Cloud, CI/CD, monitoring, and deployment (6.8K skills)
Choose and use Azure Storage services for files, shared folders, queues, and structured data. Covers listing and transferring blobs, comparing storage tiers by access frequency, redundancy options, and lifecycle management, with MCP tools and CLI examples.
Inspect an Azure resource group and document how its resources connect. The skill creates Mermaid diagrams, text-based architecture charts, alongside a resource inventory and explanations of network connections, data flows, identities, and dependencies in Markdown.
Prepare applications for deployment with Azure Developer CLI (azd). The skill analyzes the project, builds a plan for approval, and generates azure.yaml, infrastructure definitions, and Dockerfiles before handing off to validation.
Diagnose connection, authentication, and message processing problems in Azure Event Hubs and Azure Service Bus SDKs. Use error messages, configuration checks, service health, and diagnostic logs to identify fixes supported by Microsoft documentation.
Helps plan, create, and configure Azure Kubernetes Service clusters for running container workloads. Covers cluster type selection, networking, identity, monitoring, upgrades, scaling, and cost controls, with explanations for configuration choices that are difficult to change later.
Deploy prepared and validated applications to Azure using azd, Terraform, or Azure CLI deployment commands. Follows a deployment plan, performs preflight checks, handles errors, verifies endpoints and access roles, and reports deployed URLs.
Assess existing cloud applications and convert their code and configuration for Azure. The skill produces a migration report, maps source services to Azure targets, and saves converted files separately from the original source.
Turn an app idea or existing code into an Azure deployment. The skill selects services, plans the architecture, estimates costs, and generates infrastructure code, with approval steps before file generation and deployment.
Learn how to collect monitoring data from Azure-hosted web apps with Application Insights. Provides guidance on automatic and manual instrumentation, SDK configuration, and resource setup, with references for ASP.NET Core, Node.js, Python, and Container Apps.
Find installable agent skills for Azure and Microsoft cloud tasks. The skill searches a catalog, checks candidate descriptions, identifies the plugin containing each match, and provides installation guidance for the agent client in use.
Check Azure quotas, the limits on resource usage, alongside current usage and remaining allowance. Compare regions before deployment, investigate quota errors, and submit requests to increase adjustable limits using Azure CLI.
Configure Python applications to send traces, which record execution paths, metrics, and logs to Application Insights. Supports custom OpenTelemetry pipelines with control over sampling, export intervals, retry storage, and shutdown flushing.
Build Python code that sends custom logs to Azure Monitor Log Analytics. Covers uploading JSON files, retrying failed records, and asynchronous uploads, with guidance on authentication and rules that define log fields and destinations.
Manage Microsoft Fabric capacities, which provide computing resources, using Python. Provides examples for creating and listing capacities, changing their size, suspending and resuming them, and checking names and available capacity sizes.
Create and manage Azure Bot Service resources with Python. This skill guides bot creation, updates, channel configuration for Teams and Web Chat, and OAuth connections that let bots authenticate with external services.
Set up Python application monitoring in Application Insights using automatic instrumentation, which records application activity. The skill covers framework integration, custom traces, metrics and logs, plus sampling and authentication settings.
Manage files and directories in Azure Data Lake Storage Gen2 with Python. Provides patterns for uploads, downloads, directory moves, recursive listings, metadata, and access permissions, including chunked uploads for large files and asynchronous operations.
Write Python code to query Log Analytics logs and Azure Monitor metrics, such as CPU usage. Covers time ranges, batch queries, metric summaries, and conversion to pandas tables for further analysis.
Add monitoring to Node.js applications with Azure Monitor and OpenTelemetry. Collect traces that follow application work, performance measurements, and logs in Application Insights, with guidance for automatic collection, custom measurements, sampling, and shutdown.
Manage container images in Azure Container Registry using Python. Inspect repositories, tags, and manifests, which describe image contents; protect images against deletion, download image data, and clean up old untagged images with synchronous or asynchronous clients.
Send custom logs from Java applications to Azure Monitor. Covers collection rules that route logs to tables, authentication, batch and asynchronous uploads, concurrent sending, and error handling for failed entries or requests.
Build Java applications that run large batches of parallel work on Azure Batch. The skill guides compute pool management, job and task creation, progress checks, recurring schedules, and automatic scaling of the machines that execute tasks.
Configure Java applications to send OpenTelemetry traces, metrics, and logs to Azure Monitor. Follow examples for timing operations, recording errors, and adding context, with guidance for replacing the deprecated exporter package with the recommended autoconfigure package.
Build .NET code to create and manage Azure SQL servers, databases, shared resource pools, and firewall rules. The skill guides infrastructure management through Azure Resource Manager, including authentication, resource listing, and error handling.