Microsoft Azure DevOps Engineer (AZ-400) Exam Dumps & Questions 2026 Microsoft Azure DevOps Engineer (AZ-400) Exam Questions 2026 Contains 750+ exam questions to pass the exam in first attempt. SkillCertPro offers real exam questions for practice for all major IT certifications. For a full set of 750 questions. Go to https://skill certpro.com/product/microsoft - azure - devops - solutions - az - 400 - practice - exam - set/ SkillCertPro offers detailed explanations to each question which helps to understand the concepts better. It is recommended to score above 85% in SkillCertPro exams before attempting a real exam. SkillCertPro updates exam questions every 2 weeks. You will get life time access and life time free updates SkillCertPro assures 100% pass guarantee in first attempt. Below are the free 10 sample questions. Question 1: You use a Git repository in Azure Repos to manage the source code of a web application. Developers commit changes directly to the master branch. You need to implement a change management procedure that meets the following requirements: The master branch must be protected, and new changes must be built in the feature branches first. Changes must be reviewed and approved by at least one release manager before each merge. Changes must be brought into the master branch by using pull requests. What should you configure in Azure Repos? A. branch policies of the master branch B. Services in Project Settings C.Deployment pools in Project Settings D. branch security of the master branch Answer: A Explanation: ✅ A. branch policies of the master branch Branch policies in Azure Repos are the correct mechanism to enforce the stated requirements. You can configure policies on the master branch to: Require a minimum number of reviewers: This satisfies the "Changes must be reviewed and approved by at least one release manager" requirement. You can specify security groups (like a "Release Managers" group) as required reviewers. Require a build to pass: This addresses "new changes must be built in the feature branches first" and ensures code quality before merging. Require pull requests: This enforces "Changes must be brought into the master branch by using pull requests," preventing direct pushes to master. ❌ B. Services in Project Settings "Services" in Project Settings generally refers to external service connections (e.g., to Azure subscriptions, GitHub, Jenkins). While these are essential for integrating Azure DevOps with other tools, they do not directly control branch protection, review processes, or pull request enforcement for a Git repository. ❌ C. Deployment pools in Project Settings Deployment pools are used for managing target machines for deployments, typically in release pipelines. They have no direct relevance to protecting Git branches, requiring pull requests, or enforcing code reviews within Azure Repos. ❌ D. branch security of the master branch Branch security in Azure Repos controls permissions on a branch (e.g., who can contribute, who can force push, who can bypass policies). While you might use branch security to restrict direct pushes to master (by denying "Contribute" permissions to certain users), it's not the primary or most granular way to implement the entire set of requirements like requiring pull requests, builds, and specific reviewers. Branch policies are designed specifically for enforcing workflow and quality gates on branches. Security settings are more about who can do what, whereas policies define how things must be done. Question 2: You need to execute inline testing of an Azure DevOps pipeline that uses a Docker deployment model. The solution must prevent the results from being published to the pipeline. What should you use for the inline testing? A. a single stage Dockerfile B. an Azure Kubernetes Service (AKS) pod C. a multi-stage Dockerfile D. a Docker Compose file Answer: C Explanation: ✅ C. a multi-stage Dockerfile A multi-stage Dockerfile is the ideal solution for inline testing within a Docker deployment model while preventing test results from being published to the pipeline. Here's why: Isolation of testing: With a multi-stage Dockerfile, you can create a dedicated "build" or "test" stage where you install testing frameworks, run your tests, and generate reports. This stage can include all the necessary tools for testing without those tools ending up in your final production image. Preventing result publication: By design, the intermediate layers and artifacts of previous stages in a multi-stage build are not included in the final image, unless explicitly copied. If you perform your tests in an intermediate stage and do not copy the test results (e.g., JUnit XML files) to the final stage or to an external location that would be published by a PublishTestResults task in Azure Pipelines, then the results will effectively not be published to the pipeline's test summary. The tests run, but their output is contained within that specific Docker build stage. Efficiency: Multi-stage builds lead to smaller, more efficient final images because only the necessary runtime components are transferred to the final stage. ❌ A. a single stage Dockerfile A single-stage Dockerfile would include all build tools, test tools, and application code in one image. While you could run tests within this single stage, it would be much harder to prevent the test results from being part of the image or to prevent a subsequent PublishTestResults task in your Azure Pipeline from picking them