{"id":22813,"date":"2026-09-26T08:02:26","date_gmt":"2026-09-26T08:02:26","guid":{"rendered":"https:\/\/www.examlabs.com\/certification\/?p=22813"},"modified":"2026-09-26T08:02:26","modified_gmt":"2026-09-26T08:02:26","slug":"microsoft-ai-200-practice-test-questions-and-exam-dumps-part9-q161-180","status":"publish","type":"post","link":"https:\/\/www.examlabs.com\/certification\/microsoft-ai-200-practice-test-questions-and-exam-dumps-part9-q161-180\/","title":{"rendered":"Microsoft AI-200 Practice Test Questions and Exam Dumps Part9 Q161-180"},"content":{"rendered":"

View Full <\/b>Microsoft AI-200 Exam Dumps<\/b><\/a> and Practice Test Dumps<\/b><\/h2>\n

 <\/p>\n

Question 161<\/b><\/h3>\n

Which Azure AI Search capability retrieves documents using vector similarity?<\/b><\/p>\n

    \n
  1. Vector search<\/span><\/li>\n
  2. Faceting<\/span><\/li>\n
  3. Autocomplete<\/span><\/li>\n
  4. Synonym expansion<\/span><\/li>\n<\/ol>\n

    Correct Answer: 1<\/b><\/p>\n

    Explanation:<\/b><\/p>\n

    Vector search in Azure AI Search retrieves documents based on the similarity between vector representations rather than relying only on exact keyword matches. This makes it useful for AI applications where users may express an idea using words that differ from those stored in the source content. Faceting organizes results into categories, autocomplete assists with query completion, and synonym expansion handles predefined equivalent terms. Vector search can be combined with keyword retrieval to create hybrid experiences that consider both lexical matching and semantic similarity when finding relevant information.<\/span><\/p>\n

    Question 162<\/b><\/h3>\n

    Which Azure AI Search field attribute enables a value to appear in search results?<\/b><\/p>\n

      \n
    1. Filterable<\/span><\/li>\n
    2. Sortable<\/span><\/li>\n
    3. Retrievable<\/span><\/li>\n
    4. Facetable<\/span><\/li>\n<\/ol>\n

      Correct Answer: 3<\/b><\/p>\n

      Explanation:<\/b><\/p>\n

      A retrievable field in Azure AI Search can have its value returned in search results. This is important when an application needs to display stored document information after a matching record is found. Filterable fields support filtering expressions, sortable fields allow ordering results, and facetable fields support category-based navigation. Field attributes determine how indexed data can be used by search operations, so selecting them appropriately helps balance functionality and index behavior. A field that should be displayed to users generally needs to be configured as retrievable.<\/span><\/p>\n

      Question 163<\/b><\/h3>\n

      Which Cosmos DB operation reads one item using its identifier and partition key?<\/b><\/p>\n

        \n
      1. Cross-partition query<\/span><\/li>\n
      2. Point read<\/span><\/li>\n
      3. Analytical scan<\/span><\/li>\n
      4. Change-feed pull<\/span><\/li>\n<\/ol>\n

        Correct Answer: 2<\/b><\/p>\n

        Explanation:<\/b><\/p>\n

        A point read in Azure Cosmos DB retrieves a single item when the application provides the item’s identifier together with its partition key. Because Cosmos DB can directly locate the logical partition and item, point reads are generally an efficient way to access known records. Cross-partition queries search across multiple logical partitions, analytical scans support broader analytical processing, and change-feed operations consume changes rather than directly retrieving a specific item. Applications should use point reads when they already know which individual document they need.<\/span><\/p>\n

        Question 164<\/b><\/h3>\n

        Which Cosmos DB consistency model provides the strongest read guarantees?<\/b><\/p>\n

          \n
        1. Eventual<\/span><\/li>\n
        2. Session<\/span><\/li>\n
        3. Consistent prefix<\/span><\/li>\n
        4. Strong<\/span><\/li>\n<\/ol>\n

