Lilly Tech Systems
Learn Azure OpenAI Infrastructure
Master the infrastructure behind Azure OpenAI Service. Learn deployment patterns, scaling strategies, PTU vs Pay-As-You-Go pricing, and enterprise networking for production GPT-4 and foundation model workloads.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
Azure OpenAI Service overview, available models, and the infrastructure architecture behind the service.
2. Deployment
Create deployments, configure model versions, manage quotas, and set up multi-region architectures.
3. Scaling
Rate limits, token-per-minute quotas, load balancing, and strategies for handling traffic spikes.
4. PTU vs PayGo
Compare Provisioned Throughput Units and Pay-As-You-Go pricing for different workload patterns.
5. Networking
Private Endpoints, VNet integration, API Management, and secure enterprise connectivity patterns.
6. Best Practices
Production readiness, monitoring, content filtering, disaster recovery, and governance for Azure OpenAI.
What You'll Learn
By the end of this course, you'll be able to:
Deploy Models
Create and manage Azure OpenAI deployments with proper quotas, versions, and multi-region failover.
Scale for Production
Handle production traffic with rate limiting, load balancing, and provisioned throughput strategies.
Optimize Costs
Choose between PTU and Pay-As-You-Go pricing based on your workload patterns and budget.
Secure Access
Implement enterprise networking with Private Endpoints, APIM, and content safety controls.