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| Section | Objectives |
|---|---|
| Secure, monitor, troubleshoot Azure solutions | - Operate AI cloud solutions
|
| Connect to and consume Azure services | - Integrate Azure services
|
| Develop containerized solutions on Azure | - Implement containerized applications
|
| Develop AI solutions by using Azure data management services | - Work with Azure data platforms for AI workloads
|
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質問 # 101
You need to configure a connection string for the partner-facing service according to the technical requirements.
What should you use?
正解：D
解説：
Detailed Explanation: Azure Key Vault references in App Service settings satisfy the requirement to keep secrets out of container images, source control, and directly stored application configuration. App Service resolves the referenced secret at runtime by using the app identity, so the application can consume the value as a normal setting without embedding credentials in the image. GitHub secrets are build/deployment secrets rather than a runtime App Service secret-delivery mechanism. Dockerfile ENV instructions would place secret material in the image configuration and violate the case requirements.
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 | Use Key Vault references for App Service and Functions | Managed identities for Azure resources
質問 # 102
You deploy a production Azure Function app that connects to an Azure SQL Database.
The solution must provide the following functionality:
* Prevent secrets from being exposed in source control.
* Support secret rotation without redeploying the function app.
* Avoid downtime during credential updates.
You need to configure secure and maintainable secret management. What should you configure?
正解：D
解説：
Detailed Explanation: Key Vault references in Function/App Service application settings keep the connection secret outside source control while allowing the platform to resolve it at runtime by identity. When a referenced secret version is not fixed, rotation can be picked up without rebuilding or redeploying the function code. `local.settings.json` is intended for local development and must not be used as a production secret store. A source-controlled parameter file or hard-coded connection string directly violates the security requirement.
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 | Use Key Vault references for App Service and Functions
質問 # 103
You need to improve throughput for concurrent application requests to PostgreSQL.
What should you implement?
正解：A
解説：
The correct solution is to implement connection pooling , ideally by using the built-in PgBouncer capability in Azure Database for PostgreSQL Flexible Server. Connection pooling allows many concurrent application requests to share and reuse a smaller set of established PostgreSQL server connections instead of repeatedly opening and closing database sessions. Microsoft notes that creating a new PostgreSQL connection for each operation consumes server resources because each connection involves its own backend process. Reusing pooled connections therefore reduces connection overhead, lowers CPU and memory consumption, and improves throughput for high-concurrency workloads.
This directly matches Fabrikam ' s stated requirement that database connections support high concurrency with minimal latency through connection optimization . PgBouncer can efficiently multiplex large numbers of client connections onto fewer PostgreSQL connections, particularly in transaction pooling mode.
Increasing max_connections is not the preferred solution because each additional PostgreSQL connection consumes memory and other resources; Microsoft explicitly recommends PgBouncer instead when more concurrent connections are required. Increasing shared_buffers addresses caching and memory allocation rather than connection-management overhead. Read replicas can scale read workloads, but they do not optimize the application ' s connection lifecycle.
Study Guide references: Azure Database for PostgreSQL Flexible Server # connection pooling; PgBouncer; connection management and high-concurrency performance.
質問 # 104
You are creating an Azure Functions app project in your local development environment by using Azure Functions Core Tools.
You must create the project in either Python or C# without using a template.
You need to specify the command and its parameter required to create the Azure Functions app project.
Which command and parameter should you specify? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
* Command: func init
* Parameter: --worker-runtime
Use func init to initialize a new Azure Functions project. Microsoft documents func init as the Azure Functions Core Tools command that creates the project structure in either the current directory or a specified project folder. The command is specifically intended for creating a new Functions application project, whereas func new creates an individual function from a template inside an already initialized project.
The --worker-runtime parameter specifies the language/runtime model for the Functions project. For example, Microsoft documents func init --worker-runtime python for Python projects and func init --worker- runtime dotnet-isolated for modern C#/.NET isolated-worker projects.
--language is not the primary parameter used to establish the Functions worker runtime in this scenario. It can be relevant to certain runtime combinations, such as Node.js, but the Core Tools project initialization examples for Python and C# rely on --worker-runtime. --target-framework is used to select a specific .NET target framework after the worker/runtime model is determined; it does not identify whether the project should be Python or C#.
Therefore, the correct combination is func init + --worker-runtime .
Study Guide references: Azure Functions Core Tools # func init; local Functions project creation; --worker- runtime; Python and .NET isolated worker projects.
質問 # 105
You deploy an API to Azure Container Apps.
The solution must provide the following functionality:
* Support the concurrent activation of multiple application versions.
* Allocate a specific percentage of incoming requests to a secondary version You need to configure revision behavior.
Which configurations should you use? To answer, move the appropriate configurations to the correct requirements. You may use each configuration 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.
正解：
解説：
Explanation:
oncurrent active versions: Multiple revision mode. Route a percentage to the secondary version: Traffic splitting.
Detailed Explanation: Azure Container Apps supports side-by-side application versions through multiple revision mode. Once multiple revisions can be active, ingress traffic can be distributed by percentage across those revisions. This is the required combination for canary or controlled rollout scenarios. Single revision mode deactivates the previous revision as a new one becomes active, while traffic splitting is the specific feature that assigns a percentage of incoming requests to each active revision.
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
質問 # 106
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AI-200関連日本語内容: https://www.passtest.jp/Microsoft/AI-200-shiken.html