AI-103 Practice Test 10 — 10 Questions

Question 1

You are developing an application that uses the Azure AI Language REST API for text analysis. Which TWO requirements must be met when constructing HTTP requests to the service? (Choose two.)

Accepted Answer

Set the 'Content-Type' header to 'application/json'.. Option C is correct because the Azure AI Language REST API expects request bodies in JSON format, so the 'Content-Type' header must be set to 'application/json' for the service to correctly parse the payload. Option E is correct because the service authenticates requests using the 'Ocp-Apim-Subscription-Key' header, which must contain a valid API subscription key for the request to be authorized. Option A is incorrect because the API uses JSON, not XML, for request payloads. Option B is incorrect because authentication does not use a master account password in the query string; the subscription key is passed in the header. Option D is incorrect because the service does not rely exclusively on HTTP Basic Authentication with username and password; it uses the subscription key header.

Answer

Format all request payloads as XML documents.

Answer

Include the master account password in the request query string.

Answer

Authenticate exclusively using HTTP Basic Authentication with username and password.

Question 2

Which component in Azure AI Foundry allows you to visualize and debug the execution path of a model call, including input/output mapping?

Accepted Answer

Prompt Flow. Prompt Flow in Azure AI Foundry is the orchestration and authoring tool that lets you build flows as DAGs of nodes (LLM, Python, prompt, tool) and visually inspect each node's inputs/outputs, execution time, and token usage. It is purpose-built for debugging and tracing the execution path of a model call, including input/output mapping between nodes.

Answer

Compute Instance

Answer

Model Benchmarks

Answer

Deployment Endpoint

Question 3

You are designing an enterprise text analysis solution with high availability and security requirements. Which THREE practices should you implement? (Choose three.)

Accepted Answer

Implement exponential backoff retry logic in client applications to handle rate limiting (429 errors).. Option B is correct because Azure AI services enforce rate limits and return HTTP 429 (Too Many Requests) responses; implementing exponential backoff retry logic lets client applications gracefully retry after the indicated delay, which is essential for high availability under load. Option C is correct because using managed identities (via Microsoft Entra ID) eliminates hardcoded subscription keys, providing secure, credential-free authentication that supports key rotation and least-privilege access. Option E is correct because private endpoints (Azure Private Link) restrict traffic to your virtual network, removing public internet exposure and meeting enterprise network security requirements. Option A is not appropriate because storing subscription keys in plain text in a source code repository exposes secrets and violates security best practices. Option D is not appropriate because disabling TLS would remove encryption in transit, degrading security and violating compliance requirements rather than improving a legitimate design goal.

Answer

Store subscription keys in plain text configuration files inside the source code repository.

Answer

Disable TLS encryption on HTTP client requests to improve API throughput.

Question 4

You are creating a Custom Vision project and need to select a domain. Your project involves classifying images of various food dishes. Which domain should you select to optimize model accuracy for food classification?

Accepted Answer

Food. The Food domain in Custom Vision is a specialized model pretrained on food imagery, so it produces higher accuracy for classifying dishes than a generic domain. Selecting the domain that matches the image category is the recommended way to optimize model performance in Custom Vision.

Answer

Landmark

Answer

General

Answer

Retail

Question 5

A user asks a question that triggers a 'Blocked' response from Azure AI Content Safety, even though the query seems harmless. What is the best step to investigate this?

Accepted Answer

Check the Content Safety logs in the Azure AI Foundry portal.. When Azure AI Content Safety returns a 'Blocked' result for a seemingly benign prompt, the correct diagnostic step is to inspect the Content Safety logs and severity scores in the Azure AI Foundry portal. These logs show which category (hate, violence, sexual, self-harm) and which severity level triggered the block, letting you determine whether a threshold is misconfigured or a specific phrase is being flagged. This is a read-only investigation that preserves the safety posture.

Answer

Change the system prompt to ignore safety.

Answer

Increase the model temperature.

Answer

Disable Content Safety for the deployment.

Question 6

You are troubleshooting an Azure OpenAI deployment in Azure AI Foundry where agents are failing to complete tasks due to excessive timeouts. Which THREE diagnostic steps should you take? (Choose three.)

Accepted Answer

Check if the tokens-per-minute (TPM) quota is throttling requests, causing queued delays.. Option A is correct because Azure OpenAI enforces tokens-per-minute (TPM) quotas per deployment; when requests exceed the quota, they are throttled with HTTP 429 responses and retried after a Retry-After delay, which manifests as queued latency and agent timeouts, so verifying TPM utilization and quota limits is a valid diagnostic step. Option D is correct because Application Insights integrated with Azure AI Foundry captures distributed traces of agent runs, including per-step durations, tool call latency, and dependency calls, letting you pinpoint exactly which step or tool is consuming the time budget. Option E is correct because the client-side HTTP timeout (for example, the timeout setting on the AzureOpenAI/OpenAI SDK client or HttpClient) may be shorter than the actual end-to-end agent execution time, so raising that threshold prevents premature client aborts while you investigate. Option B is not appropriate because temperature controls randomness, not reasoning speed, and 2.0 is outside the supported range (0–2) and would degrade output quality rather than fix timeouts. Option C is not appropriate because deleting vector indices destroys the retrieval data agents depend on and does not accelerate processing; it would break RAG functionality instead of resolving latency.