up if they are left in the image's filesystem. More importantly, it would create a much larger and less secure production image. ❌ B. an Azure Kubernetes Service (AKS) pod An AKS pod is a runtime environment for deploying and running containerized applications. While you would eventually deploy your application to AKS, using an AKS pod directly for inline testing within the pipeline where the goal is to prevent publishing results is not the most direct or appropriate mechanism. Testing within the Docker build process itself (via a Dockerfile) is more suited for "inline" testing as part of the image creation. Deploying to an AKS pod for testing would typically be part of a later, more integrated testing phase (e.g., integration testing, UAT) and would usually involve publishing results. ❌ D. a Docker Compose file A Docker Compose file is used to define and run multi-container Docker applications. While you can use Docker Compose for local development and testing of interconnected services, it's not the primary mechanism for "inline testing" within a single Docker image build process in the context of preventing test results from being published to the pipeline. You might use Docker Compose to spin up a test environment, but the question specifically asks about inline testing within a Docker deployment model (implying the image build itself) and the prevention of publishing results to the pipeline. A multi-stage Dockerfile directly addresses this. Question 3: Your company uses the following resources: Windows Server 2019 container images hosted in an Azure Container Registry. Azure virtual machines that run the latest version of Ubuntu An Azure Log Analytics workspace Azure Active Directory (Azure AD) An Azure key vault For which of the resources can you receive vulnerability assessments in Azure Security Center? A.the Azure Log Analytics workspace B. the Azure key vault C. the Azure virtual machines that run the latest version of Ubuntu D. Azure Active Directory (Azure AD) Answer: C Explanation: ✅ C. the Azure virtual machines that run the latest version of Ubuntu Microsoft Defender for Cloud offers vulnerability assessment solutions for virtual machines, including Linux VMs like Ubuntu. It can integrate with built-in scanners (like Qualys, which is included at no extra cost for Defender for Servers plan) or other third-party solutions to scan for vulnerabilities in the operating system and installed software. ❌ A. the Azure Log Analytics workspace Azure Log Analytics workspaces are used to collect, store, and analyze log data from various Azure resources and on-premises servers. While Security Center uses Log Analytics to store security data and findings, and you can export vulnerability assessment results to a Log Analytics workspace, Security Center does not perform vulnerability assessments on the Log Analytics workspace itself. Its purpose is data ingestion and analysis, not to be a target for vulnerability scanning. ❌ B. the Azure key vault Azure Key Vault is a service for securely storing and managing cryptographic keys, secrets, and certificates. While Microsoft Defender for Cloud offers threat protection for Azure Key Vault (detecting unusual or suspicious access attempts), it does not provide traditional vulnerability assessments of the Key Vault service itself in the same way it does for VMs or container images (i.e., scanning for CVEs in its underlying software or configurations). The security of Key Vault is largely managed by Microsoft. ❌ D. Azure Active Directory (Azure AD) Azure Active Directory (now Microsoft Entra ID) is a comprehensive identity and access management service. While Azure AD is a critical component of security, and Microsoft offers tools like Identity Protection within Azure AD to detect and respond to identity-based risks (e.g., risky sign-ins, compromised credentials), Azure Security Center (Defender for Cloud) does not perform "vulnerability assessments" on Azure AD in the sense of scanning for software vulnerabilities or misconfigurations within the Azure AD service. Identity Protection provides its own form of "assessment" related to user and sign-in risk. Question 4: Your company currently has an Azure DevOps organization and an Azure subscription. They want to implement various security practices when it comes to managing resources in their Azure subscription. The requirements for security implementation are given below. > Be able to provide just-in-time access to Azure resources. > Provide time-bound access to resources. You decide to implement Conditional Access. Would this fulfill the requirement? A. Yes B. No Answer: B Explanation: ✅ No Implementing Conditional Access alone does not fulfill the requirement for just- in-time (JIT) and time-bound access to Azure resources. Conditional Access policies in Microsoft Entra ID (Azure AD) provide granular, context-aware access controls based on conditions like user, device, location, and risk, but they do not inherently provide time-limited or just-in-time access capabilities. Just-in-time access is specifically provided by Microsoft Defender for Cloud's Just- in-Time VM access and Privileged Identity Management (PIM) in Azure AD, which enable temporary, time-bound access to resources. PIM integrates with Conditional Access to enforce policies during the activation of privileged roles, but Conditional Access by itself does not grant or limit access duration. Therefore, while Conditional Access enhances security by enforcing