Expert knowledge for Azure Confidential Computing development including decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building SGX/SEV-SNP apps, AKS confidential containers, SKR/Key Vault flows, vTPM/CVMs, or Fortanix CCM, and other Azure Confidential Computing related development tasks. Not for Azure Virtual Enclaves (use azure-virtual-enclaves), Azure Dedicated HSM (use azure-dedicated-hsm), Azure Cloud Hsm (use azure-cloud-hsm), Azure Payment Hsm (use azure-payment-hsm).
npx skills add https://github.com/MicrosoftDocs/Agent-Skills --skill azure-confidential-computing
This skill provides expert guidance for Azure Confidential Computing. Covers decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
> IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g., L35-L120), use read_file with the specified lines. For categories with file links (e.g., security.md), use read_file on the linked reference file
> IMPORTANT for Agent: If metadata.generated_at is more than 3 months old, suggest the user pull the latest version from the repository. If mcp_microsoftdocs tools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.| Category | Lines | Description |
|----------|-------|-------------|
| Decision Making | L35-L46 | Guidance on choosing Azure confidential computing options: VMs (AMD/Intel), containers, GPUs, deployment models, capabilities, products, and use cases for secure workloads. |
| Architecture & Design Patterns | L47-L56 | Architectural patterns and design guidance for using Azure confidential VMs, SGX enclaves, AKS, and multi-party analytics to build secure AI and containerized workloads. |
| Limits & Quotas | L57-L62 | Intel SGX capacity, quotas, and sizing for Azure confidential computing: AKS confidential node limits, SGX VM sizing guidance, and FAQ on SGX resource constraints. |
| Security | L63-L78 | Security, attestation, and key/secrets management for Azure confidential workloads: SGX enclaves, CVMs, vTPM, AKS confidential containers, clean rooms, and hardening Linux images. |
| Configuration | L79-L90 | Configuring and deploying Azure confidential VMs and containers (AKS SGX, VMMD blob, CMK rotation, ARM/CLI), plus Secure Key Release policies and Virtual Machine Metablob Disk usage. |
| Integrations & Coding Patterns | L91-L101 | Coding patterns and samples for building, running, and attesting Intel SGX/AMD SEV-SNP confidential apps and containers, including SKR flows, tools, and Fortanix/Key Vault integrations. |
| Deployment | L102-L110 | How to deploy and migrate Azure confidential VMs/VMSS and AKS (SGX and confidential node pools), create custom images, and set up Fortanix CCM using CLI and ARM templates. |
| Topic | URL |
|-------|-----|
| Select Azure confidential container offerings | https://learn.microsoft.com/en-us/azure/confidential-computing/choose-confidential-containers-offerings |
| Choose Azure confidential computing deployment models | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-computing-deployment-models |
| Understand Azure confidential container options | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-containers |
| Overview of confidential containers on Azure | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-containers |
| Understand and choose Azure confidential VM capabilities | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-vm-overview |
| Use Azure confidential GPUs for secure compute offload | https://learn.microsoft.com/en-us/azure/confidential-computing/gpu-options |
| Choose Azure confidential computing use cases | https://learn.microsoft.com/en-us/azure/confidential-computing/use-cases-scenarios |
| Select Azure confidential VM options on AMD or Intel | https://learn.microsoft.com/en-us/azure/confidential-computing/virtual-machine-options |
| Topic | URL |
|-------|-----|
| Apply confidential computing to AI workloads on Azure | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-ai |
| Design solutions with Azure confidential computing options | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-computing-solutions |
| Use SGX enclave nodes in AKS workloads | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-nodes-aks-overview |
| Design enclave-aware container applications on AKS | https://learn.microsoft.com/en-us/azure/confidential-computing/enclave-aware-containers |
| Understand Azure confidential VM guest attestation design | https://learn.microsoft.com/en-us/azure/confidential-computing/guest-attestation-confidential-virtual-machines-design |
| Architect multi-party analytics on Azure confidential computing | https://learn.microsoft.com/en-us/azure/confidential-computing/multi-party-data |
| Topic | URL |
|-------|-----|
| AKS confidential nodes Intel SGX capacity details | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-nodes-aks-faq |
| Deploy and size Intel SGX VMs on Azure | https://learn.microsoft.com/en-us/azure/confidential-computing/virtual-machine-solutions-sgx |
| Topic | URL |
|-------|-----|
| Configure attestation for Azure SGX enclaves | https://learn.microsoft.com/en-us/azure/confidential-computing/attestation |
| Use attestation types for Azure confidential workloads | https://learn.microsoft.com/en-us/azure/confidential-computing/attestation-solutions |
