Module 17 Wrap-up: Ready for Production
Hands-on: Design a deployment strategy for a mission-critical AI agent.
Module 17 Wrap-up: The Site Reliability Engineer
You have graduated from "Developer" to "Operator." You know that a production AI system is not just code—it's Infrastructure. You have learned how to manage Versions to prevent breaking changes and how to handle Throttling to ensure your users have a smooth experience even under heavy load.
Hands-on Exercise: The Safe Upgrade
1. The Scenario
You have an agent in production (Version 1). You have just written much better instructions in your draft.
2. The Task
Describe the 5 steps to safely upgrade your production users to the new instructions.
- Test the Draft in the console.
- Create Version 2.
- Point the
STAGINGalias to Version 2. - Run automated tests against the
STAGINGalias. - If pass, update the
PRODalias to point to Version 2.
Module 17 Summary
- Versioning: Protecting the stability of your production environment.
- Aliases: Enabling blue-green deployments and rapid rollbacks.
- Throttling: Handling AWS limits gracefully with backoff and jitter.
- Queuing: Decoupling real-time UI from heavy AI processing.
Coming Up Next...
In Module 18, we enter the final chapter: AgentCore. We will learn about this specialized orchestration framework designed for the most complex, long-running, and deterministic enterprise workflows.
Module 17 Checklist
- I can explain the difference between a version and an alias.
- I have created an alias in the Bedrock console.
- I understand how exponential backoff works.
- I know why jitter is important for retries.
- I have identified which parts of my app should be real-time vs queued.