conditions such as MFA or compliant devices, it does not by itself provide the just-in-time or time-bound access control required. Question 5: You have an Azure DevOps project. Currently, you are using Azure Repos Git for source code version control. You are planning on using a third-party continuous integration tool to control the builds. Which of the following in Azure DevOps would you use for authentication? A. Certificate authentication B. Personal Access tokens C. Shared Access Signature D. NTLM Authentication Answer: B Explanation: ✅ B. Personal Access Tokens (PATs) Personal Access Tokens (PATs) are the most common and recommended way to authenticate third-party tools, scripts, or command-line clients with Azure DevOps. They are essentially alternative passwords with specific scopes and expiration dates. For a third-party CI tool to access Azure Repos Git, you would create a PAT with the necessary "Code (Read & Write)" or "Code (Full)" scope, depending on the tool's needs. This provides a secure and revokable way for external services to interact with your Azure DevOps project without using your full user credentials. ❌ A. Certificate authentication While certificate authentication (e.g., using service principals with client certificates) is a robust authentication method in Azure, particularly for service- to-service communication with Azure AD, it's generally more complex to set up and manage for a typical third-party CI tool integrating with Azure DevOps Repos. PATs are specifically designed for this type of programmatic access and are simpler to manage for this use case. ❌ C. Shared Access Signature (SAS) Shared Access Signatures (SAS) are primarily used in Azure Storage to grant limited access to storage resources (blobs, queues, tables, files). They provide a way to grant time-limited permissions to specific Azure Storage resources. SAS tokens are not used for authenticating to Azure DevOps services, including Azure Repos Git. ❌ D. NTLM Authentication NTLM (NT LAN Manager) authentication is an older authentication protocol primarily used in Windows environments. Azure DevOps, being a cloud-native platform, relies on more modern and secure authentication mechanisms like OAuth, OpenID Connect, and Personal Access Tokens. NTLM authentication is not a standard or recommended method for third-party tools to integrate with Azure DevOps. For a full set of 750 questions. Go to https://skillcertpro.com/product/microso ft - azure - devops - solutions - az - 400 - practice - exam - set/ SkillCertPro offers detailed explanations to each question which helps to understand the concepts better. It is recommended to score above 85% in SkillCertPro exams before attempting a real exam. SkillCe rtPro updates exam questions every 2 weeks. You will get life time access and life time free updates SkillCertPro assures 100% pass guarantee in first attempt. Question 6: You have a pipeline defined in your Azure DevOps project. You notice that the pipeline fails occasionally. This is because a test measures the response time of an API endpoint that causes the failures. You have to ensure that the build pipeline does not fail because of the test. Which of the following can you carry out to rectify this issue? Choose two answers from the options given below. A.Ensure to enable Test impact analysis. B. Clear the property of Flaky tests that is included in the test pass percentage. C. Set the Flaky test detection to Off. D. Manually go ahead and mark the test as flaky. Answer: B and D Explanation: ✅ B. Clear the property of Flaky tests that is included in the test pass percentage. Azure DevOps has a feature to identify and manage "flaky tests." If a test is marked as flaky, you can configure whether its results should be included in the overall test pass percentage. By clearing (or effectively, unchecking/disabling) the property that includes flaky tests in the test pass percentage, even if the test fails, it won't cause the entire pipeline to fail based on the aggregated test results. This allows the pipeline to succeed as long as the non-flaky tests pass. ✅ D. Manually go ahead and mark the test as flaky. To leverage the "flaky test" management features in Azure DevOps, you first need to identify and mark the problematic test as flaky. You can do this manually in the Azure DevOps Test Plans or Test Results view after a test run. Once a test is marked as flaky, you can then apply the configuration (as described in option B) to exclude it from the pass percentage calculation. This is the prerequisite step to addressing the issue with the built-in flaky test handling. ❌ A. Ensure to enable Test impact analysis. Test Impact Analysis (TIA) is a feature that attempts to determine which tests are relevant to a given code change, running only those tests. While TIA can speed up pipeline execution by reducing the number of tests run, it does not address the issue of an occasionally failing test causing the pipeline to fail. If the identified test is still relevant to a change, TIA will run it, and if it's flaky, it will still fail the pipeline unless other flaky test settings are applied. TIA is for optimizing test runs, not for handling flakiness. ❌ C. Set the Flaky test detection to Off. Setting flaky test detection to "Off" would mean that Azure DevOps would not automatically try to identify or flag tests as flaky based on their behavior. This would make it harder to manage the problem, as the system wouldn't help in recognizing the