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100+ Free Azure AI Cloud Developer Associate Practice Questions

Pass your Microsoft Certified: Azure AI Cloud Developer Associate (Exam AI-200) exam on the first try — instant access, no signup required.

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Which credential type should a Container App use to read messages from Service Bus without a connection string?

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Key Facts: Azure AI Cloud Developer Associate Exam

$165

Exam Fee (USD)

Microsoft

700/1000

Passing Score

Microsoft

~100 min

Exam Duration

Microsoft (unconfirmed at beta)

40-60

Question Count

Microsoft (typical associate range)

May 2026

Expected Beta Launch

Microsoft

1 year

Credential Validity

Microsoft (free online renewal)

Microsoft lists Exam AI-200 (Azure AI Cloud Developer Associate) as a role-based associate exam delivered through Pearson VUE, with a 700/1000 passing score and a $165 USD fee. The exam is expected to launch in beta in May 2026 and typically presents roughly 40 to 60 questions in about 100 minutes. The four skill areas are Develop containerized solutions on Azure (20-25%), Develop AI solutions by using Azure data management services (25-30%), Connect to and consume Azure services (20-25%), and Secure, monitor, and troubleshoot Azure solutions (20-25%). Question count and exact timing may change at general availability.

Sample Azure AI Cloud Developer Associate Practice Questions

Try these sample questions to test your Azure AI Cloud Developer Associate exam readiness. Each question includes a detailed explanation. Start the interactive quiz above for the full 100+ question experience with AI tutoring.

1Which Azure service stores, versions, and manages container images for an AI inference workload?
A.Azure Blob Storage
B.Azure Container Registry
C.Azure App Configuration
D.Azure Files
Explanation: Azure Container Registry (ACR) is the managed, private registry for building, storing, and versioning Docker container images on Azure. AI-200 expects you to push tagged images to ACR and pull them from compute services such as AKS, Container Apps, and App Service.
2You want to build a container image directly in the cloud without a local Docker daemon. Which feature should you use?
A.Azure Container Registry Tasks
B.Azure DevTest Labs
C.Azure Batch
D.Azure Automation runbooks
Explanation: Azure Container Registry Tasks (ACR Tasks) build, run, and patch container images in the cloud using a quick task or on triggers, with no local Docker engine required. This is the recommended way to build images for AI workloads when you only have ACR access.
3Which compute option provides serverless containers with built-in event-driven autoscaling for AI microservices?
A.Azure Virtual Machines
B.Azure Container Apps
C.Azure Storage queues
D.Azure Logic Apps
Explanation: Azure Container Apps runs containerized microservices serverlessly and includes KEDA-based, event-driven autoscaling, including scale-to-zero. It is well suited to bursty AI inference and background processing workloads on AI-200.
4In Azure Container Apps, which technology powers scaling based on the depth of a Service Bus queue?
A.Horizontal Pod Autoscaler
B.KEDA scalers
C.Azure Monitor autoscale rules
D.Virtual Machine Scale Sets
Explanation: Container Apps uses KEDA (Kubernetes Event-driven Autoscaling) scalers to react to external event sources such as Service Bus queue length, Event Hubs, or HTTP traffic. You define a scale rule referencing the queue, and KEDA adds or removes replicas, including scale-to-zero.
5Which Azure service is best for running large, GPU-accelerated AI inference clusters with full Kubernetes control?
A.Azure Kubernetes Service
B.Azure Functions
C.Azure App Service
D.Azure Spring Apps
Explanation: Azure Kubernetes Service (AKS) gives full Kubernetes control, GPU node pools, and fine-grained scheduling needed for large AI inference and training clusters. AI-200 positions AKS for workloads that need control beyond what Container Apps offers.
6You must deploy a single containerized AI API quickly with minimal orchestration overhead and built-in HTTPS. Which is the simplest fit?
A.Azure App Service for Containers
B.A self-managed Kubernetes cluster on VMs
C.Azure Service Fabric
D.Azure HDInsight
Explanation: Azure App Service for Containers hosts a single container image with managed TLS, scaling, and deployment slots, requiring minimal orchestration. It is the simplest managed host when full Kubernetes is unnecessary.
7Which authentication method should an AKS pod use to pull images from Azure Container Registry without storing credentials?
A.Admin user account with username and password
B.Microsoft Entra workload identity / managed identity
C.A shared access signature token
D.An anonymous pull
Explanation: Using a managed identity or Microsoft Entra workload identity lets AKS authenticate to ACR with no stored secrets and no admin credentials. AI-200 strongly favors managed identity over connection strings, keys, or the registry admin account.
8What does enabling 'scale to zero' on a Container App achieve for an intermittent AI workload?
A.It removes all replicas when there is no demand, reducing cost
B.It permanently deletes the container revision
C.It disables logging to save storage
D.It guarantees a fixed number of warm replicas at all times
Explanation: Scale to zero lets Container Apps remove all running replicas when no events or requests arrive, so you pay nothing for compute during idle periods. KEDA spins replicas back up when traffic returns, which suits intermittent inference jobs.
9Which file in a container image build defines the base image, dependencies, and runtime command?
A.Dockerfile
B.azure-pipelines.yml
C.bicep main file
D.appsettings.json
Explanation: A Dockerfile declares the base image, layered build steps, dependencies, and the entrypoint/command for the container. ACR Tasks and local builds both consume the Dockerfile to produce the image.
10Why use multi-stage builds in a Dockerfile for an AI service?
A.To run the container in multiple regions automatically
B.To produce a smaller final image by discarding build-time dependencies
C.To enable GPU passthrough
D.To encrypt the image layers at rest
Explanation: Multi-stage builds compile or install dependencies in an intermediate stage and copy only the needed artifacts into a lean final image. This reduces image size and attack surface, which speeds pulls and cold starts for inference containers.

