Skill UI

A comprehensive guide covering crucial API architectural decisions and best practices. Learn when to choose between REST, GraphQL, and tRPC, define robust response formats, implement versioning strategies, and secure endpoints using OAuth or JWT. This skill helps developers build scalable, maintainable, and secure backend services.

This skill provides comprehensive guidance on mastering proven backend architectural patterns, including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design (DDD). It helps users design, refactor, and scale complex systems by defining clear module boundaries, managing dependencies, and ensuring testability. Use it when migrating monolithic applications, initiating microservices decomposition, or establishing robust architectural standards.

This skill provides comprehensive guidance on mastering proven backend architectural patterns, including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design (DDD). It helps users design, refactor, and scale complex systems by defining clear module boundaries, managing dependencies, and ensuring testability. Use it when migrating monolithic applications, initiating microservices decomposition, or establishing robust architectural standards.

This comprehensive guide covers the best practices for building production-ready, scalable serverless applications on Amazon Web Services (AWS). Learn to leverage core services like Lambda, API Gateway, and DynamoDB, and implement advanced patterns such as event-driven architectures (SQS/SNS). The content emphasizes performance optimization, robust error handling, structured logging, and deploying infrastructure using SAM/CDK.

This comprehensive guide covers the best practices for building production-ready, scalable serverless applications on Amazon Web Services (AWS). Learn to leverage core services like Lambda, API Gateway, and DynamoDB, and implement advanced patterns such as event-driven architectures (SQS/SNS). The content emphasizes performance optimization, robust error handling, structured logging, and deploying infrastructure using SAM/CDK.

This skill provides comprehensive guidance and established patterns for developing applications on Amazon Web Services (AWS). It focuses specifically on implementing robust infrastructure automation and adhering to best-practice cloud architecture patterns, ensuring scalable, secure, and resilient cloud deployments. Use this when building enterprise-grade systems requiring modern cloud development methodologies.

This skill provides comprehensive guidance and established patterns for developing applications on Amazon Web Services (AWS). It focuses specifically on implementing robust infrastructure automation and adhering to best-practice cloud architecture patterns, ensuring scalable, secure, and resilient cloud deployments. Use this when building enterprise-grade systems requiring modern cloud development methodologies.

A comprehensive solution for deploying multi-service, containerized applications (frontend + backend) to Azure Container Apps. This utility uses the Azure Developer CLI (azd) to manage the entire lifecycle, ensuring idempotent infrastructure provisioning, remote builds, managed identity integration, and robust environment configuration across development, staging, and production environments.

A comprehensive solution for deploying multi-service, containerized applications (frontend + backend) to Azure Container Apps. This utility uses the Azure Developer CLI (azd) to manage the entire lifecycle, ensuring idempotent infrastructure provisioning, remote builds, managed identity integration, and robust environment configuration across development, staging, and production environments.

This SDK allows developers to build robust anomaly detection applications in Java using Azure AI services. It supports both univariate and multivariate time-series analysis, enabling detection of outliers, trend changes, and correlated signals over large datasets. Ideal for real-time monitoring, operational intelligence, and advanced data quality checks.

This SDK allows developers to build robust anomaly detection applications in Java using Azure AI services. It supports both univariate and multivariate time-series analysis, enabling detection of outliers, trend changes, and correlated signals over large datasets. Ideal for real-time monitoring, operational intelligence, and advanced data quality checks.

This SDK provides a comprehensive Python client library for interacting with Azure AI Speech-to-Text services. It supports both real-time streaming transcription and robust batch processing of audio files. Users can leverage advanced features such as speaker diarization (identifying multiple speakers) and capturing precise timestamps, making it invaluable for automated meeting minute generation, podcast content processing, and live captioning solutions.