non-deterministic nature of the test. The goal is to manage the flaky test so it doesn't fail the build, not to ignore its flakiness entirely in the detection mechanism. To fix the pipeline failure, you need to mark it as flaky (D) and then decide how to handle its impact on the pass percentage (B). Question 7: You currently have a web application hosted in an Azure Web App. Application Insights are monitoring this. You have to ensure that alerts are sent when there is a sudden rise in performance issues and failures. Which of the following can you use for this purpose? A. Application Insights Profiler B. Continuous export C. Smart Detection D. Custom events Answer: C Explanation: ✅ C. Smart Detection Application Insights Smart Detection is specifically designed to automatically detect and alert you to sudden increases in failed requests, performance anomalies (like increased response time), and other unusual patterns in your web application's telemetry. It uses machine learning to learn your application's normal behavior and then identifies deviations that could indicate a problem, sending proactive alerts. This directly addresses the requirement of "sudden rise in performance issues and failures." ❌ A. Application Insights Profiler Application Insights Profiler is a tool used for diagnosing performance bottlenecks in your live web application. It helps you understand which code paths are taking the most time when a request is slow. While it's excellent for diagnosing performance issues after they occur, it does not proactively alert you to a sudden rise in performance issues or failures. Its purpose is deep-dive analysis, not automatic alerting. ❌ B. Continuous export Continuous export in Application Insights allows you to export your telemetry data to Azure Storage (e.g., blob storage) in JSON format. This is useful for long- term retention, integration with other data analytics tools (like Azure Databricks or Power BI), or custom processing. However, it is a data export mechanism and does not provide an alerting capability for sudden anomalies or performance issues. ❌ D. Custom events Custom events in Application Insights allow you to track specific user interactions or business-related events in your application. While you can send custom events and then build custom alerts based on their count or properties, "Custom events" themselves are a data collection feature. They don't inherently provide the "smart detection" of sudden rises in performance issues and failures like Smart Detection does, which automatically learns normal baselines. You would need to define complex custom alert rules to mimic what Smart Detection offers out-of-the-box for general performance and failure anomalies. Question 8: You have an Azure DevOps project that contains a build pipeline. The pipeline builds a container image named contosoimage and pushes the image to the Azure Container registry. The image uses a base image that is stored in Docker Hub. You have to ensure that contosoimage is updated automatically whenever the base image is updated. Which of the following can you implement for this requirement? A. Use the Azure Container Registry task B. Use a Docker Hub service connection in Azure Pipelines. C. Use Azure Event Grid and subscribe for registry events. D. Use a service hook in the DevOps project. Answer: A Explanation: ✅ A. Use the Azure Container Registry task Azure Container Registry (ACR) Tasks provide a built-in mechanism to automatically detect updates to base images (including those stored in Docker Hub) and trigger rebuilds of dependent container images like contosoimage. ACR Tasks track base image dependencies and can automatically rebuild your application images whenever the base image is updated, fulfilling the requirement to keep contosoimage updated automatically. This is the recommended and native solution for automating container image updates based on base image changes. ❌ B. Use a Docker Hub service connection in Azure Pipelines While a Docker Hub service connection allows Azure Pipelines to authenticate and pull images from Docker Hub, it does not provide an automatic trigger or mechanism to rebuild your image when the base image is updated. This option alone cannot ensure automatic updates of contosoimage based on base image changes. ❌ C. Use Azure Event Grid and subscribe for registry events Azure Event Grid can be used to subscribe to events from Azure Container Registry, such as image pushes, but it does not natively track or trigger rebuilds based on base image updates from external registries like Docker Hub. Additional custom automation would be required to implement this, making it a more complex and indirect solution. ❌ D. Use a service hook in the DevOps project Service hooks in Azure DevOps can trigger external services or pipelines based on DevOps events, but they do not inherently detect base image updates in Docker Hub or trigger rebuilds automatically. This option does not directly address the requirement for automatic updates when the base image changes. Question 9: You have an Azure Application Insights availability test configured. You have an Azure Logic App that will be used to send emails. You have to ensure the availability tests invoke the Logic App if there are issues detected via the Availability tests. Which of the following would you setup as the trigger type? A. An ApiConnection B. A Request trigger C. A HTTP Webhook trigger D. An HTTP trigger Answer: C Explanation: ✅ C. A HTTP Webhook