Week 18: Exercises & Checklist

Graded exercises

Easy: Run notebooks/01-foundry-serverless-endpoints.ipynb to completion. It deploys/calls a serverless endpoint, runs the Week 6 bill-of-lading extraction prompt, and prints per-field accuracy plus an estimated cost. Record the printed cost in the Week 18 tracker sheet.
Standard: Run the same extraction prompt against a second deployment (for example a Phi-4 serverless endpoint vs a GPT deployment in Azure OpenAI). Add a markdown cell with a two-row table comparing per-field accuracy and estimated cost, and state in one line which model you would pick for high-volume BoL extraction and why.
Stretch: Put the support-agent endpoint behind the AI Gateway (Azure API Management). Configure a token-rate-limit policy and a content-safety policy, then fire a burst of calls and capture evidence that the rate limit actually throttles. Re-run the evaluation batch behind the gateway and confirm the score did not regress.
Portfolio: Commit a foundry-deployment-guide.md to your fork (setup steps, endpoint call, agent definition, eval trace, cost estimate, gateway config). This is the Microsoft column of the three-cloud comparison matrix you complete in Week 20, keep the "how do I do X here" notes so the matrix writes itself.

Easy: The printed cost is the final TOTAL_ESTIMATED_COST_USD; dry-run still walks the whole pipeline, but the real number requires credentials, don't record a dry-run 0.000 as if it were a measurement.
Standard: Reuse call_openai_sdk with a different deployment= argument; keep the same 4 documents and seed so the two rows are a fair comparison, not two different tests.
Stretch: The rate limit only shows itself under a burst: fire many requests in a tight loop and count the 429/429-equivalent responses as your throttling evidence.
Portfolio: Structure the guide as a "how do I do X here" list (endpoint, agent, eval, gateway, cost), the Week 20 matrix column writes itself from those headings.

[ ] Mon: Set up the Azure subscription and AI Foundry hub/project (free tier).
[ ] Tue: Deploy a serverless model endpoint; call it from the Python SDK and OpenAI SDK.
[ ] Wed: Create the support agent in Foundry with tools; test in the playground.
[ ] Thu: Run an online evaluation batch; read the trace; fix the worst failure.
[ ] Fri: Use case: put the agent behind the AI Gateway (rate limit + content safety); publish cost.
[ ] Sat: Take the Week 18 quiz (quiz.md), pass with 8/10; record the score in Notes.
[ ] Milestone: Update the Excel tracker; commit the Foundry deployment guide.