| 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. |