio

bygiuseppe-trisciuoglio

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Cloud Infrastructure

Provisions and manages production-ready DynamoDB infrastructure using standardized AWS CloudFormation templates and best practices.

About

This skill provides Claude with domain-specific patterns and implementation logic for deploying DynamoDB tables via AWS CloudFormation. It covers the full lifecycle of NoSQL database infrastructure, including configuring primary keys, Global and Local Secondary Indexes (GSI/LSI), capacity modes, and auto-scaling policies. By utilizing modular template structures with parameters, mappings, and cross-stack references, it ensures that your database infrastructure is scalable, maintainable, and aligned with AWS architectural best practices for security and performance.

Key Features

Secure configuration of encryption at rest and Point-in-Time Recovery
Advanced index management including GSIs and LSIs with projection settings
Data lifecycle management via TTL and DynamoDB Streams for change capture
Automated creation of DynamoDB tables with HASH and RANGE keys
Implementation of Auto Scaling policies and capacity mode configurations
84 GitHub stars

Use Cases

Automating database scaling and recovery policies for production environments
Structuring complex IaC deployments using nested stacks and cross-stack references
Setting up a serverless backend database for a web or mobile application

About

Key Features

Secure configuration of encryption at rest and Point-in-Time Recovery
Advanced index management including GSIs and LSIs with projection settings
Data lifecycle management via TTL and DynamoDB Streams for change capture
Automated creation of DynamoDB tables with HASH and RANGE keys
Implementation of Auto Scaling policies and capacity mode configurations
84 GitHub stars

Use Cases

Automating database scaling and recovery policies for production environments
Structuring complex IaC deployments using nested stacks and cross-stack references
Setting up a serverless backend database for a web or mobile application