Answer

Double the model temperature to 2.0 to accelerate reasoning speed.

Answer

Delete all vector indices to force local memory processing.

Question 7

Your organization is implementing strict network isolation for Azure OpenAI. Direct internet access from worker nodes is prohibited. Which THREE mechanisms must be correctly configured to allow secure communication? Each correct answer presents part of the solution.

Accepted Answer

Public network access disabled on the Azure OpenAI resource. Option A is correct because disabling public network access on the Azure OpenAI resource ensures that the service is not reachable over the public internet, forcing all traffic through approved private paths. Option D is correct because a Private DNS zone (privatelink.openai.azure.com) must be integrated with the virtual network so that the FQDN <resource>.openai.azure.com resolves to the private endpoint's private IP instead of the public IP. Option E is correct because an Azure Private Endpoint placed in the application virtual network subnet provides the private IP interface that worker nodes use to reach the Azure OpenAI service over the Microsoft backbone. Option B is wrong because assigning public IP addresses to the AI service endpoint contradicts the strict isolation requirement and would expose the service publicly. Option C is wrong because Azure Bastion is a jump-host service for RDP/SSH access to VMs and has no role in connecting to Azure OpenAI backend storage.

Answer

Public IP addresses assigned directly to the AI service endpoint

Answer

Azure Bastion host attached to the OpenAI backend storage

Question 8

You are configuring network isolation and security for an Azure AI Search service that connects to an Azure SQL Database backend. Which THREE features can you utilize to secure this data flow? (Choose three.)

Accepted Answer

IP firewall rules restricting Azure SQL Database access to the Azure AI Search service outbound IPs.. Option A is correct because Azure SQL Database supports server-level and database-level IP firewall rules, and you can allow the specific outbound IP addresses of the Azure AI Search service (its public egress IPs) so only that traffic reaches the SQL server. Option B is correct because Azure Private Endpoint creates a private IP address in your VNet for both Azure AI Search and Azure SQL Database, so the data flow stays on the Microsoft backbone/private network instead of traversing the public internet, and it can be combined with disabling public access. Option C is correct because Azure AI Search indexers can use a managed identity (system-assigned or user-assigned) to authenticate to Azure SQL Database with Microsoft Entra ID, and secure connection strings avoid embedding credentials in code or configuration. Option D is wrong because disabling TLS would remove encryption in transit and weaken security, not legitimately secure the data flow, and TLS does not meaningfully slow query execution in this context. Option E is wrong because storing plain-text admin credentials in a search index configuration file exposes secrets and is a security anti-pattern, not a supported or recommended way to secure the connection.

Answer

Disabling all transport layer security (TLS) requirements to speed up query execution.

Answer

Storing plain-text database admin credentials in the search index configuration file.

Question 9

You are troubleshooting an intermittent connectivity issue between a client application and an Azure AI Speech service that sits behind an Azure Firewall and a Virtual Network. Which THREE diagnostic steps or tools should you utilize? (Choose three.)

Accepted Answer

Use Azure Network Watcher IP Flow Verify to check if traffic is being blocked by network security groups.. Option A is correct because Azure Network Watcher IP Flow Verify tests a specific 5-tuple (source/destination IP, port, protocol) against the effective NSG rules on a VM's NIC and reports whether traffic is allowed or denied, which directly isolates NSG-caused intermittent blocking. Option C is correct because enabling Azure AI service diagnostic settings routes request/response logs and metrics to a Log Analytics workspace, letting you correlate service-side failures and latency with client-side symptoms. Option D is correct because NSG flow logs capture inbound and outbound flow metadata (allowed/denied, source/destination, ports, bytes) that reveals intermittent drops and asymmetric traffic patterns over time. Option B is wrong because Azure Advisor cost recommendations address pricing and utilization, not connectivity diagnostics. Option E is wrong because the ARM template visualizer only shows resource deployment dependencies and cannot trace live network traffic or firewall/NSG behavior.

Answer

Run the Azure Advisor cost recommendation analyzer to optimize resource pricing tiers.

Answer

Use the Azure Resource Manager template visualizer to inspect regional resource dependencies.

Question 10

You are preparing a prompt template for a summarization task. You want to provide three distinct examples of input text and expected summaries before asking the model to process the target text. What is this prompting technique called?

Accepted Answer

Few-shot prompting. Few-shot prompting provides a small number of input-output examples (typically 2-5) in the prompt to demonstrate the desired task before asking the model to perform it on new input. Three examples of input text and expected summaries is the textbook definition of few-shot summarization prompting.

Answer

Retrieval-augmented generation

Answer

Chain-of-thought prompting

Answer

Zero-shot prompting