You have an Azure API Management (APIM) Standard tier instance named APIM1 that uses a managed gateway. You plan to use APIM1 to publish an API named API1 that uses a backend database that supports only a limited volume of requests per minute. You also need a policy for API1 that will minimize the possibility that the number of requests to the backend database from an indivi...

The goal in this scenario is to minimize the possibility of an individual IP address exceeding the backend database's supported request limits, which suggests limiting the number of requests based on IP addresses. Let's analyze each policy option to determine the best fit: A) ip-filter - Explanation: The `ip-filter` policy is used to allow or deny access to an API based on the IP address. It doesn't limit or rate-limit the number of requests from an IP address but rather controls whether the IP address can access the API in the first place. While it can be used to block or allow requests from certain IPs, it does not enforce a limit on request volume. - Rejected because: This policy is about access control rather than rate-limiting the number of requests from specific IP addresses, which is what the scenario requires. B) quota-by-key - Explanation: The `quota-by-key` policy limits the number of requests that can be made within a specified time window, but it is based on a specific key (e.g., API key, subscription key, etc.). This means it would limit the number of requests per user or per key, rather than per IP address. - Rejected because: The requirement specifies limiting requests per IP address, and `quota-by-key` is not design...

Author: Mia · Last updated May 11, 2026

You develop a web application that sells access to last-minute openings for child camps that run on the weekends. The application uses Azure Application Insights for all alerting and monitoring. The application must alert operators when a technical issue is preve...

In this scenario, you want to create an alert to detect technical issues that may be preventing sales to camps. Given that the application uses Azure Application Insights for alerting and monitoring, the type of alert you should choose will depend on the nature of the monitoring data and how you intend to detect issues. A) Metric alert using multiple time series - Explanation: This alert type is used when you want to monitor multiple metrics across different time series. It's useful for monitoring metrics like CPU usage, memory, or request count from multiple sources. However, this is generally used when you have specific numerical metrics that you need to monitor over time, not necessarily for detecting more complex or dynamic issues like those related to application failures or service disruptions. - Rejected because: This alert is more suited for monitoring simple, quantitative metrics over time and does not provide the flexibility needed to handle complex scenarios like dynamic technical issues affecting sales. It is not ideal for situations where you need to monitor log-based events that can indicate a technical issue. B) Metric alert using dynamic thresholds - Explanation: A metric alert with dynamic thresholds uses historical data to automatically determine a baseline of normal behavior and sets thresholds dynamically based on this baseline. This alert is great for detecting anomalies or outliers in metrics (like request rates or response times) when the baseline can change over time. - Selected because: This alert is suitable for detecting technical issues that may cause failures or disruptions in the application. For example, if sales are not occurring due to a backend issue (like a service failure), a metric-based...

Author: Rohan · Last updated May 11, 2026

Case study - This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided. To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study. At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section. To start the case study - To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. When you are ready to answer a question, click the Question button to return to the question. Background - Munson's Pickles and ...

To address the requirement of aggregating telemetry values for distributor API calls while minimizing data traffic, data costs, and storage costs, let's examine the different Application Insights API methods listed: A) TrackEvent - Purpose: This method is used to log custom events, typically for tracking business or application events. Each time the event is logged, it records one occurrence. - Why it's rejected: Although `TrackEvent` can capture telemetry data, it does not focus on capturing or aggregating specific metrics or performance data related to API calls. For telemetry aggregation, `TrackEvent` would generate too many individual data points, which would increase traffic and storage costs. B) TrackDependency - Purpose: This method is used to track dependencies, such as database calls, HTTP requests, or calls to other external services. It records the duration and success or failure of the external dependency. - Why it's rejected: While `TrackDependency` could track an external call made by the distributor API, it is not designed for aggregating telemetry values. It primarily tracks the performance of external dependencies but would not aggregate custom telemetry or allow for statistical analysis in the way needed for the distributor API telemetry aggregation. C) TrackMetric - Purpose: This method is used to track numeric metrics (e.g., request durations, counts, etc.). It allows aggregation over time and is well-suited for aggregating telemetry values, as it allows you to track values such as the number of requests, response times, or throughput in a statistically meaningful way. - W...

Author: Aria · Last updated May 11, 2026

DRAG DROP - Case study - This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided. To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study. At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section. To start the case study - To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. When you are ready to answer a question, click the Question button to return to the question. Background - ...

Author: Ming · Last updated May 11, 2026

HOTSPOT - Case study - This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided. To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study. At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section. To start the case study - To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. When you are ready to answer a question, click the Question button to return to the question. Background - Mu...