trigger A HTTP Webhook trigger is the appropriate trigger type to ensure that Azure Application Insights availability tests can invoke an Azure Logic App when issues are detected. Webhook triggers allow external services, such as Application Insights alerts, to send an HTTP POST request to the Logic App endpoint, effectively starting the workflow in response to an alert or event. This aligns with common practices for integrating monitoring alerts with Logic Apps to automate responses like sending emails. ❌ A. An ApiConnection An ApiConnection is a connector used within Logic Apps to connect to various services (e.g., Office 365, Azure Monitor) but is not itself a trigger type. It facilitates actions inside the Logic App but does not define how the Logic App is started externally by Application Insights alerts. ❌ B. A Request trigger A Request trigger is similar to a webhook but is a generic HTTP trigger that waits for an HTTP request to start the Logic App. While it can be used for manual or programmatic invocation, it lacks the built-in webhook semantics and management features that a HTTP Webhook trigger provides for alert-based invocation scenarios. ❌ D. An HTTP trigger An HTTP trigger is a generic trigger that starts the Logic App when it receives an HTTP request. It is similar to the Request trigger but does not specifically support webhook subscription semantics. For alert-driven invocations, the HTTP Webhook trigger is preferred because it supports handshake and lifecycle management for webhook calls. Question 10: You have an ASP.Net core web application that is deployed to the Azure Web App service. You have to run a URL ping test every 10 minutes to ensure that the web app is accessible from different regions. You have to ensure that an alert is generated if the web application is unavailable from certain Azure regions. The solution needs to minimize development time. Which of the following must you implement for this requirement? A. Ensure to use Azure Application Insights availability test and alerts. B. Ensure to use Azure Service Health for specific Azure regions. C. Use Azure Monitor availability metrics and alerts. D. Deploy an Azure Function to specific regions. Answer: A Explanation: ✅ A. Ensure to use Azure Application Insights availability test and alerts. Azure Application Insights availability tests are specifically designed for this exact scenario. You can configure a URL ping test (or a standard URL test, multi-step web test) to: Run every 10 minutes: You define the frequency. From different regions: Application Insights allows you to select multiple geographic locations from which the tests should originate. Generate an alert if unavailable from certain Azure regions: You can set up alerts based on the availability test results, specifically triggering when tests fail from a certain number of locations or all locations. Minimize development time: This is an out-of-the-box feature of Application Insights, requiring configuration rather than custom code development. ❌ B. Ensure to use Azure Service Health for specific Azure regions. Azure Service Health provides personalized alerts and guidance when Azure service issues, planned maintenance, or health advisories affect your Azure services. While it's crucial for understanding the health of Azure infrastructure, it monitors the Azure platform itself, not the availability of your specific deployed application. It won't tell you if your web app is inaccessible from certain regions due to an application-level issue or misconfiguration, only if the underlying Azure Web App service in that region is having problems. ❌ C. Use Azure Monitor availability metrics and alerts. While Azure Monitor is the overarching service for monitoring, and Application Insights is a component of Azure Monitor, simply stating "Azure Monitor availability metrics and alerts" is less precise and comprehensive than "Azure Application Insights availability test and alerts." Application Insights provides the specific "availability test" functionality that runs ping tests from multiple regions, which then feeds into Azure Monitor's alerting capabilities. Without the Application Insights availability test, Azure Monitor wouldn't have the specific multi-region ping test data you need. ❌ D. Deploy an Azure Function to specific regions. You could technically deploy Azure Functions to various regions to ping your web app and then write custom logic to send alerts. However, this approach would: Increase development time: You'd need to write, deploy, and maintain the Function code for the ping test, error handling, and alerting logic. Reinvent the wheel: This duplicates functionality already provided by Application Insights out-of-the-box. Increase operational overhead: Managing multiple Functions in different regions adds complexity compared to a single Application Insights configuration. Therefore, this option does not minimize development time compared to using Application Insights. For a full set of 750 questions. Go to https://skillcertpro.com/product/microsoft - azure - devops - solutions - az - 400 - practice - exam - set/ SkillCertPro offers detailed explanations to each question which helps to understand the concepts better. It is recommended to score above 85% in SkillCertPro exam s before attempting a real exam. SkillCertPro updates exam questions every 2 weeks. You will get life time access and life time free updates SkillCertPro assures 100% pass guarantee in first attempt.