Chapter 11 — Azure OpenAI: Tokens, Throughput, and Provisioned Capacity Full Book
"What you need isn't a bigger pipe. You need to understand how Azure OpenAI measures, limits, and bills for capacity."
📖 This chapter is available in the full book
Your team launched an internal GPT-4o chatbot on a Monday. Day one: smooth sailing. Day three: users start reporting "the bot is slow." Day five: 30 percent of requests return HTTP 429 errors. You pull up Azure Monitor and discover you're hitting the 80K TPM quota ceiling. The data science team's response? "Just increase the limit."
But it's not that simple. Quota increases aren't instant, and throwing more TPM at the problem doesn't address the underlying design. Some requests are consuming 4,000 tokens for a question that could be answered in 200. The system prompt alone is 1,800 tokens — copied from a blog post and never trimmed.
By the end of this chapter, you'll speak the capacity planning language of Azure OpenAI as fluently as you speak VM sizing and network bandwidth.
What You'll Learn in This Chapter
- The 429 That Changed Everything
- Token Fundamentals
- Deployment Types — The Critical Decision
- Understanding Throttling
- Capacity Planning
- High-Availability Architecture
- Monitoring Azure OpenAI
- Optimization Techniques