Microsoft · AZ-401
Microsoft Certified: Agentic DevOps Engineer Expert (AZ-401) Practice Tests
Validates expertise in designing and implementing Microsoft Agentic DevOps solutions using Azure DevOps and GitHub with GitHub Copilot AI assistance. Demonstrates the ability to deliver continuous value through AI-assisted DevOps practices including pipelines, security, compliance, and instrumentation.
Exam Details
Practice Questions
400
≈ 8 practice exams
Duration
120 minutes
Passing Score
700/1000
Difficulty
ProfessionalLast Updated
Oct 2026
Topics Covered
Design Processes and CommunicationsSource Control StrategyBuild and Release PipelinesSecurity and ComplianceInstrumentation StrategyAI-Assisted DevOps with GitHub Copilot
Microsoft Certified: Agentic DevOps Engineer Expert (AZ-401) Practice Exam Preparation
Use this AZ-401 practice exam to prepare for Microsoft Certified: Agentic DevOps Engineer Expert (AZ-401) with realistic questions, detailed explanations, and focused study modes. The practice bank includes 400 questions for Microsoft AZ-401, so you can review the exam steadily instead of relying on one long cram session.
As you practice, pay extra attention to recurring topics such as Design Processes and Communications, Source Control Strategy, Build and Release Pipelines, Security and Compliance, and Instrumentation Strategy. Start with short sessions to identify weak areas, then move into timed quizzes once your accuracy is consistent.
The explanations are written for candidates preparing for Microsoft certification questions and reviewing how the concepts apply in practice. Use the free preview first, then unlock the full question bank when you are ready to build a complete study routine.
Sample Questions
5 sample questions with answers and explanations. The full bank has 400 questions, enough for 8 full-length practice exams.
Preview — answers shown1. A team wants to use AI-assisted tools to generate natural language queries for Azure Monitor logs. Which operator should they use in the generated KQL query to efficiently filter specific column values? (Select one!)
Awhere
Btake
Ctop
Dsearch
Explanation
The 'where' operator filters records based on specific column values and is significantly more efficient than 'search', which scans all columns. 'take' and 'top' are used for limiting result sets, not for filtering by value. Using 'where' ensures optimal performance for targeted queries generated by AI tools.
2. You are monitoring pipeline health and notice that a specific test task fails intermittently without code changes. Which metric should you track to identify this issue? (Select one!)
AFailure rate
BFlaky test rate
CPipeline duration
DQueue time
Explanation
Flaky tests are tests that pass and fail intermittently without code changes. Tracking the flaky test rate helps identify these unstable tests. Pipeline duration measures execution time. Failure rate tracks overall failures but does not distinguish between consistent and intermittent failures. Queue time measures how long a job waits for an agent.
3. A team is using the GitHub MCP Server to integrate AI agents with their source control. They notice that the agent cannot trigger workflows. Which toolset is missing from the default configuration? (Select one!)
Aactions
Bissues
Cpull_requests
Drepos
Explanation
The default toolsets for the GitHub MCP Server are context, repos, issues, pull_requests, and users. The actions toolset is not included by default, which prevents the agent from triggering or managing workflows. The repos, issues, and pull_requests toolsets are already enabled by default and do not control workflow execution.
4. You are designing a strategy for agentic development. You need to ensure that AI agents can access Azure DevOps data via the MCP server. Which operational mode must the AI assistant be in? (Select one!)
AStandard mode
BDeep investigation mode
CAgent mode
DChat mode
Explanation
The AI assistant must operate in agent-mode to access data via the MCP Server. Standard mode does not support MCP server integration for data access. Chat mode is for conversational interactions without direct tool execution. Deep investigation mode is a specific capability of the Observability Agent, not a general requirement for MCP server access.
5. An SRE team deploys the Azure SRE Agent to monitor a production AKS cluster. They want to ensure that the agent can investigate Kubernetes audit logs. Which Log Analytics table contains these logs? (Select one!)
AKubernetesNode
BKubernetesPod
CAKSAuditAdmin
DAKSAudit
Explanation
The 'AKSAudit' table in Log Analytics stores Kubernetes audit logs for AKS clusters. 'AKSAuditAdmin' stores admin audit logs, which are a subset of audit logs for administrative actions. 'KubernetesPod' and 'KubernetesNode' contain pod and node metadata, respectively. To investigate general Kubernetes audit logs, the team must query the 'AKSAudit' table.
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