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Plan And Manage AN Azure AI SolutionhardMultiple ChoiceObjective-mapped

AI-103 Plan And Manage AN Azure AI Solution Practice Question

You are designing an automated deployment pipeline for Azure AI Search using GitHub Actions. The pipeline must authenticate to Azure securely without storing credentials or long-lived secrets in GitHub repository settings. Which authentication mechanism should you implement?

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

OpenID Connect (OIDC) with Azure workload identity federation

Federated identity credentials with OpenID Connect (OIDC) allow GitHub Actions to authenticate to Azure without storing secrets.

Answer analysis

Option-by-option breakdown

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

  • Hardcoded administrator API keys stored in GitHub Action variables

    Why it's wrong here

    Storing keys as variables or secrets in GitHub still exposes static credentials that can be leaked or compromised.

  • OpenID Connect (OIDC) with Azure workload identity federation

    Why this is correct

    OIDC federation allows GitHub Actions to exchange tokens with Microsoft Entra ID securely without storing static client secrets.

  • A personal access token (PAT) with full subscription ownership

    Why it's wrong here

    PAT tokens provide broad access and carry high security risks if leaked.

  • Anonymous access enabled during deployment time

    Why it's wrong here

    Azure AI Search does not support anonymous deployment access.

About these practice questions

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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

This AI-103 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-103 exam.