Author: Manish · Last updated May 11, 2026

HOTSPOT - Case study - This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided. To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study. At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section. To start the case study - To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. When you are ready to answer a question, click the Question button to return to the question. Background - Mu...

Author: Sam · Last updated May 11, 2026

You manage an Azure subscription that contains 100 Azure App Service web apps. Each web app is associated with an individual Application Insights instance. You plan to remove Classic availability tests from all Application Insights instances that have this functionality configured. You have the following PowerShell statement: Get...

To address the question of selecting the correct value for the `$condition` variable in the PowerShell statement, let's break down the different options and understand their meaning in the context of Azure Application Insights web tests. Key Concepts: - Classic Availability Tests: These are older, legacy availability tests in Application Insights, which could be of the type "ping" (for simple ping tests) or "standard" (for HTTP-based availability tests). - Application Insights Web Tests: When you retrieve web tests using `Get-AzApplicationInsightsWebTest`, you're querying availability tests associated with Application Insights. The `Type` or `WebTestKind` properties are the ones that determine the nature of the test (such as whether it's a "ping" or "standard" test). Now, let's review each option and see which one best meets the requirement of filtering and removing Classic availability tests: A) $_ .Type -eq "ping" - Meaning: This option filters for web tests that are of the type "ping." Classic availability tests of type "ping" are used to check the availability of an endpoint using a simple ping. - Why it's rejected: While this might correctly identify "ping" type tests, it doesn't cover all the types of Classic availability tests, especially those of the "standard" type, which would also need to be removed. B) $_ .WebTestKind -eq "ping" - Meaning: This option filters for web tests that have a `WebTestKind` property equal to "ping." This aligns with the classic ping tests, which would be relevant if the goal was to remove only the "ping" type availability tests. - Why it's rejected: As with option A, this option onl...

Author: Jack · Last updated May 11, 2026

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have an Azure App Service web app named WebApp1 and an Azure Functions app named Function1. WebApp1 is associated with an Application Insights instance named appinsights1. You configure a web test and ...

Analysis of the scenario: - You have a web app (WebApp1) and a function app (Function1). - There is an Application Insights instance (appinsights1) associated with WebApp1. - A web test is configured in appinsights1, and an alert is set up to notify you via email. - The goal is to ensure that the alert also triggers the execution of Function1. Solution Review: - Azure Monitor Insights workbook: Workbooks in Azure are primarily used for visualizing and analyzing metrics and logs, but they are not designed to trigger actions directly (such as executing a function) when an alert occurs. Workbooks can present data or dashboards but do not provide built-in automation for triggering functions. To achieve the goal of triggering an execution of Function1 when an alert occurs, Az...

Author: Oliver · Last updated May 11, 2026

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have an Azure App Service web app named WebApp1 and an Azure Functions app named Function1. WebApp1 is associated with an Application Insights instance named appinsights1. You configure a web test and a c...

Analysis of the scenario: - You have a web app (WebApp1) and a function app (Function1). - Application Insights (appinsights1) is being used to monitor WebApp1. - A web test is configured in Application Insights, and an alert triggers an email when an issue is detected. - The goal is to ensure that the alert also triggers the execution of Function1. Solution Review: - Application Insights Smart Detection: Smart Detection in Application Insights is a feature that uses machine learning to automatically detect anomalies in the performance of your application. It helps identify potential issues without the need to manually configure each condition. However, Smart Detection itself is a monitoring feature and doesn't directly trigger actions like the execution of a function. While it can send notifications about detected anomalies, it does not inherently trigger the execution of a function app. - Triggering Function1 Execution...

Author: Noah Williams · Last updated May 11, 2026

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have an Azure App Service web app named WebApp1 and an Azure Functions app named Function1. WebApp1 is associated with an Application Insights instance named appinsights1. You configure a web test ...

Analysis of the scenario: - You have an Azure App Service web app (WebApp1) and an Azure Functions app (Function1). - Application Insights (appinsights1) is being used to monitor WebApp1. - A web test and corresponding alert are configured in Application Insights to notify via email when certain conditions are met. - The goal is to ensure that each alert also triggers the execution of Function1. Solution Review: - Azure Monitor Action Group: An Azure Monitor action group is a feature that allows you to specify actions to be taken when an alert is triggered. Action groups can be configured to execute various actions such as sending notifications, invoking a webhook, or executing a function app. This is exactly the type of functionality needed to trigger the execution of Function1 when an alert is triggered from Application Insights. By creating an action group, you can associate the alert with Function1. This ensures that when the...

