Skill UI

This comprehensive Python SDK serves as a client library for managing the full lifecycle of Machine Learning resources on Azure Machine Learning. It allows users to programmatically handle workspaces, register data and models, provision compute clusters, define complex training jobs, and build reproducible, end-to-end MLOps pipelines.

This comprehensive Python SDK serves as a client library for managing the full lifecycle of Machine Learning resources on Azure Machine Learning. It allows users to programmatically handle workspaces, register data and models, provision compute clusters, define complex training jobs, and build reproducible, end-to-end MLOps pipelines.

This SDK provides comprehensive management plane capabilities for provisioning and controlling Microsoft Fabric compute capacities via Azure Resource Manager (ARM). Use it to perform core lifecycle operations such as creating, updating (including scaling), suspending, resuming, and deleting Fabric capacities. Note: This SDK manages the underlying compute resource, not the data plane elements like workspaces or lakehouses.

This SDK provides comprehensive management plane capabilities for provisioning and controlling Microsoft Fabric compute capacities via Azure Resource Manager (ARM). Use it to perform core lifecycle operations such as creating, updating (including scaling), suspending, resuming, and deleting Fabric capacities. Note: This SDK manages the underlying compute resource, not the data plane elements like workspaces or lakehouses.

This SDK provides the management plane capabilities for Azure Cosmos DB within the .NET ecosystem. It allows developers to programmatically provision and manage core infrastructure resources, such as Cosmos DB accounts, databases, containers, throughput settings, and perform resource lifecycle operations using Azure Resource Manager (ARM). It is designed for infrastructure automation and setup tasks.

A comprehensive SDK guide for managing Azure MySQL Flexible Server deployments using C# and the .NET framework. This skill provides workflows for automated resource management, including server creation, database provisioning, configuring firewall rules, tuning server parameters, and integrating Entra ID (Azure AD) for robust security and operational control.

This SDK provides full management plane capabilities for Azure Cache for Redis within the .NET ecosystem. It allows developers to provision, configure, and manage various aspects of the Redis resource using the Azure Resource Manager (ARM) framework. Key functions include creating and updating cache instances, managing network firewall rules, rotating access keys, scheduling patch updates, and performing data import/export operations.

This SDK provides the management plane interface for provisioning and administering Azure SQL resources (servers, databases, firewalls, etc.) using C# and .NET. It allows developers to automate the deployment lifecycle of SQL infrastructure entirely through code, integrating seamlessly with the Azure Resource Manager.

This skill simulates a cloud cost optimization expert specializing in reducing infrastructure expenses across AWS, Azure, and GCP. It analyzes complex cloud spending patterns, identifies waste, overprovisioning, and potential savings opportunities. It provides actionable recommendations, implements cost controls, and proposes cost-effective, reliable architectures, ensuring cost efficiency without sacrificing performance or reliability.

Configure robust role-based access control (RBAC) for Granola workspaces, essential for enterprise-level data security and governance. This guide details setting up role hierarchies (Owner, Admin, Member, Viewer), defining granular permissions, integrating SSO/SCIM for automated provisioning, and implementing least-privilege access principles. It also covers advanced features like per-workspace sharing policies and detailed audit logging to ensure regulatory compliance.

Provides Meta AI’s Segment Anything Model for zero-shot image segmentation via interactive prompts or automatic mask generation, enabling rapid dataset creation and integration in vision pipelines.

A comprehensive guide for deploying Machine Learning training jobs and inference services on the Vast.ai GPU cloud. This skill covers the entire deployment lifecycle, including optimizing Docker images for performance, creating automated provisioning scripts using the Vast.ai CLI, implementing robust data transfer strategies (SCP, rsync), and performing post-deployment health checks.