| Use Secure Key Release with Azure Key Vault and confidential computing | https://learn.microsoft.com/en-us/azure/confidential-computing/concept-skr-attestation |
| Security model for AKS Confidential Containers | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-containers-aks-security-policy |
| Understand security details for Azure confidential VMs | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-vm-faq |
| Configure guest attestation for Azure confidential VMs | https://learn.microsoft.com/en-us/azure/confidential-computing/guest-attestation-confidential-vms |
| Secure confidential VMs with Defender for Cloud and guest attestation | https://learn.microsoft.com/en-us/azure/confidential-computing/guest-attestation-defender-for-cloud |
| Harden Linux images by removing Azure guest agent | https://learn.microsoft.com/en-us/azure/confidential-computing/harden-a-linux-image-to-remove-azure-guest-agent |
| Harden Linux images by removing sudo users for confidential VMs | https://learn.microsoft.com/en-us/azure/confidential-computing/harden-the-linux-image-to-remove-sudo-users |
| Leverage vTPM features in Linux confidential VMs | https://learn.microsoft.com/en-us/azure/confidential-computing/how-to-leverage-virtual-tpms-in-azure-confidential-vms |
| Manage secrets and keys in Azure confidential computing | https://learn.microsoft.com/en-us/azure/confidential-computing/secret-key-management |
| Use virtual TPMs in Azure confidential VMs securely | https://learn.microsoft.com/en-us/azure/confidential-computing/virtual-tpms-in-azure-confidential-vm |
| Topic | URL |
|-------|-----|
| Configure Confidential Containers on AKS (preview) | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-containers-on-aks-preview |
| Configure AKS Intel SGX device plugin (confcom) | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-nodes-aks-addon |
| Configure opt-out of VMMD blob for Azure Confidential VMs | https://learn.microsoft.com/en-us/azure/confidential-computing/disable-confidential-vm-metadata-blob |
| Rotate customer-managed keys for Azure confidential VMs | https://learn.microsoft.com/en-us/azure/confidential-computing/key-rotation-offline |
| Deploy Azure confidential VMs with ARM templates | https://learn.microsoft.com/en-us/azure/confidential-computing/quick-create-confidential-vm-arm |
| Provision Azure confidential VMs using Azure CLI | https://learn.microsoft.com/en-us/azure/confidential-computing/quick-create-confidential-vm-azure-cli |
| Author Secure Key Release policies for Azure confidential TEEs | https://learn.microsoft.com/en-us/azure/confidential-computing/skr-policy-examples |
| Use Virtual Machine Metablob Disk with confidential VMs | https://learn.microsoft.com/en-us/azure/confidential-computing/virtual-machine-metablob-disk |
| Topic | URL |
|-------|-----|
| Use development tools for Intel SGX enclaves on Azure | https://learn.microsoft.com/en-us/azure/confidential-computing/application-development |
| Run confidential containers with Intel SGX enclaves | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-containers-enclaves |
| Build Intel SGX enclave apps with OSS tools | https://learn.microsoft.com/en-us/azure/confidential-computing/enclave-development-oss |
| Use guest attestation sample app with confidential VMs | https://learn.microsoft.com/en-us/azure/confidential-computing/guest-attestation-example |
| Run apps with Fortanix CCM and Node Agent | https://learn.microsoft.com/en-us/azure/confidential-computing/how-to-fortanix-confidential-computing-manager-node-agent |
| Implement SKR with confidential containers on Azure Container Instances | https://learn.microsoft.com/en-us/azure/confidential-computing/skr-flow-confidential-containers-azure-container-instance |
| Implement SKR from Key Vault to AMD SEV-SNP confidential VMs | https://learn.microsoft.com/en-us/azure/confidential-computing/skr-flow-confidential-vm-sev-snp |
| Topic | URL |
|-------|-----|
| Deploy AKS cluster with SGX enclave nodes via CLI | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-enclave-nodes-aks-get-started |
| Use confidential VM node pools in AKS | https://learn.microsoft.com/en-us/azure/confidential-computing/confidential-node-pool-aks |
| Create custom images for Azure confidential VMs with CLI | https://learn.microsoft.com/en-us/azure/confidential-computing/how-to-create-custom-image-confidential-vm |
| Deploy Fortanix CCM as Azure managed app | https://learn.microsoft.com/en-us/azure/confidential-computing/how-to-fortanix-confidential-computing-manager |
| Migrate nested Azure confidential VMs across regions | https://learn.microsoft.com/en-us/azure/confidential-computing/migrate-nested-confidential-vms |
| Deploy VM scale sets with hardened Linux images | https://learn.microsoft.com/en-us/azure/confidential-computing/vmss-deployment-from-hardened-linux-image |
Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.
Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
Take microsoftdocs/azure-confidential-computing from the repository into ~/.claude/skills for personal
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