          Correct Answer: 4<\/b><\/p>\n

          Explanation:<\/b><\/p>\n

          Strong consistency in Azure Cosmos DB provides the strongest read guarantees by ensuring that reads reflect the latest committed write according to the configured consistency behavior. This can be important for workloads where clients must not observe stale values. Eventual consistency provides weaker guarantees with greater flexibility, session consistency provides read-your-writes behavior within a client session, and consistent prefix ensures reads do not observe writes out of order. Choosing a consistency level requires balancing application correctness requirements against latency, availability, and geographic distribution considerations.<\/span><\/p>\n

          Question 165<\/b><\/h3>\n

          Which Azure Storage redundancy option synchronously copies data across availability zones?<\/b><\/p>\n

            \n
          1. ZRS<\/span><\/li>\n
          2. LRS<\/span><\/li>\n
          3. GRS<\/span><\/li>\n
          4. RA-GRS<\/span><\/li>\n<\/ol>\n

            Correct Answer: 1<\/b><\/p>\n

            Explanation:<\/b><\/p>\n

            Zone-redundant storage, or ZRS, synchronously replicates supported storage data across multiple availability zones within the primary Azure region. This helps protect applications against failures affecting an individual availability zone while keeping data available within the region. LRS maintains copies within a single physical location, while GRS and RA-GRS provide geo-replication to a secondary region. ZRS is therefore useful when an AI workload requires stronger resilience against zone-level infrastructure failures without depending primarily on cross-region replication.<\/span><\/p>\n

            Question 166<\/b><\/h3>\n

            Which Azure Storage access tier is intended for frequently accessed blob data?<\/b><\/p>\n

              \n
            1. Archive<\/span><\/li>\n
            2. Cool<\/span><\/li>\n
            3. Hot<\/span><\/li>\n
            4. Deep archive<\/span><\/li>\n<\/ol>\n

              Correct Answer: 3<\/b><\/p>\n

              Explanation:<\/b><\/p>\n

              The Hot access tier is designed for data that is accessed frequently. It generally provides lower access costs compared with less frequently accessed tiers, making it appropriate for active application data and workloads that repeatedly read stored content. Cool is intended for data accessed less frequently, while Archive is designed for long-term offline storage with higher retrieval latency. Selecting an appropriate access tier can help AI applications manage storage costs according to actual data-access patterns, particularly when large datasets are continuously processed or queried.<\/span><\/p>\n

              Question 167<\/b><\/h3>\n

              Which Azure Blob Storage feature preserves previous blob versions after updates?<\/b><\/p>\n

                \n
              1. Soft delete<\/span><\/li>\n
              2. Versioning<\/span><\/li>\n
              3. Leasing<\/span><\/li>\n
              4. Immutability<\/span><\/li>\n<\/ol>\n

                Correct Answer: 2<\/b><\/p>\n

                Explanation:<\/b><\/p>\n

                Blob versioning automatically maintains previous versions of a blob when supported updates occur. This allows applications or administrators to recover earlier content and provides a history of blob modifications. Soft delete protects deleted blobs for a configured retention period, leasing provides coordination between clients, and immutability prevents protected content from being modified or deleted during a retention period. Versioning is useful for AI applications that repeatedly update documents or datasets and may need to recover an earlier version after an unintended modification.<\/span><\/p>\n

                Question 168<\/b><\/h3>\n

                Which Azure Service Bus feature groups related messages for ordered processing?<\/b><\/p>\n

                  \n
                1. Topics<\/span><\/li>\n
                2. Sessions<\/span><\/li>\n
                3. Filters<\/span><\/li>\n
                4. Forwarding<\/span><\/li>\n<\/ol>\n

                  Correct Answer: 2<\/b><\/p>\n

                  Explanation:<\/b><\/p>\n

                  Azure Service Bus sessions provide a mechanism for grouping related messages and maintaining ordered processing for applications that require it. A session identifier associates messages with the same logical conversation or workflow, allowing a receiver to process that sequence as a unit. Topics provide publish-subscribe messaging, filters determine which messages a subscription receives, and forwarding routes messages between entities. Sessions are particularly useful for workflows where message order and state continuity matter, such as multi-step processing or conversational application interactions.<\/span><\/p>\n