Author: Scarlett · Last updated May 11, 2026

You have a Standard tier instance of Azure Cache for Redis named redis1 configured with the default settings. You need to configure a Maxmemory policy to increase the amount of cache ...

Analysis of the scenario: - You are working with an Azure Cache for Redis instance named redis1 that is configured with the default settings. - The goal is to increase the amount of cache available for read operations. This means you want to make more cache space available for data that can be read and potentially keep more data in memory. - Redis uses a maxmemory policy to manage how it handles situations where the cache memory limit is reached. Key Considerations: - Maxmemory policy controls how Redis behaves when it reaches the maximum memory limit. - Maxmemory-reserved defines the memory reserved for internal operations, and adjusting this value can impact the overall memory available for caching. - For read operations, we want to ensure that memory usage is efficient and that Redis doesn't evict data that might be needed for reads. Option Analysis: 1. A) Decrease the value of maxmemory-reserved: - maxmemory-reserved refers to the memory that Redis keeps for internal management operations. Decreasing this value would make more memory available for actual caching. However, this would not directly impact the maxmemory policy for cache eviction and may reduce internal memory needed for Redis operations, which could affect performance. 2. B) Increase the value of maxmemory-reserved: - Increasing maxmemory-reserved would allocate more memory for Redis internal operations, reducing the amount of memory available for cache storage. This would not increase cache available for read operations; in fact, it would reduce the available cach...

Author: James · Last updated May 11, 2026

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have an Azure App Service web app named WebApp1 and an Azure Functions app named Function1. WebApp1 is associated with an Application Insights instance named appinsights1. You configure a web test a...

Analysis of the scenario: - You have a web app (WebApp1) and an Azure Functions app (Function1). - Application Insights (appinsights1) is being used to monitor WebApp1. - A web test is configured in Application Insights, and an alert triggers an email when certain conditions are met. - The goal is to ensure that each alert also triggers the execution of Function1. Solution Review: - Application Insights Funnel: A funnel in Application Insights is used to track the progression of users through different stages or events in a process. It is typically used for analyzing user behavior, such as how users move from one step to the next in a series of events (e.g., from viewing a product to making a purchase). While funnels help in understanding user journeys, they are not designed to trigger actions like invoking a function app. A funnel focuses on analyzing user activity and is n...

Author: Andrew · Last updated May 11, 2026

Case study - This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided. To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study. At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section. To start the case study - To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. When you are ready to answer a question, click the Question button to return to the question. Background - Fourth Coffee is a gl...

Author: Krishna · Last updated May 11, 2026

Case study - This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided. To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study. At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section. To start the case study - To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. When you are ready to answer a question, click the Question button to return to the question. Background - Fourth Coffee is a gl...

Author: FrozenWolf2022 · Last updated May 11, 2026

You develop an ASP. Net Care application by integrating the Application Insights SDK into your solution. The application sends a very high rate of telemetry in a short time interval. You observe a reduced number of events, traces, and metrics being recorded and increased error rates for telemetry ingestion. Telemetry data must synchronize the client and server information to allow HTTP request and response correla...

Analysis of the scenario: - You are working with an ASP.NET Core application integrated with Application Insights SDK to collect telemetry data. - There is a high rate of telemetry being sent in a short period, resulting in: - A reduced number of recorded events, traces, and metrics. - Increased error rates for telemetry ingestion. - The need to synchronize client and server data to allow proper HTTP request/response correlation. - The objective is to reduce telemetry traffic, data costs, and storage costs, while maintaining statistically correct analysis of application telemetry data. Option Breakdown: 1. A) Set a daily cap on the Log Analytics workspace. Create an Activity log alert rule. - Setting a daily cap limits how much data is ingested into the Log Analytics workspace. While this helps in controlling costs, it does not directly reduce telemetry traffic or data being sent from your application. It also might result in missing important telemetry if the daily cap is reached. Additionally, an Activity log alert rule would monitor Azure activities but wouldn't directly solve the issue of reducing telemetry traffic or optimizing telemetry data transmission from your application. - Not ideal for reducing telemetry traffic or optimizing the analysis of telemetry data. 2. B) Modify the pricing tier for the Log Analytics workspace. - Changing the pricing tier affects how much you pay for data ingestion, retention, and query costs. While this might help with cost management, it does not solve the problem of reducing telemetry traffic or the issues with ingestion errors. It doesn’t address the high rate of telemetry data sent from your application or the issue of reducing storage and data costs in an efficient way. - Not the right solution for managing telemetry volume or improving data synchronization. 3. C) U...

