Azure OpenAI Service: Production Architecture and Cost Optimization скачать в хорошем качестве

Azure OpenAI Service: Production Architecture and Cost Optimization

In this deep dive, we cover everything that is needed to deploy Azure OpenAI Service in production environments. We cover the architectural decisions, security configurations, and cost management strategies that separate prototype implementations from enterprise-ready systems. ================ What you will learn: ================ Resource Provisioning & Setup Creating Azure OpenAI resources with proper region selection Model deployment strategies and version management Understanding TPM quota allocation across deployments Authentication & Security API key vs Azure AD authentication comparison Implementing managed identities for zero-credential architecture Private endpoints and VNet integration RBAC configuration and audit logging Cost Management Strategies Understanding Azure OpenAI pricing structure (tokens, models, regions) Prompt engineering for 60% cost reduction Intelligent model routing between GPT-4 and GPT-3.5-Turbo Response caching implementation with Redis Strategic max token configuration by use case Streaming responses for cost and latency optimization Quota Management & Rate Limiting Allocating TPM quota across production and development deployments Implementing exponential backoff for 429 errors Queue-based request handling for high-volume scenarios Monitoring & Observability Configuring Azure Monitor diagnostic settings Building cost dashboards with KQL queries Setting up automated alerts for budget overruns Tracking token usage, latency, and error rates Production Best Practices Multi-region deployment architecture Request timeout configuration by use case Content filtering policies and customization Complete production architecture with caching, routing, and monitoring Migration Path & Common Pitfalls 5-phase migration from prototype to production (4-6 week timeline) Avoiding quota planning mistakes Regional selection considerations Secret management with Key Vault =========== Timestamps: =========== 00:00 - Introduction: Azure OpenAI Service Production Setup & Cost Management 00:41 - Why Azure OpenAI Service? 02:33 - Azure OpenAI Architecture Overview 03:44 - Resource Provisioning - Part 1 05:06 - Resource Provisioning - Part 2 06:18 - Model Deployment Strategy 08:12 - API Configuration - Authentication 09:54 - Making Your First API Call 11:29 - API Configuration Flow 12:41 - Security Best Practices - Part 1 (Network Security & Identity) 14:30 - Security Best Practices - Part 2 (Zero-Trust Architecture) 15:48 - Cost Structure Overview 17:33 - Cost Management Architecture 19:06 - Cost Optimization Strategy 1: Prompt Engineering 21:10 - Cost Optimization Strategy 2: Model Selection 23:11 - Cost Optimization Strategy 3: Response Caching 25:12 - Response Caching Implementation 26:57 - Cost Optimization Strategy 4: Token Limits 28:42 - Cost Optimization Strategy 5: Streaming Responses 30:05 - Streaming Implementation 31:34 - Quota Management 33:27 - Handling Rate Limits 35:28 - Monitoring Setup - Part 1 (Diagnostic Settings & Storage) 37:15 - Monitoring Setup - Part 2 (Analytics Flow) 38:32 - Cost Monitoring Query Examples 40:10 - Building Cost Dashboards 42:13 - Alert Configuration Example 43:20 - Production Best Practices - Part 1 (Multi-Region Deployments) 44:54 - Production Best Practices - Part 2 (Request Timeout) 46:32 - Production Best Practices - Part 3 (Content Filtering) 48:15 - Production Architecture Example 49:35 - Migration Path from Prototype to Production 50:46 - Migration Path (Continued) & Optimization 52:18 - Common Pitfalls to Avoid 54:00 - Key Takeaways 55:44 - Next Steps & Resources ========= About me: ========= I'm Mukul Raina, a Senior Software Engineer and Tech Lead at Microsoft, with a Master's in Computer Science from the University of Oxford. On this channel, I create technical deep dives on System Design and ML/AI architectures #AzureOpenAI #CloudArchitecture #CostOptimization #EnterpriseAI #MicrosoftAzure #ProductionDeployment