/microsoft-foundry-classic

name: microsoft-foundry-classic
description: Expert knowledge for Microsoft Foundry Classic (aka Azure AI Foundry classic) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Foundry hubs/agents, model routing, Azure OpenAI integrations, RAG apps, or secure private endpoints, and other Microsoft Foundry Classic related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Local (use microsoft-foundry-local), Content Safety in Foundry Control Plane (use azure-content-safety), Azure Speech in Foundry Tools (use azure-speech).
compatibility: Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
metadata:
  generated_at: "2026-08-09"
  generator: "docs2skills/1.0.0"

Microsoft Foundry Classic Skill

This skill provides expert guidance for Microsoft Foundry Classic. Covers troubleshooting, best practices, 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.

How to Use This Skill

> **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](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](https://github.com/MicrosoftDocs/mcp/blob/main/README.md)

This skill requires **network access** to fetch documentation content:

• **Preferred**: Use `mcp_microsoftdocs:microsoft_docs_fetch` with query string `from=learn-agent-skill`. Returns Markdown.
• **Fallback**: Use `fetch_webpage` with query string `from=learn-agent-skill&accept=text/markdown`. Returns Markdown.

Category Index

| Category | Lines | Description | |----------|-------|-------------| | Troubleshooting | L37-L46 | Diagnosing and fixing Foundry classic issues: prompt flow compute, deployments/monitoring, private endpoints, Azure OpenAI (incl. fine-tuning), risks & safety alerts, and known portal bugs. | | Best Practices | L47-L60 | Best practices for designing system/safety prompts, fine-tuning and using GPT/DeepSeek models, optimizing latency/throughput, and evaluating/operating Foundry chat apps in production | | Decision Making | L61-L87 | Guides for choosing models, regions, deployment and billing options, sizing PTU, and planning migrations (Prompt Flow, hubs, APIs) and lifecycle for Foundry and Azure OpenAI workloads. | | Architecture & Design Patterns | L88-L95 | Designing multi-agent architectures, configuring Foundry Agent Service for resilience, and understanding model router behavior, failover, and disaster recovery strategies. | | Limits & Quotas | L96-L111 | Quotas, rate limits, and regional availability for Foundry agents and models (incl. Azure OpenAI/Claude), plus how to monitor, request, and increase deployment and throughput limits. | | Security | L112-L157 | Security, privacy, and compliance for Foundry: auth/RBAC, encryption and keys, network isolation/Private Link, Azure Policy guardrails, content filters/PII, and secure use of tools and models. | | Configuration | L158-L209 | Configuring and monitoring Foundry classic/AI apps: hosts, agents, evaluators, storage, networking, tracing, OpenAI settings, and continuous quality/usage monitoring. | | Integrations & Coding Patterns | L210-L319 | Patterns and code to integrate Foundry/ Azure OpenAI agents and models with tools and data (Search, Bing, SharePoint, MCP, Functions, Logic Apps, LangChain, RAG, fine-tuning, realtime audio, images). | | Deployment | L320-L340 | Deploying Foundry hubs/models with Bicep, CLI, Terraform; using managed/serverless compute; integrating with Azure DevOps/GitHub; upgrading Azure OpenAI; and checking regional availability. |

Troubleshooting

| Topic | URL | |-------|-----| | Troubleshoot Prompt Flow compute session issues in Foundry | https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/prompt-flow-troubleshoot | | Troubleshoot Foundry deployments and monitoring issues | https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/troubleshoot-deploy-and-monitor | | Troubleshoot Foundry private endpoint connection errors | https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/troubleshoot-secure-connection-project | | Troubleshoot Azure OpenAI fine-tuning in Foundry classic | https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/fine-tuning-troubleshoot | | Monitor and troubleshoot Risks & Safety in Foundry | https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/risks-safety-monitor | | Resolve known issues in Microsoft Foundry classic portal | https://learn.microsoft.com/en-us/azure/foundry-classic/reference/foundry-known-issues |

Best Practices

| Topic | URL | |-------|-----| | Design effective system messages for Azure OpenAI | https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/advanced-prompt-engineering | | Apply safety system message templates in Azure OpenAI | https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/safety-system-message-templates | | Author safety system messages for Azure OpenAI | https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/system-message | | Apply safety evaluation when fine-tuning Foundry models | https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/fine-tuning-safety-evaluation | | Fine-tune GPT-4 vision models with