AI-102 Plan and manage an Azure AI solution Practice Question
Your company is deploying an Azure AI solution that uses multiple AI services. You need to ensure that all API calls are authenticated securely using managed identities. Which of the following steps is required to enable managed identity authentication for an Azure AI service?
⚠ Common exam trap
Test-takers frequently confuse managed identity with key management solutions like Key Vault, or assume that enabling a managed identity at a higher scope (subscription) automatically applies to all resources, when in fact the identity must be explicitly assigned to each resource and granted RBAC permissions.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Assign a managed identity to the Azure AI service and grant it the required RBAC role
Managed identity authentication for Azure AI services requires assigning either a system-assigned or user-assigned managed identity to the resource, and then granting that identity the appropriate RBAC role (e.g., Cognitive Services User) on the target AI service. This eliminates the need for keys or secrets in the code and leverages Microsoft Entra ID tokens for secure, passwordless authentication.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable system-assigned managed identity at the subscription level
Why it's wrong here
Managed identity is enabled on the individual Azure resource, not at subscription scope, so this step cannot authenticate the service. Subscription-level settings govern policy and billing; enabling a system-assigned identity on the specific AI service is what issues the principal Microsoft Entra ID can authorise.
- ✓
Assign a managed identity to the Azure AI service and grant it the required RBAC role
Why this is correct
Managed identity authentication requires two elements: a managed identity assigned to the Azure AI resource, plus an RBAC role assignment granting that identity access to the target service. Without the role grant, token acquisition succeeds but authorisation fails.
- ✗
Store the authentication key in Azure Key Vault and reference it in the application
Why it's wrong here
Key Vault stores secrets for application retrieval, so the app still authenticates with a key rather than a managed identity token; no service principal or token endpoint is involved. Key Vault is the right choice when rotating credentials for legacy services that cannot use Microsoft Entra ID authentication.
- ✗
Configure a shared access key in the Azure AI service
Why it's wrong here
Shared access keys are static credentials passed in request headers, so the service validates the key itself and no Microsoft Entra ID token is issued or validated. Shared keys suit quick prototyping or services where managed identity is unavailable, not identity-based authentication.
Quick reference
Access Control Model Comparison
| Model | Acronym | Who Controls Access? | Best For |
|---|---|---|---|
| Discretionary Access Control | DAC | Resource owner | Small teams, file shares |
| Mandatory Access Control | MAC | System / security labels | Classified govt / military |
| Role-Based Access Control | RBAC | Administrator (via roles) | Enterprise environments |
| Attribute-Based Access Control | ABAC | Policy engine (user + resource attributes) | Fine-grained, dynamic policies |
| Rule-Based Access Control | RuBAC | System rules / ACLs | Firewall rules, network ACLs |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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