자신을 부단히 업그레이드하려면 많은 노력이 필요합니다. IT업종 종사자라면 국제승인 IT인증자격증을 취득하는것이 자신을 업그레이드하는것과 같습니다. Microsoft인증 AI-200시험을 패스하여 원하는 자격증을 취득하려면PassTIP의Microsoft인증 AI-200덤프를 추천해드립니다. 하루빨리 덤프를 공부하여 자격증 부자가 되세요.
| Section | Objectives |
|---|---|
| Plan and manage Azure AI solutions | - Plan security and compliance requirements - Select appropriate Azure AI services - Monitor and optimize AI solutions |
| 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 |
| Implement and monitor AI workloads | - Deploy AI models and services - Monitor performance and troubleshoot issues |
Microsoft AI-200시험을 어떻게 패스할가 고민그만하시고 PassTIP의Microsoft AI-200시험대비덤프를 데려가 주세요. 가격이 착한데 비해 너무나 훌륭한 덤프품질과 높은 적중율은 PassTIP가 아닌 다른곳에서 찾아볼수 없는 혜택입니다. Microsoft AI-200 덤프구매전 데모부터 다운받아 공부해보세요.
질문 # 140
You are developing several microservices to run on Azure Container Apps.
The microservices must allow HTTPS access by using a custom domain.
You need to configure the custom domain in Azure Container Apps.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
정답：
설명：
Explanation:
Verified Answer: 1) Enable ingress; 2) add the required DNS records; 3) validate ownership of the custom domain; 4) add the custom domain to the Container App; 5) bind the certificate.
Detailed Explanation: A custom HTTPS hostname requires an ingress endpoint, DNS proof that the requester controls the hostname, the hostname association itself, and a TLS certificate bound to that hostname.
DNS records must exist before ownership validation can succeed. Once ownership is validated, the domain can be associated with the Container App and the certificate can be bound to provide HTTPS. Skipping ingress or DNS validation would prevent the hostname from being correctly routed and secured.
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 | Custom domains and certificates in Container Apps
질문 # 141
You are investigating high latency in an AI search application that processes millions of requests daily.
Telemetry is stored in Azure Monitor Logs.
You must create a KQL query that correlates information from the AppRequests table and the AppDependencies table. The query must meet the following requirements:
* Include only data from the last 24 hours.
* Filter for failed requests only.
* Calculate the average duration of dependencies, grouped by operation.
The query must follow best practice to optimize the performance by minimizing the initial data scan.
You need to create the query.
In which order should perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
정답：
설명：
Explanation:
Verified Answer: 1) Select the requests table; 2) apply the 24-hour time filter; 3) filter failed requests; 4) join the dependencies table; 5) summarize average dependency duration by operation.
Detailed Explanation: KQL performs best when high-selectivity filters are applied as early as possible, especially the time predicate that limits the amount of data scanned. Starting from AppRequests, restricting to the last 24 hours, and then filtering failures reduces the left-side dataset before the join. The dependency table is then correlated with those requests, and aggregation is performed last to calculate average dependency duration by operation. Joining or summarizing before the time and failure filters would process more data than necessary.
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 | Optimize log queries in Azure Monitor
질문 # 142
An Azure Storage Blob upload must trigger backend processing.
The solution must:
* Avoid polling.
* Minimize latency.
* Trigger automatically when the upload occurs.
You need to ensure that processing starts as soon as a file is uploaded.
Which trigger should you implement?
정답：A
설명：
Use an Azure Event Grid trigger for event-driven processing of new blob uploads. Azure Blob Storage can publish events such as Microsoft.Storage.BlobCreated to Event Grid, which then pushes the event to the subscribed Azure Function or other event handler. This eliminates the need for the application to periodically scan the storage container for changes.
Microsoft distinguishes traditional polling-based Blob triggers from event-driven Blob/Event Grid processing . Event Grid-based processing provides low-latency, near-real-time delivery and supports high- scale workloads. Microsoft specifically notes that the Event Grid source eliminates polling delays and can process newly created blobs within seconds of upload.
A Timer trigger would explicitly introduce polling on a schedule. A Queue Storage trigger requires another component to place a message in a queue when the blob arrives, so it is not the direct event source described.
An HTTP trigger requires an external caller to invoke the function and therefore does not automatically react to a Blob Storage creation event.
Therefore, Event Grid is the correct trigger for automatic, low-latency, non-polling blob processing.
Study Guide references: Azure Functions # Event Grid triggers; Azure Blob Storage events; event-driven Blob processing; BlobCreated events; near-real-time processing.
질문 # 143
You are designing an Azure Function app that processes large image uploads submitted by users through an HTTP endpoint.
The solution must:
* Prevent client timeouts by decoupling image processing from the initial upload request.
* Support automatic retry behavior for failed processing attempts.
* Scale the background processing independently of the rate of incoming HTTP uploads.
You need to design a scalable and reliable asynchronous processing solution.
Which two actions should you implement? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
정답：B,D
설명：
The correct architecture uses an Azure Storage queue as an asynchronous buffer between the HTTP ingestion path and the computationally expensive image-processing workload. The HTTP-triggered function should accept the upload, enqueue a work message, and return promptly rather than waiting for image processing to finish. Microsoft specifically recommends asynchronous patterns for long-running HTTP operations because an HTTP-triggered Azure Function can encounter the Azure Load Balancer response timeout even though the underlying function continues executing.
A queue-triggered function then performs image processing independently. Azure Functions applies target- based scaling to Azure Queue Storage triggers based on queued workload, allowing worker capacity to expand as the backlog increases rather than being directly tied to HTTP arrival processing.
For reliability, Azure Queue-triggered Functions provide retry behavior. The visibilityTimeout setting controls the delay before a failed message becomes available for another attempt, while maxDequeueCount controls how many processing attempts occur before the message is transferred to the < queue-name > - poison queue. The default maximum is five attempts.
C defeats the asynchronous requirement. D can be useful for tracking upload state, but it does not itself provide workload decoupling, retry handling, or queue-driven scaling.
Study Guide references: Azure Functions # Queue Storage triggers and bindings; event-driven scaling; retry
/poison queue behavior; asynchronous HTTP processing.
질문 # 144
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. The API key must not be stored in application configuration directly. The API key must be accessed securely from Azure Key Vault.
You need to ensure that the API key is stored securely in Azure Key Vault and is available to the container at runtime without being exposed in source control or Git commit history.
Solution: Store the API key as a GitHub repository secret.
Does the solution meet the goal?
정답：A
질문 # 145
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Microsoft AI-200시험은 PassTIP 에서 출시한Microsoft AI-200덤프로 도전하시면 됩니다. Microsoft AI-200 덤프를 페펙트하게 공부하시면 시험을 한번에 패스할수 있습니다. 구매후 일년무료 업데이트 서비스를 제공해드리기에Microsoft AI-200시험문제가 변경되어도 업데이트된 덤프를 받으면 가장 최신시험에 대비할수 있습니다.
AI-200최신 시험대비자료: https://www.passtip.net/AI-200-pass-exam.html