Episode 50 — Deploy Safely: Change Management, Rollback Plans, and Guardrail Monitoring (Domain 3)
The deployment phase is the most critical transition in the AI lifecycle, requiring a structured approach to change management to prevent service disruptions. This episode details the steps for a safe deployment, including the use of "canary releases" or "blue-green" deployments to test the new model in a limited capacity before a full rollout. For the AAIR certification, candidates must know how to develop effective rollback plans that allow the organization to quickly return to a previous, stable version of the model if the new deployment fails. We also discuss the implementation of real-time guardrail monitoring that sits between the model and the user to intercept and block unsafe or erroneous outputs immediately upon launch. Best practices include conducting a final "go/no-go" review that verifies all testing and validation steps have been successfully completed. By ensuring a disciplined deployment process, risk professionals can mitigate the operational risks of AI updates and maintain consistent service quality for end-users. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
