How does this skill help with DynamoDB performance?

It provides guidance on avoiding hot partitions, implementing exponential backoff, and choosing between GSIs and LSIs to minimize latency and throttling.

How does this skill handle cost optimization?

It offers advice on selecting the right capacity mode (On-Demand vs. Provisioned) and using TTL for automatic data expiration to reduce storage costs.

Can it help with Single-Table Design?

Yes, it includes patterns and best practices for using partition keys (PK) and sort keys (SK) to model complex relational data within a single table.

Does it support both AWS CLI and Boto3?

Yes, the skill provides reference implementations and commands for both the Python Boto3 library and the AWS Command Line Interface.

AWS DynamoDB Expert

Name: AWS DynamoDB Expert
Author: itsmostafa

byitsmostafa

•

963

データベース管理

Optimizes AWS DynamoDB workflows with expert schema design, query patterns, and performance troubleshooting guidance.

概要

This Claude Code Skill provides comprehensive expertise for managing Amazon DynamoDB, a fully managed NoSQL database. It streamlines the entire development lifecycle, from designing efficient single-table schemas and composite keys to implementing complex CRUD operations and batch processing using the AWS CLI or Boto3. By integrating best practices for indexing (GSI/LSI), performance tuning, and cost optimization, it helps developers build scalable, cost-effective data layers while offering deep troubleshooting for issues like throttling and hot partitions.

主な機能

Optimization of secondary indexes (GSI/LSI) and sparse index strategies
Implementation of CRUD, query, and batch operations via CLI and Boto3
Performance troubleshooting for hot partitions and throughput throttling
963 GitHub stars
Cost-saving guidance for on-demand versus provisioned capacity modes
Advanced schema design following single-table and composite key patterns

ユースケース

Debugging performance bottlenecks and optimizing database costs in AWS environments
Migrating legacy data access patterns to efficient DynamoDB query structures
Designing and deploying scalable NoSQL table schemas for high-traffic applications

概要

主な機能

Optimization of secondary indexes (GSI/LSI) and sparse index strategies
Implementation of CRUD, query, and batch operations via CLI and Boto3
Performance troubleshooting for hot partitions and throughput throttling
963 GitHub stars
Cost-saving guidance for on-demand versus provisioned capacity modes
Advanced schema design following single-table and composite key patterns

ユースケース

Debugging performance bottlenecks and optimizing database costs in AWS environments
Migrating legacy data access patterns to efficient DynamoDB query structures
Designing and deploying scalable NoSQL table schemas for high-traffic applications