About the Azure AI Cloud Developer Associate Exam

Exam AI-200 leads to the Microsoft Certified: Azure AI Cloud Developer Associate credential, validating skills to build, integrate, secure, and operate AI solutions on Azure. The blueprint centers on containerized compute with Azure Container Registry, Container Apps, AKS, and Functions; AI-enabled data services such as PostgreSQL with pgvector, Cosmos DB, Azure AI Search, and Azure Managed Redis; event-driven pipelines with Service Bus, Event Grid, and Event Hubs; and securing, monitoring, and cost-optimizing inference workloads.

Questions

50 scored questions

Time Limit

100 minutes

Passing Score

700/1000

Exam Fee

$165 (Microsoft)

Azure AI Cloud Developer Associate Exam Content Outline

20-25%

Develop containerized solutions on Azure

Build, store, version, and scan images with Azure Container Registry and ACR Tasks; deploy to Azure Container Apps, AKS, App Service, and Functions; and implement KEDA-based event-driven and scale-to-zero patterns for AI inference.

25-30%

Develop AI solutions by using Azure data management services

Store and query embeddings using PostgreSQL with pgvector, Cosmos DB for NoSQL, Azure AI Search, and Azure Managed Redis; apply indexing strategies such as HNSW; and queue back-end work reliably with Azure Service Bus.

20-25%

Connect to and consume Azure services

Call Azure OpenAI for chat completions, function calling, structured outputs, and streaming; consume Azure AI Search and Document Intelligence; authenticate with managed identity and DefaultAzureCredential; and manage secrets in Key Vault behind API Management.

20-25%

Secure, monitor, and troubleshoot Azure solutions

Instrument distributed tracing with Application Insights and OpenTelemetry, query logs with KQL, configure alerts, harden identity and network posture, and optimize inference cost using token metrics and provisioned throughput.

How to Pass the Azure AI Cloud Developer Associate Exam

What You Need to Know

  • Passing score: 700/1000
  • Exam length: 50 questions
  • Time limit: 100 minutes
  • Exam fee: $165

Keys to Passing

  • Complete 500+ practice questions
  • Score 80%+ consistently before scheduling
  • Focus on highest-weighted sections
  • Use our AI tutor for tough concepts

Azure AI Cloud Developer Associate Study Tips from Top Performers

1Practice the Microsoft Entra managed identity flow against Service Bus, Container Registry, Cosmos DB, and Key Vault; on AI-200 answers that rely on connection strings or shared keys are usually wrong.
2Spend the most prep time on data management services, which is the heaviest area at 25-30%, including pgvector, Cosmos DB vector search, Azure AI Search hybrid search, and Service Bus.
3Know when to choose Container Apps versus AKS versus Functions, and how KEDA scale rules and scale-to-zero control both responsiveness and cost.
4Understand RAG building blocks end to end: chunking, embeddings, vector indexing such as HNSW, hybrid plus semantic search, and grounding the model with top-k results.
5Be fluent in observability: Application Insights dependency tracking, OpenTelemetry distributed tracing, KQL in Log Analytics, and alerting through action groups.
6Memorize inference cost levers such as token-usage monitoring, semantic caching in Redis, API Management response caching and quotas, and provisioned throughput for steady workloads.

Frequently Asked Questions

What are the current exam facts for AI-200?

Microsoft lists Exam AI-200 as a role-based associate exam with a 700/1000 passing score and a $165 USD fee, delivered through Pearson VUE. It is expected to launch in beta in May 2026 and typically presents about 40 to 60 questions in roughly 100 minutes.

What does the AI-200 exam measure?

AI-200 validates building, integrating, securing, and operating AI solutions on Azure. The four skill areas are containerized solutions, AI data management services, connecting to and consuming Azure services, and securing, monitoring, and troubleshooting solutions.

Which skill area carries the most weight on AI-200?

Develop AI solutions by using Azure data management services is the largest area at 25-30%, covering vector databases such as PostgreSQL with pgvector, Cosmos DB, Azure AI Search, Azure Managed Redis, and Service Bus queuing.

Does AI-200 replace AZ-204?

Microsoft has positioned AI-200 as a new AI-focused developer certification that overlaps with and is widely seen as a modern successor to AZ-204. Confirm the latest retirement and overlap details on the official Microsoft Learn certification page.

How long is the credential valid?

Microsoft role-based certifications are valid for one year and can be renewed for free through an online assessment on Microsoft Learn before the expiration date.

What is the best way to prepare for AI-200?

Get hands-on with managed identity against Service Bus, Container Registry, Cosmos DB, and Key Vault, since connection-string answers are usually wrong. Then drill vector search, KEDA scaling, and Application Insights observability until each pattern feels routine.