Topexamというサイトは世界的に知名度が高いです。それはTopexamが提供したIT業種のトレーニング資料の適用性が強いですから。それはTopexamのIT専門家が長い時間で研究した成果です。彼らは自分の知識と経験を活かして、絶え間なく発展しているIT業種の状況によってTopexamのMicrosoftのAI-200トレーニング資料を作成したのです。多くの受験生が利用してからとても良い結果を反映しました。もしあなたはIT認証試験に準備している一人でしたら、TopexamのMicrosoftのAI-200「Developing AI Cloud Solutions on Azure」トレーニング資料を選らんだほうがいいです。利用しないのならメリットが分からないですから、速く使ってみてください。
| Section | Objectives |
|---|---|
| Topic 1: Secure, monitor, troubleshoot Azure solutions | - Operate AI cloud solutions
|
| Topic 2: Develop containerized solutions on Azure | - Implement containerized applications
|
| Topic 3: Develop AI solutions by using Azure data management services | - Work with Azure data platforms for AI workloads
|
| Topic 4: Connect to and consume Azure services | - Integrate Azure services
|
最近では、コンピューター支援ソフトウェアを使用してAI-200試験に合格することが新しいトレンドになっています。新しい技術には明確な利点があるため、便利で包括的です。この傾向を追うために、当社の製品はAI-200試験問題を提供しており、従来の方法と斬新な方法を組み合わせて学習することができます。教材の合格率は最大99％です。一度にAI-200認定資格を取得できない場合は、目標に到達して夢が実現するまで、さまざまな割引でAI-200製品を無制限に使用できます。
質問 # 20
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?
正解：B
解説：
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.
質問 # 21
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.
正解：A、B
解説：
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.
質問 # 22
Your team wants to track token usage, latency, and error rates for an Azure OpenAI-backed application in production, with alerting on anomalies. What should you configure?
正解：C
解説：
Azure Monitor, configured via diagnostic settings on the Azure OpenAI resource, collects logs and metrics such as token consumption, latency, and errors, and supports alert rules for anomaly detection in production.
質問 # 23
You have a newly provisioned Azure subscription. You are designing a custom Event Grid workflow for AI inference events.
You need to implement the Event Grid components to support routing of high-confidence events to a downstream processor.
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.
正解：
解説：
Explanation:
Verified answer: 1) Register the Event Grid resource provider; 2) create a custom topic; 3) create an event subscription.
Detailed Explanation: A newly provisioned subscription must have the Event Grid resource provider available before Event Grid resources can be created. The publisher needs a custom topic as the event-ingress resource, and routing to a downstream processor is then defined by an event subscription on that topic. The event subscription can include filters such as event type or data fields so that only high-confidence events reach the processor. Creating a partner topic or domain is unnecessary for the stated custom workflow.
Study Guide Alignment: Azure service integration: Service Bus, Event Grid, Azure Functions triggers
/bindings, and event-driven processing.
Official Microsoft Learn References: AI-200 Study Guide | Create an Event Grid custom topic or domain
質問 # 24
You need to ensure that responses from your Azure OpenAI application include citations back to the specific source documents used, to support user trust and verification. What should you implement?
正解：D
解説：
Citation support requires passing document metadata (source name, page/section) through the retrieval step and prompting the model to reference that metadata explicitly in its answer -- this is a pipeline and prompt design pattern, not a sampling parameter.
質問 # 25
......
Microsoft証明書を取得することは、あなたのキャリアにおける地位を高める素晴らしく迅速な方法です。 AI-200試験に合格するというこの目標を達成するには、外部の支援が必要です。弊社が市場で最も人気のあるベンダーであるため、このリンクをクリックすると幸運です。私たちはこのキャリアに10年以上携わっており、AI-200試験問題では、夢のMicrosoft認定を得るための支援を受けるだけでなく、オンラインで一流のサービスを楽しむことができます。
AI-200試験時間: https://www.topexam.jp/AI-200_shiken.html