Design the ALM Process for AI-powered Business Solutions AB-100 Practice Questions (Page 7)

Questions 31–35

1. 31application · medium

   A team manages multiple Microsoft Foundry Agents that use custom AI models. They want to implement a CI/CD pipeline that automatically deploys agent updates to a staging environment, runs validation tests, and then promotes to production only if tests pass. What should you include in the pipeline?

   • AA manual process where developers copy agent files to production servers.
   • BA build stage that packages the agent definition and model version, a test stage that runs automated validation, and a release stage that deploys to staging and then production.
   • CA single stage that deploys directly to production and relies on manual monitoring.
   • DA script that updates the model in production without versioning.
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2. 32expert · hard

   A company uses Microsoft Foundry Agents that depend on a dataset stored in Azure Data Lake. The dataset is updated by multiple teams, and each update can change the schema. The company needs to ensure that agents are not broken by schema changes and that updates are traceable. What should you implement?

   • AA schema registry that validates changes and a dataset versioning system that agents reference
   • BA manual approval process for all dataset changes
   • CA shared dataset that is overwritten with each update
   • DA notification system that alerts agents when the schema changes
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4. 33foundation · easy

   What is the primary purpose of an ALM process for Copilot Studio agents?

   • ATo manage the lifecycle of agent configurations, connectors, and actions across environments
   • BTo automatically generate new agent responses without human intervention
   • CTo replace the need for testing agents by using automated deployment
   • DTo ensure that agents are deployed only to production and never to lower environments
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5. 34foundation · easy

   What is the primary purpose of designing a data ALM process for AI-powered business solutions?

   • ATo replace the need for a separate application ALM process by combining all artifacts into a single pipeline
   • BTo ensure that all data used by AI models is stored in a single cloud data warehouse
   • CTo manage versioning, validation, and promotion of datasets used by AI models and agents across environments
   • DTo automate the creation of new datasets without human review or approval
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6. 35expert · hard

   A team manages Microsoft Foundry Agents that use custom AI models. The models are updated frequently, but the agents have a service-level agreement (SLA) that requires 99.9% uptime. They need to deploy model updates without violating the SLA. What should you do?

   • ATake all agents offline, update them, and bring them back online.
   • BSchedule a maintenance window where the agents are unavailable.
   • CDeploy the model update to all agents simultaneously during off-peak hours.
   • DUse a rolling deployment strategy that updates agents in batches, ensuring that a portion of the agents remain available during the update.
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