AI-200 Official Practice Test - AI-200 New Test Camp

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Microsoft AI-200 Exam Syllabus Topics:

SectionObjectives
Topic 1: Implement Azure AI solutions- Implement knowledge mining with Azure AI Search
- Implement natural language processing solutions
- Implement computer vision solutions
- Implement generative AI solutions using Azure OpenAI
Topic 2: Plan and manage Azure AI solutions- Plan security and compliance requirements
- Monitor and optimize AI solutions
- Select appropriate Azure AI services
Topic 3: Implement and monitor AI workloads- Deploy AI models and services
- Monitor performance and troubleshoot issues

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Microsoft Developing AI Cloud Solutions on Azure Sample Questions (Q79-Q84):

NEW QUESTION # 79
You plan to create a Docker image that runs an ASP.NET Core application named ContosoApp. You have a setup script named setupScript.psl and a series of application files including ContoscApp.dll.
You need to create a Dockerfile document that meets the following requirements:
* Call SQiupScript.psI when the container is built.
* Run CantosoApp.dill when the container starts.
The Dockerfile document must be created in the same folder where ContosoApp.dll and setupScnpt.ps! are stored.

Answer:

Explanation:

Explanation:


NEW QUESTION # 80
Hotspot Question
A company uses Azure Monitor Application Insights to monitor application behavior, including incoming requests and dependencies.
You must identify failed requests from the last hour. You must also calculate the average duration of failed request dependency calls, grouped by operation name.
You need to analyze telemetry in Application Insights.
Which operators should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Box 1: where
Filter telemetry rows
The where operator filters a table to rows that satisfy a specific predicate. Both box 1 and box 2 require filtering telemetry data to the last hour (timestamp > ago(1h)).
Box 2: where
In the Kusto Query Language (KQL), the where operator filters a table to rows that satisfy a specific predicate or condition. Inside the inner subquery, you need to filter the dependencies telemetry table to only include records from the last hour (timestamp > ago(1)) Box 3: summarize Aggregate calculated data The summarize operator produces a table that aggregates the content of the input table. It is used here with the avg() aggregation function to calculate the average duration grouped by the operation_Name.
Reference:
https://tryhackme.com/room/kqlkustobasicqueries


NEW QUESTION # 81
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.
You are using Azure Monitor Application Insights to investigate a production API. You open the Logs blade and set the time range to Last 24 hours.
An engineer recommends the following query to count requests by result code and sort the results from most frequent to least frequent:
requests
| summarize request_count = count() by resultCode
| order by request_count desc
You need to determine whether the query returns the number of requests grouped by result code and sorted from most to least frequent.
Solution: The result codes are sorted alphabetically.
Does the solution meet the goal?

Answer: A

Explanation:
The solution does not meet the goal because the query does not sort by resultCode. The summarize operator groups request records by each distinct resultCode value and calculates the number of requests in each group by using count().
The resulting table contains a resultCode column and a calculated request_count column. The next statement:
| order by request_count desc
sorts the output by request_count in descending order , which places the most frequently occurring result code first and the least frequent last.
Therefore, the output is sorted by frequency , not alphabetically or numerically by the resultCode field.
If alphabetical sorting by result code were required, the query would instead use a statement such as:
| order by resultCode asc
That is not what the provided query does.
Because the Logs blade is already scoped to the Last 24 hours , the query operates over that selected time range unless additional time filtering is explicitly added.
Study Guide references: Azure Monitor Logs; Application Insights requests table; KQL summarize; count() aggregation; order by; descending sort semantics.


NEW QUESTION # 82
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.

Answer:

Explanation:

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


NEW QUESTION # 83
An AI platform uses App Configuration for feature flags and endpoint routing.
The platform stores secrets alongside configuration data and does NOT support dynamic configuration refresh.
You need to redesign the configuration approach so that:
configuration supports dynamic refresh;
secrets are stored outside App Configuration;
the application can securely access both App Configuration and Key Vault.
You need to enable secure dynamic configuration management for the platform.
Which three actions should you perform? Each correct answer presents part of the solution. Choose three.
NOTE: Each correct selection is worth one point.

Answer: A,D,E

Explanation:
Detailed Explanation: The original answer omitted the secret-storage requirement. API keys and other secrets should be held in Key Vault, while App Configuration should retain non-secret configuration and Key Vault references. Dynamic refresh is implemented through the App Configuration refresh/polling mechanism rather than requiring an application restart. Managed identity provides credential-free access to both services in Azure. Environment variables do not provide centralized dynamic refresh, and a stored service-principal secret creates exactly the credential-management problem the design is intended to eliminate.
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 | Dynamic configuration in ASP.NET Core | Use Key Vault references in App Configuration | Managed identities for Azure resources


NEW QUESTION # 84
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