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Microsoft AI-200 Exam Syllabus Topics:

Microsoft Developing AI Cloud Solutions on Azure Sample Questions:

1. Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
You plan to deploy a container to an Azure App Service API app named api1. You host the source code for api1 in a GitHub repository. The container uses the API key at runtime to connect to a backend service.
The container must be able to retrieve the API key at runtime without exposing it in the source repository or Git commit history.
You need to ensure that the API key remains outside of Git commit history and is available to the container at runtime.
Solution: Store the API key in Azure Key Vault and reference it from an App Service application setting.
Does the solution meet the goal?

A) Yes
B) No

2. A large retail company operates online and physical stores. The company tracks inventory levels in real time to manage stock efficiently across all locations. You develop an Azure Event Grid solution to handle events generated by the inventory management system deployed to Azure.
You need to implement a subscription filter that dynamically adjusts to seasonal changes in product demand.
Which event filter should you use?

A) A static subject filter that targets events with a subject ending in "/seasonal/inventory"
B) An advanced filter using a Boolean condition that evaluates multiple data fields, including a season field within the event data
C) A subscription filter that uses a label filter to include events tagged with seasonal promotional codes
D) A prefix filter on the event type field that matches the current season's name

3. Your organization requires that all prompts and completions sent to Azure OpenAI be retained for zero data logging beyond what's required for abuse monitoring, per contractual requirements.
What should you do?

A) Disable Azure Monitor entirely
B) Use a lower model version
C) Store all data only in Cosmos DB
D) Request modified content filtering / abuse monitoring configuration through Microsoft for the resource

4. Case Study 2 - Proseware Inc.
Background
Proseware Inc. develops AI-powered knowledge management solutions for enterprise customers.
The company is modernizing its platform to support semantic search, intelligent document retrieval, and real-time partner integrations.
The engineering team uses Python and Azure SDKs. The architecture is being redesigned to support containerized microservices, vector search workloads, and serverless backend processing.
Planned Application Architecture
Microservices are containerized by using Docker.
Code for containerized microservices and Azure Function apps is developed locally but stored in a GitHub repository.
Custom images for containerized microservices are stored in Azure Container Registry (ACR).
Base images are stored in Docker Hub. Custom images must be rebuilt automatically whenever their base images are updated.
Azure Cosmos DB for NoSQL stores documents, metadata, and vector embeddings.
Azure Functions generate vector embeddings of Azure Cosmos DB for NoSQL-hosted documents and send messages to Service Bus to trigger search index updates.
Azure Container Apps (ACA) apps host backend API services that provide semantic search across Azure Cosmos DB for NoSQL documents. API services process Service Bus messages and update search indexes.
Azure Kubernetes Service (AKS) processes batch vector embedding regeneration for existing Azure Cosmos DB for NoSQL documents (whenever the embedding model is changed).
An extranet-facing containerized webhook allows business partners to submit documents to be processed by internal AI workflows for semantic search and retrieval.
Monitoring
Telemetry generated by Azure resources is sent to Azure Monitor.
A Log Analytics workspace is used to collect ACA apps logs, AKS container logs, and Azure Functions apps logs.
Monitoring of Azure Functions is currently implemented by using Azure Application Insights SDK instrumentation.
Business Requirements
Embeddings for new or updated Azure Cosmos DB for NoSQL-hosted documents must be automatically generated.
Backend API services must scale automatically during business hours.
Cold start delay of backend APIs must be minimized.
Secrets must be stored outside of container images.
Developers must be able to correlate telemetry across Azure Functions hosts and apps.
All tracing must be implemented by using OpenTelemetry SDK instrumentation.
Development efforts must be minimized.
Technical Requirements
Container images must be built automatically and validated before code updates are merged into the main branch.
Image build automation must run inside the Azure Container Registry, eliminating dependency on local developer machines and external build services.
Dependency of image builds on local developer machines must be eliminated.
Event-driven scaling in ACA must occur based on the number of pending messages in the Azure Service Bus queue.
Azure Cosmos DB for NoSQL RU consumption must be minimized.
Vector similarity search must use embeddings stored in Azure Cosmos DB for NoSQL.
The partner-facing containerized webhook service must run on Azure App Service.
Secrets must NOT be stored in container images, source control, or application configuration directly. They must be accessed securely at runtime.
All secrets must be stored centrally in Azure Key Vault and accessed at runtime through a managed identity.
Azure App Service must supply secrets at runtime without relying on external services.
Resources and workloads must be deployed by using Bicep templates through an automated, version-controlled pipeline. Local and command-line deployments must be eliminated to ensure repeatable, auditable deployments.
Known Issues
RU consumption spikes during vector similarity queries.
Drag and Drop Question
You need to configure event-driven scaling for the backend API services to meet the technical requirements.
Which settings should you use for each element? To answer, move the appropriate settings to the correct elements. You may use each setting once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

5. Hotspot Question
You are developing several microservices to run on Azure Container Apps. External HTTP ingress traffic has been enabled for the microservices.
A deployed microservice must be updated to allow users to test new features. You have the following requirements:
- Enable and maintain a single URL for the updated microservice to
provide to test users.
- Update the microservice that corresponds to the current microservice
version.
You need to configure Azure Container Apps.
Which features should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Solutions: