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| Section | Objectives |
|---|---|
| Plan and manage Azure AI solutions | - Select appropriate Azure AI services - Plan security and compliance requirements - Monitor and optimize AI solutions |
| Implement and monitor AI workloads | - Deploy AI models and services - Monitor performance and troubleshoot issues |
| Implement Azure AI solutions | - Implement computer vision solutions - Implement natural language processing solutions - Implement generative AI solutions using Azure OpenAI - Implement knowledge mining with Azure AI Search |
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NEW QUESTION # 113
You plan to deploy an Azure Container Apps app named App1. App1 will use an access key to connect to a backend API.
The solution must store the key outside of the App1 environment and minimize maintenance efforts.
You need to configure secure key storage for App1.
Which configurations should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
* Provide the key storage for App1: Azure Key Vault secret
* Secure App1 access to the key storage: Managed identity
An API access key is a sensitive string value, so it should be stored as an Azure Key Vault secret , not as an Azure Key Vault cryptographic key. Azure Container Apps supports direct Key Vault secret references , allowing sensitive values to remain centrally stored outside the container app rather than being embedded in images or supplied directly as Container Apps secret values. Microsoft recommends Key Vault references for production secrets because they provide centralized lifecycle management and avoid placing secret values directly in application configuration.
App1 should authenticate to Key Vault by using a managed identity . Azure Container Apps supports both system-assigned and user-assigned managed identities, enabling the workload to obtain Microsoft Entra tokens without maintaining client secrets or credentials. The identity must be granted appropriate Key Vault permissions, such as the Key Vault Secrets User RBAC role, to retrieve the stored secret.
This configuration also minimizes maintenance. When the Key Vault reference omits a specific secret version, Container Apps uses the latest version and automatically detects newer versions, retrieving the updated value within approximately 30 minutes.
Therefore, the required combination is Azure Key Vault secret + Managed identity .
Study Guide references: Azure Container Apps # secrets management; Key Vault references; managed identities; secret rotation and runtime retrieval.
NEW QUESTION # 114
You are using the Python SDK to develop a containerized AI application that retrieves the value of a runtime setting stored in an Azure App Configuration resource. The application will run in Azure in the security context of a managed identity.
The application must work in a local development environment without any code changes.
You need to complete the code that implements the retrieval.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Verified answer: var1 = DefaultAzureCredential(); retrieval call = get_configuration_setting(...).
Detailed Explanation: DefaultAzureCredential is designed to support the same application code across local development and Azure-hosted environments. Locally it can use developer credentials, while in Azure it can use the workload's managed identity. The App Configuration client's get_configuration_setting method retrieves a specific key/label pair, which matches the code shown. Using ManagedIdentityCredential directly would not provide the same local-development credential chain without code or environment-specific handling.
Study Guide Alignment: Security and operations: Key Vault, App Configuration, managed identity, OpenTelemetry, Azure Monitor, and KQL-based troubleshooting.
Official Microsoft Learn References: AI-200 Study Guide | Azure App Configuration Python client | Managed identities for Azure resources
NEW QUESTION # 115
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.
Answer:
Explanation:
Explanation:
Verified Answer: Single URL for test users: Revision label. Current microservice activation behavior:
Revision mode.
Detailed Explanation: Azure Container Apps revision labels provide a stable label-specific URL that can be reassigned to a different revision, which is appropriate for a consistent test endpoint. Revision mode controls whether one or multiple revisions can be active at the same time and therefore governs how the current and updated application versions are activated. The container image and registry identify what is deployed, but they do not provide the stable test URL or the application-level revision activation behavior requested.
Study Guide Alignment: Containerized Azure workloads: registry builds, App Service containers, Container Apps revision/scaling behavior, and AKS deployment choices.
Official Microsoft Learn References: AI-200 Study Guide | Azure Container Apps revisions | Azure Container Apps revision labels
NEW QUESTION # 116
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.
You need to configure Azure Functions to generate vector embeddings according to planned environment application architecture.
Which trigger type should you use?
Answer: A
Explanation:
The most appropriate trigger type for this architecture is the Azure Cosmos DB Trigger.
This trigger monitors your NoSQL container's underlying change feed. When a document is created or modified, the function fires automatically, processes the data, generates the embedding, and places a message in Azure Service Bus.
Scenario, Planned Application Architecture
Azure Functions generate vector embeddings of Azure Cosmos DB for NoSQL-hosted documents and send messages to Service Bus to trigger search index updates.
Reference:
https://learn.microsoft.com/en-us/azure/cosmos-db/integrated-embeddings
NEW QUESTION # 117
You are deploying an AI service to Azure Container Apps.
The service must retrieve secrets securely from Key Vault by using managed identity.
You need to configure secure access.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
NEW QUESTION # 118
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