                  Question 169<\/b><\/h3>\n

                  Which Event Grid capability delivers events to supported handlers without polling?<\/b><\/p>\n

                    \n
                  1. Push delivery<\/span><\/li>\n
                  2. Batch scanning<\/span><\/li>\n
                  3. Manual retrieval<\/span><\/li>\n
                  4. Scheduled polling<\/span><\/li>\n<\/ol>\n

                    Correct Answer: 1<\/b><\/p>\n

                    Explanation:<\/b><\/p>\n

                    Event Grid uses event-driven push delivery to send events to supported handlers when subscribed events occur. This allows applications to react to changes without repeatedly polling a source to discover whether something happened. Push-based event handling can reduce unnecessary requests and improve responsiveness for reactive cloud applications. Batch scanning and scheduled polling require consumers to actively check for new information, while manual retrieval requires application-driven interaction. Push delivery is therefore well suited to architectures where services should respond automatically to events as they are generated.<\/span><\/p>\n

                    Question 170<\/b><\/h3>\n

                    Which Azure Event Grid concept defines what events a subscriber receives?<\/b><\/p>\n

                      \n
                    1. Topic endpoint<\/span><\/li>\n
                    2. Event subscription<\/span><\/li>\n
                    3. Event payload<\/span><\/li>\n
                    4. Delivery attempt<\/span><\/li>\n<\/ol>\n

                      Correct Answer: 2<\/b><\/p>\n

                      Explanation:<\/b><\/p>\n

                      An Event Grid event subscription defines the events that a subscriber receives from a topic or supported event source. It can include configuration such as event-type filters and subject-based filtering to control which events are delivered. The topic endpoint represents the event source location, the event payload contains event information, and delivery attempts describe the process of sending an event to a handler. Event subscriptions are therefore central to controlling event routing between Azure services and application endpoints.<\/span><\/p>\n

                      Question 171<\/b><\/h3>\n

                      Which Azure Functions trigger starts execution when a blob changes?<\/b><\/p>\n

                        \n
                      1. Timer trigger<\/span><\/li>\n
                      2. HTTP trigger<\/span><\/li>\n
                      3. Blob trigger<\/span><\/li>\n
                      4. Queue trigger<\/span><\/li>\n<\/ol>\n

                        Correct Answer: 3<\/b><\/p>\n

                        Explanation:<\/b><\/p>\n

                        A Blob trigger starts an Azure Function when changes to supported blob data are detected according to the trigger’s configuration and hosting model. This is useful for event-driven processing such as transforming uploaded files, extracting information from documents, or initiating downstream AI workflows. Timer triggers run according to schedules, HTTP triggers respond to HTTP requests, and Queue triggers react to queue messages. Blob-triggered functions can help create automated processing pipelines where newly stored content immediately initiates application logic.<\/span><\/p>\n

                        Question 172<\/b><\/h3>\n

                        Which Azure Functions hosting option is designed for rapid serverless scaling?<\/b><\/p>\n

                          \n
                        1. Consumption plan<\/span><\/li>\n
                        2. Dedicated plan<\/span><\/li>\n
                        3. App Service Environment<\/span><\/li>\n
                        4. Kubernetes hosting<\/span><\/li>\n<\/ol>\n

                          Correct Answer: 1<\/b><\/p>\n

                          Explanation:<\/b><\/p>\n

                          The Azure Functions Consumption plan provides a serverless execution model in which Azure manages infrastructure allocation and automatically scales function instances according to workload demand within the plan’s capabilities. It is useful for event-driven applications where traffic can vary significantly and maintaining dedicated compute continuously may not be necessary. Dedicated plans provide allocated App Service compute, App Service Environment provides an isolated hosting environment, and Kubernetes hosting runs functions through Kubernetes infrastructure. The Consumption model is commonly suited to lightweight, event-driven workloads with variable execution patterns.<\/span><\/p>\n

                          Question 173<\/b><\/h3>\n

                          Which Azure Container Apps setting controls the container’s listening port for ingress?<\/b><\/p>\n

