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AI-200 Security And Observability Practice Question

Your team is developing an AI solution that uses Azure Cognitive Services. You need to ensure that the API keys cannot be extracted from the client-side mobile application. What is the recommended architectural pattern to achieve this?

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

Implement a backend API proxy (e.g., Azure Functions or API Management) that authenticates mobile clients and calls Cognitive Services using secure server-side keys

Routing mobile client requests through an intermediary backend service (such as Azure API Management or Azure Functions) that holds the API keys securely prevents embedding keys in mobile code.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Use Azure Front Door to strip API keys from incoming mobile requests

    Why it's wrong here

    Incorrect. Stripping API keys would cause the backend cognitive service to reject the requests due to missing authentication.

  • Implement a backend API proxy (e.g., Azure Functions or API Management) that authenticates mobile clients and calls Cognitive Services using secure server-side keys

    Why this is correct

    Correct. Mobile clients should never store secret keys; a backend proxy handles authentication and secure upstream API calls.

  • Store the Cognitive Services API key in an encrypted local SQLite database on the mobile device

    Why it's wrong here

    Incorrect. Local device storage can be reverse-engineered and decompiled, exposing API keys.

  • Configure Cognitive Services for anonymous public access and rely on mobile app version checks

    Why it's wrong here

    Incorrect. Anonymous access allows anyone to abuse and drain the service quota.

Quick reference

Cloud Service Model Comparison

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, AKS, GKE

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JA

Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official Microsoft exam blueprint

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