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Last Updated: Sep 18, 2026
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Microsoft AI-200 Practice Q&A's
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Most candidates don't fail the AI-200 exam because they skipped studying — they fail because their material was stale or shallow. ActualTestsQuiz keeps its Microsoft Developing AI Cloud Solutions on Azure questions current with the live exam, so your effort lands where it counts in 2026.
Microsoft AI-200 Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Developing AI Cloud Solutions on Azure |
| Exam Number: | AI-200 |
| Related Certifications: | Microsoft Certified: Azure AI Cloud Developer Associate |
| Exam Format: | Multiple Choice, Hands-on/Performance-based Items, Proctored Exam, Interactive Questions, Case Study |
| Exam Duration: | 100 minutes |
| Passing Score: | 700 |
| Available Languages: | English |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored or test center delivery through Pearson VUE. |
| Pre Condition: | Candidates should have experience with Python programming, Azure services, Azure data management services, Azure monitoring, Azure messaging and eventing, vector databases, and containerized applications. No mandatory prerequisite exam is required. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-cloud-developer-associate/ |
Microsoft AI-200 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Develop containerized solutions on Azure | - Implement containerized applications
|
| Secure, monitor, troubleshoot Azure solutions | - Operate AI cloud solutions
|
| Develop AI solutions by using Azure data management services | - Work with Azure data platforms for AI workloads
|
| Connect to and consume Azure services | - Integrate Azure services
|
AI-200 Exam Questions and Answers
Candidates should have experience with Python programming, Azure services, Azure data management services, Azure monitoring, Azure messaging and eventing, vector databases, and containerized applications. No mandatory prerequisite exam is required. Keep in mind that vendors adjust their requirements over time, so verify the current rules on the official exam page (AI-200 official exam details) before you schedule anything.
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Per the official blueprint, the Microsoft Developing AI Cloud Solutions on Azure is organized into 4 domains — among them Develop containerized solutions on Azure, Develop AI solutions by using Azure data management services, Connect to and consume Azure services. The weights show where the exam spends its questions, so let them guide your study hours. The full domain-and-subtopic breakdown is in the outline section above.
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The Microsoft Developing AI Cloud Solutions on Azure is the vendor's official exam for the Azure AI Engineer Associate certification, a credential at the Associate level. It is widely recognized because it verifies genuine, job-ready skill — exactly what employers shortlist for. It also connects to related credentials including Microsoft Certified: Azure AI Cloud Developer Associate, which makes it a solid anchor for a longer certification roadmap.
Microsoft Developing AI Cloud Solutions on Azure Sample Questions:
You have two Azure Container Registry (ACR) instances: ACR01 and ACR02.
You plan to implement a containerized application named APP1 that will use a base image named BASE1.
The image for APP1 will be stored in ACR01. The image BASE1 will be stored in ACR02.
You need to automate the planned implementation by using a sequence of five Azure command-line interface (Azure CLI) commands. Your solution must ensure that the APP1 image stored in ACR01 will be automatically updated when the BASE1 image is updated.
In which order should you arrange the commands to develop the solution? To answer, move all commands from the list of commands to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
Correct Answer:
Explanation:
An AI application uses a database. The database credential rotates every 30 days.
The application currently requires a manual update each time the credential rotates.
You need to ensure that the application always uses the latest secret version without manual updates.
Which two actions should you perform? Each correct answer presents part of the solution. Choose two.
NOTE: Each correct selection is worth one point.
- A. Retrieve secrets by specifying a version identifier.
- B. Retrieve secrets without specifying a version identifier.
- C. Cache the secret for 30 days.
- D. Configure a Key Vault rotation policy.
Correct Answer: B,D 🗳️
Hotspot Question
You have an Azure Functions app using the Consumption hosting plan for a company. The app contains the following functions:
You plan to enable dynamic concurrency on the app. The company requires that each function has its concurrency level managed separately.