                            \n
                          1. Target port<\/span><\/li>\n
                          2. Replica count<\/span><\/li>\n
                          3. CPU request<\/span><\/li>\n
                          4. Registry path<\/span><\/li>\n<\/ol>\n

                            Correct Answer: 1<\/b><\/p>\n

                            Explanation:<\/b><\/p>\n

                            The target port in Azure Container Apps identifies the port on which the application container listens for incoming ingress traffic. Correctly configuring this value allows the Container Apps ingress layer to route requests to the appropriate application process inside the container. Replica count controls how many instances are running, CPU request relates to allocated compute, and the registry path identifies where an image is stored. Target-port configuration is therefore important when exposing containerized APIs or services through Container Apps ingress.<\/span><\/p>\n

                            Question 174<\/b><\/h3>\n

                            Which Azure Container Registry feature restricts access to selected repositories?<\/b><\/p>\n

                              \n
                            1. Geo-replication<\/span><\/li>\n
                            2. Repository permissions<\/span><\/li>\n
                            3. Image layers<\/span><\/li>\n
                            4. Build logs<\/span><\/li>\n<\/ol>\n

                              Correct Answer: 2<\/b><\/p>\n

                              Explanation:<\/b><\/p>\n

                              Azure Container Registry supports repository-scoped permissions that can restrict access to specific repositories within a registry. This allows organizations to apply more granular access controls when different teams or workloads should only interact with selected container images. Geo-replication distributes registry content across regions, image layers form the contents of container images, and build logs provide information about image-building operations. Repository-level permissions are particularly useful in larger AI development environments where multiple applications share a container registry but should not automatically have access to every image repository.<\/span><\/p>\n

                              Question 175<\/b><\/h3>\n

                              Which Azure Monitor metric represents the number of requests handled by an application?<\/b><\/p>\n

                                \n
                              1. Request count<\/span><\/li>\n
                              2. CPU temperature<\/span><\/li>\n
                              3. Storage capacity<\/span><\/li>\n
                              4. Network route<\/span><\/li>\n<\/ol>\n

                                Correct Answer: 1<\/b><\/p>\n

                                Explanation:<\/b><\/p>\n

                                Request count represents the number of requests processed by an application or monitored component when the relevant telemetry source exposes that metric. Monitoring request volume helps developers understand application traffic, detect unusual changes, and correlate workload levels with latency or failures. CPU temperature is not a standard application request metric, storage capacity measures available or consumed storage, and network routes describe traffic paths rather than application demand. Request metrics can therefore contribute to capacity planning and operational monitoring for cloud-based AI applications.<\/span><\/p>\n

                                Question 176<\/b><\/h3>\n

                                Which Azure Monitor component can trigger automation when a condition is met?<\/b><\/p>\n

                                  \n
                                1. Metric namespace<\/span><\/li>\n
                                2. Alert rule<\/span><\/li>\n
                                3. Workbook panel<\/span><\/li>\n
                                4. Diagnostic category<\/span><\/li>\n<\/ol>\n

                                  Correct Answer: 2<\/b><\/p>\n

                                  Explanation:<\/b><\/p>\n

                                  An Azure Monitor alert rule evaluates telemetry against defined conditions and can initiate configured actions when those conditions are satisfied. Alert rules can monitor metrics or other supported signals and work with action groups to deliver notifications or trigger automation. A metric namespace organizes metric definitions, workbook panels present monitoring information visually, and diagnostic categories identify types of platform logs or metrics. Alert rules are therefore important for detecting operational problems such as elevated errors, resource saturation, or unusual application behavior.<\/span><\/p>\n

                                  Question 177<\/b><\/h3>\n

                                  Which Azure Resource Manager feature prevents accidental resource deletion?<\/b><\/p>\n

                                    \n
                                  1. Resource lock<\/span><\/li>\n
                                  2. Resource tag<\/span><\/li>\n
                                  3. Deployment output<\/span><\/li>\n
                                  4. Template parameter<\/span><\/li>\n<\/ol>\n

