基础设施与 DevOps技能

Review Azure Advisor recommendations and service retirement information, including totals, breakdowns, and affected resources. Update recommendation states with confirmation, and route requests to implement fixes to the separate azure-advisor-actionability skill.

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• Review recommendation counts and breakdowns
• Identify resources affected by recommendations
• Check service retirement information

Prepare remediation steps for Azure Advisor recommendations using the affected resource’s details. Guidance comes from the Advisor remediation tool or public Microsoft Learn documentation, with warnings, verification steps, and clear source attribution.

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• Prepare steps to address an Azure Advisor recommendation
• Tailor remediation to a specific Azure resource
• Find Microsoft Learn guidance when remediation is unavailable

Find the Azure portal screen for a specific operation and generate a direct link. Provide a supported resource’s URL or resource ID plus a plain-language query to locate the relevant menu.

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• Find the portal screen for a resource operation
• Generate a direct link from a resource ID
• Locate a menu using a plain-language query

Investigate live Azure Kubernetes Service incidents through read-only checks of logs, events, and resource state. Trace workload, node, networking, or upgrade failures and produce an incident report with supporting evidence, confidence, and proposed remediation.

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• Investigating crashing or Pending pods
• Tracing DNS, ingress, and connectivity failures
• Diagnosing node-pool scaling and quota failures

Collect bounded packet captures from AKS nodes or pods alongside Azure network settings. Use the captured traffic as evidence when investigating where packets are lost, after initial checks that do not change the environment.

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• Collect packet captures from an AKS node
• Gather evidence of where packets are lost
• Retrieve captures alongside Azure network settings

Find documented fixes for known AKS errors by matching the exact error message and required conditions. Get an explanation of the cause, a proposed fix, a Microsoft Learn reference, and read-only verification steps.

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• Look up a documented fix for a specific AKS error
• Check the cause of a node pool creation failure
• Review verification steps before changing AKS resources

Investigate GPU and KAITO failures in AKS using read-only evidence. Helps distinguish scheduling problems, memory shortages, workspace readiness issues, and scaling failures, then organizes findings with confidence levels and missing evidence.

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• Investigating GPU pods stuck in Pending
• Distinguishing container memory shortages from GPU memory failures
• Investigating a KAITO Workspace that is not ready

Deploy Azure OpenAI models by checking available capacity in the current region first. If capacity is unavailable, reviews other regions and presents alternatives, then deploys with GlobalStandard and monitors deployment progress.

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• Deploying an Azure OpenAI model with preset settings
• Finding another region when the current region has no capacity
• Comparing model capacity across regions

Deploy Azure OpenAI models through a guided workflow. Choose the model version, deployment type, capacity, content filter, and supported advanced options, then review the configuration before deployment and monitor its status.

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• Deploy a specific model version
• Choose a deployment type and capacity
• Select a content filtering policy

Create separate Microsoft Entra identities for AI agent instances and configure their permissions. The skill guides Microsoft Graph provisioning, token exchange, actions on behalf of users, cross-tenant authentication, and shared authentication containers for multiple programming languages.

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• Create a separate identity for each agent instance
• Assign permissions to individual agents
• Configure authentication on behalf of users

Assess existing AKS clusters or local Kubernetes configuration files for AKS Automatic compatibility. Identify migration blockers, distinguish required changes from automatic adjustments, and present proposed file changes and migration steps.

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• Assessing migration readiness from AKS Standard to AKS Automatic
• Checking local Kubernetes configuration files offline
• Reviewing proposed changes for incompatible settings

Find Azure OpenAI deployment locations that meet a required token rate. Compare accessible regions and projects, check platform capacity and subscription quotas, and receive a ranked table of candidates before moving to a separate deployment workflow.

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• Find deployment locations with enough tokens per minute
• Compare model availability across regions
• Find alternative locations after a quota error

Deploy an existing web app or API to Azure Kubernetes Service. The skill detects the framework, creates container and deployment files, checks AKS safety requirements, and verifies the deployment.

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• Deploying an existing web app or API to AKS
• Creating container and Kubernetes configuration files
• Investigating AKS Deployment Safeguards failures

Assess and carry out upgrades within Azure, including Functions hosting plans and Redis migrations. Guides readiness checks, settings transfer, deployment, and validation, with a separate workflow for updating legacy Azure Java SDK code.

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• Assess Functions apps for a move to Flex Consumption
• Migrate Functions from Consumption to Flex Consumption
• Migrate Azure Cache for Redis to Azure Managed Redis

Assess whether an application is ready for Azure before infrastructure planning. Inspect source files and configuration without running builds or tests, then report component readiness, dependency compatibility, deployment blockers, and preparation needed before deployment.

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• Check application readiness before deploying to Azure
• Review dependency and framework compatibility
• Identify missing configuration and deployment blockers

Check whether an application is ready for Azure deployment by validating configuration, infrastructure definitions, role assignments, and managed identity permissions. Follow a staged workflow that records progress and identifies issues to resolve before deployment.

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• Check deployment readiness
• Validate azure.yaml and Bicep
• Review role assignments and managed identity permissions

Configure Azure API Management as a shared gateway for AI models, tools, and agents. Apply usage limits, caching, content checks, and load balancing, then test requests and track token consumption.

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• Set token limits and track AI usage
• Configure caching and load balancing for model requests
• Limit requests to MCP tools

Route Azure virtual machine requests to workflows for choosing sizes, comparing prices, creating machines or scale sets, reserving capacity, and managing machine enrollment and monitoring. Helps identify the appropriate process for each infrastructure task.

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• Compare VM sizes and prices for a workload
• Create a VM or Virtual Machine Scale Set
• Reserve VM capacity and manage associations

Assess deployed Azure Functions and Azure App Service applications for resilience to failures. Review zone redundancy, storage replication, health checks, and regional failover, then apply approved improvements through Azure CLI or infrastructure configuration files.

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• Assessing reliability gaps in deployed Azure applications
• Enabling zone redundancy and health checks
• Preserving reliability settings in Bicep or Terraform

Turn workload requirements into an enterprise Azure infrastructure plan and Bicep or Terraform configuration files. Covers networks, access controls, and disaster recovery, with validation, security checks, and approval gates before deployment.

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• Planning an Azure landing zone
• Designing networks, firewalls, and private endpoints
• Planning disaster recovery across multiple regions

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.

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• Checking remaining resource allowance before deployment
• Comparing quota availability across Azure regions
• Investigating quota exceeded errors

Find and list Azure resources across subscriptions and resource groups. Use it to build an inventory, count resources by type, check missing tags, or discover unattached disks through dedicated tools and Azure Resource Graph queries.

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• Listing Azure resources across subscriptions
• Finding Web Apps and App Services
• Checking resources for missing tags

Deploy Flask, Django, FastAPI, or other Python code to Azure App Service on Linux. The skill creates missing hosting resources, configures startup and deployment builds, and selects Azure CLI or azd based on the project.

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• Deploy a Flask or Django application to Azure App Service
• Configure startup and deploy a FastAPI application
• Create missing resources needed to host a Python application

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.

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• Upload and download files in Blob Storage
• List storage accounts, containers, and blobs
• Compare Hot, Cool, Cold, and Archive tiers