You need to configure the app for dynamic concurrency.
Which file or function names should you use? To answer, select the appropriate values in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
* File name: host.json
* Function name: f3
Azure Functions dynamic concurrency is enabled at the function-app host level in the host.json file . The concurrency configuration section contains the dynamicConcurrencyEnabled property. Setting this value to true enables the Functions host to dynamically learn and adjust concurrency levels for supported triggers rather than requiring fixed manual limits.
Although dynamic concurrency is enabled globally, Microsoft explicitly states that the learned concurrency level is managed independently for each individual function . This allows a resource-intensive function to operate at a lower concurrency level while a lightweight function in the same app can execute with greater concurrency, protecting host health while maximizing throughput.
Of the functions listed, f3 , which uses an Azure Queue Storage trigger , supports dynamic concurrency.
Microsoft currently documents dynamic concurrency support for Azure Queue Storage, Azure Blob Storage, and Azure Service Bus triggers , subject to the required extension versions. HTTP and Timer triggers do not participate in this dynamic-concurrency model.
Therefore, configure dynamic concurrency in host.json , and f3 is the function whose concurrency will be dynamically managed.
Study Guide references: Azure Functions # Concurrency; Dynamic concurrency; host.json; Queue Storage trigger concurrency.
You are developing a .NET application that uses Azure Cosmos DB for NoSQL to store application data The application uses the Azure Cosmos DB for NoSQL SDK to interact with the database account. The application must perform the following tasks
* Initialize the connection by using the account endpoint and key.
* Define shared throughput.
* Perform create, read, update, and delete (CRUD) operations on items stored in a container
Correct Answer:
Explanation:
Verified Answer: Initialize connection: CosmosClient. Define shared throughput: Database. Perform item CRUD: Container.
Detailed Explanation: The Cosmos DB SDK follows the service resource hierarchy. CosmosClient represents the account connection and is initialized with the account endpoint and credential. Shared throughput is configured at the database level when multiple containers share database throughput. Item create, read, update, and delete operations are performed through a container object because containers hold items and define partitioning/indexing behavior. An indexing policy is configuration attached to a container, not the SDK object used for CRUD.
Study Guide Alignment: AI data-management workloads: Cosmos DB, PostgreSQL, caching, vector storage, vector retrieval, consistency, and connection optimization.
Official Microsoft Learn References: AI-200 Study Guide | Cosmos DB databases, containers, and items
You need to deploy a batch retraining workload.
How should you complete the scaling configuration? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
* Trigger scaling based on queue depth: Azure Service Bus scaler
* Deallocate instances when the message queue is empty: Minimum replicas = 0
* Prevent uncontrolled burst scaling: Maximum replicas = 10
The batch retraining workload must scale according to queue length , so the correct KEDA trigger is the Azure Service Bus scaler . KEDA integrates with Azure Service Bus and monitors queue or subscription metrics, allowing AKS workloads to scale according to the number of pending messages rather than CPU utilization or HTTP request concurrency. Microsoft documents KEDA as the event-driven autoscaling mechanism for AKS and specifically supports Azure-based scalers for queue-driven workloads.
To meet the requirement to deallocate workload instances when no messages remain, configure minimum replicas = 0 . KEDA supports scale-to-zero for event-driven workloads, which is particularly appropriate for intermittent batch or machine-learning processing because no pods need to remain running while the queue is empty. Microsoft specifically identifies scale-to-zero as a KEDA capability and recommends it for sporadic ML workloads where cost optimization is important.
Finally, configure maximum replicas = 10 . A finite maximum replica count establishes an explicit upper scaling boundary, preventing large queue bursts from creating an uncontrolled number of worker replicas and protecting both infrastructure cost and downstream services.
Study Guide references: AKS # KEDA; Azure Service Bus event-driven scaling; minReplicaCount; maxReplicaCount; scale-to-zero; autoscaling limits.
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