                                    Correct Answer: 1<\/b><\/p>\n

                                    Explanation:<\/b><\/p>\n

                                    Azure resource locks help prevent accidental deletion or modification of resources. Depending on the lock type, a resource can be protected from deletion while still allowing permitted configuration changes, or it can be protected from both deletion and modification. Tags provide metadata for organization and governance, deployment outputs expose values from deployments, and template parameters provide configurable deployment inputs. Resource locks can be especially valuable for AI infrastructure containing production databases, storage resources, or other components that should not be removed unintentionally.<\/span><\/p>\n

                                    Question 178<\/b><\/h3>\n

                                    Which Bicep feature allows a deployment to use values supplied at runtime?<\/b><\/p>\n

                                      \n
                                    1. Module<\/span><\/li>\n
                                    2. Parameter<\/span><\/li>\n
                                    3. Output<\/span><\/li>\n
                                    4. Resource<\/span><\/li>\n<\/ol>\n

                                      Correct Answer: 2<\/b><\/p>\n

                                      Explanation:<\/b><\/p>\n

                                      Bicep parameters allow deployment values to be supplied externally rather than hard-coded directly into the template. Parameters can represent values such as resource names, regions, SKUs, or configuration settings and can be assigned during deployment. Modules organize reusable infrastructure definitions, outputs return values from a deployment, and resources define the Azure components being created or referenced. Using parameters makes infrastructure templates more reusable across environments such as development, testing, and production while reducing the need to maintain separate templates for every environment.<\/span><\/p>\n

                                      Question 179<\/b><\/h3>\n

                                      Which Azure Policy effect blocks creation when a required condition is violated?<\/b><\/p>\n

                                        \n
                                      1. Audit<\/span><\/li>\n
                                      2. Deny<\/span><\/li>\n
                                      3. Append<\/span><\/li>\n
                                      4. Modify<\/span><\/li>\n<\/ol>\n

                                        Correct Answer: 2<\/b><\/p>\n

                                        Explanation:<\/b><\/p>\n

                                        The Deny effect in Azure Policy prevents a resource request from being created or updated when it violates the policy condition. This provides proactive governance by stopping noncompliant configurations before they are deployed. Audit records noncompliance without blocking the request, Append adds fields or values in supported scenarios, and Modify can alter resource properties when the policy and permissions support the operation. Deny is therefore useful when an organization needs mandatory controls, such as restricting unsupported resource types or enforcing specific configuration requirements.<\/span><\/p>\n

                                        Question 180<\/b><\/h3>\n

                                        Which Azure service provides recommendations for improving cloud resource configuration?<\/b><\/p>\n

                                          \n
                                        1. Azure Advisor<\/span><\/li>\n
                                        2. Azure Service Health<\/span><\/li>\n
                                        3. Azure Resource Graph<\/span><\/li>\n
                                        4. Azure Activity Log<\/span><\/li>\n<\/ol>\n

                                          Correct Answer: 1<\/b><\/p>\n

                                          Explanation:<\/b><\/p>\n

                                          Azure Advisor analyzes Azure resource configurations and provides personalized recommendations across areas such as cost, performance, reliability, security, and operational excellence. These recommendations can help teams identify opportunities to improve how resources are configured or utilized. Azure Service Health provides information about service issues and planned maintenance, Azure Resource Graph enables resource inventory queries, and Activity Log records subscription-level management operations. Advisor is therefore useful when developers or administrators want actionable recommendations for improving the configuration and operation of their Azure environment.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

                                          View Full Microsoft AI-200 Exam Dumps and Practice Test Dumps   Question 161 Which Azure AI Search capability retrieves documents using vector similarity? Vector search Faceting Autocomplete Synonym expansion Correct Answer: 1 Explanation: Vector search in Azure AI Search retrieves documents based on the similarity between vector representations rather than relying only on exact keyword […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[1648,1647],"tags":[],"_links":{"self":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/22813"}],"collection":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/comments?post=22813"}],"version-history":[{"count":1,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/22813\/revisions"}],"predecessor-version":[{"id":22814,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/22813\/revisions\/22814"}],"wp:attachment":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/media?parent=22813"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/categories?post=22813"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/tags?post=22813"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}