Skill UI

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.

A comprehensive, low-level Software Development Kit (SDK) for building and managing stateful AI Agents within the Azure AI ecosystem using .NET. This SDK provides core clients for managing agent lifecycles, persistent conversation threads, message history, complex run execution, tool/function calling, and integrating file search through vector stores. It is essential for developing enterprise-grade, multi-turn conversational AI applications.

A comprehensive, low-level Software Development Kit (SDK) for building and managing stateful AI Agents within the Azure AI ecosystem using .NET. This SDK provides core clients for managing agent lifecycles, persistent conversation threads, message history, complex run execution, tool/function calling, and integrating file search through vector stores. It is essential for developing enterprise-grade, multi-turn conversational AI applications.

This is a low-level SDK for Java designed to create and manage persistent AI agents within Azure AI. It provides comprehensive tools for handling the entire agent lifecycle, including creating agents, managing conversation threads, sending messages, running agent processes, and cleaning up resources. Ideal for building robust, stateful AI applications requiring fine-grained control over agent interactions.

This is a low-level SDK for Java designed to create and manage persistent AI agents within Azure AI. It provides comprehensive tools for handling the entire agent lifecycle, including creating agents, managing conversation threads, sending messages, running agent processes, and cleaning up resources. Ideal for building robust, stateful AI applications requiring fine-grained control over agent interactions.

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 enables developers to build robust content moderation applications in Java using the Azure AI Content Safety services. It provides comprehensive capabilities to analyze both text and images for harmful content, detecting categories such as hate speech, violence, and sexual material. Furthermore, the SDK allows for custom blocklist management, enabling users to filter specific undesirable keywords or phrases to ensure strict content compliance and safety across various enterprise applications.