Author: MysticJaguar44 · Last updated May 11, 2026

You develop an ASP. Net Care application by integrating the Application Insights SDK into your solution. The application sends a very high rate of telemetry in a short time interval. You observe a reduced number of events, traces, and metrics being recorded and increased error rates for telemetry ingestion. Telemetry data must synchronize the client and server information to allow HTTP request and response correla...

Analysis of the scenario: - You are working with an ASP.NET Core application integrated with the Application Insights SDK. - The application is sending a very high rate of telemetry data, resulting in: - Reduced number of events, traces, and metrics recorded. - Increased error rates for telemetry ingestion. - The need to synchronize client and server information for HTTP request/response correlation. - The goal is to reduce telemetry traffic, data costs, and storage costs, while ensuring that the statistical analysis of the telemetry data remains accurate. Option Breakdown: 1. A) Set a daily cap on the Log Analytics workspace. Create an Activity log alert rule. - Setting a daily cap on the Log Analytics workspace would limit the data ingestion for the workspace, but it doesn’t directly address the root issue, which is the high volume of telemetry traffic from the application itself. This approach might result in missing telemetry data once the cap is reached. - The Activity log alert rule would monitor activity but wouldn’t reduce the telemetry traffic or solve the ingestion errors. - Not ideal, as this doesn't solve the core issue of reducing telemetry data sent from the application or improving telemetry ingestion efficiency. 2. B) Modify the pricing tier for the Log Analytics workspace. - Modifying the pricing tier might impact how much you pay for data retention and query costs, but it does not address the telemetry traffic or ingestion problem from the application side. Changing the pricing tier won’t solve the problem of excessive telemetry volume being sent or reduce the ingestion errors. - Not relevant, as it focuses on cost rather than optimizing telemetry traffic or the data synchronization. 3. C) Verify adaptive sampling is enabled. Set the maxTelemetryItemsPerSecond value. - Adaptive sampling is a fe...

Author: Mia · Last updated May 11, 2026

HOTSPOT - Case study - This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided. To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study. At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section. To start the case study - To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. When you are ready to answer a question, click the Question button to return to the question. Background - Fo...

Author: ElectricLionX · Last updated May 11, 2026

HOTSPOT - You have an Azure App Service web app named App1. App1 has Application Insights enabled. You plan to review the configuration of telemetry sampling for Application Insights of App1. You need to author an analytics query that will return the sampling rate. How should you complete th...

Author: Sam · Last updated May 11, 2026

HOTSPOT - You have a web app named App1 hosted on you, on-premises web server. You plan to use the Application Insights JavaScript SDK to implement client-side Real User Monitoring (RUM) of individual pages of App1. You need to author the script element that will be added to each of the pages. What should you set for the value of src and cfg ...

Author: Ava · Last updated May 11, 2026

You develop an ASP. Net Core application by integrating the Application Insights SDK into your solution. The application sends a very high rate of telemetry in a short time interval. You observe a reduced number of events, traces, and metrics being recorded and increased error rates for telemetry ingestion. You need to reduce telemetry traffic, data costs, and storage costs while preserving a sta...

Analysis of the scenario: - You are working with an ASP.NET Core application integrated with Application Insights SDK to monitor telemetry data. - The application is sending a high rate of telemetry data in a short period, leading to: - Reduced number of events, traces, and metrics being recorded. - Increased error rates for telemetry ingestion. - The goal is to reduce telemetry traffic, data costs, and storage costs, while ensuring statistical correctness in analysis and preserving the ability to correlate HTTP request and response data. Option Breakdown: 1. A) Configure a Log Analytics workspace data collection rule (DCR). Use a Kusto Query Language (KQL) statement to filter incoming data. - Data Collection Rules (DCR) in Log Analytics allow you to customize the data collection process, but they filter incoming data based on criteria you set. However, this option primarily affects data post-ingestion and does not address the issue of controlling telemetry volume at the point of collection. - Using KQL to filter data is helpful for storage optimization but does not reduce the actual telemetry traffic sent to Application Insights, which is the root cause of the issue. It doesn't solve the problem of ingestion errors caused by excessive telemetry volume. - Not ideal because it doesn't directly reduce the telemetry traffic being sent. 2. B) Disable adaptive sampling. Enable and configure the fixed-rate sampling module. - Disabling adaptive sampling will actually increase telemetry traffic, not reduce it. Adaptive sampling is a feature that automatically adjusts the amount of telemetry being collected based on the application load, so disabling it would exacerbate the traffic problem. - Fixed-rate sampling allows you to control telemetry collection by specifying a fixed rate, but it could result in data being missed if not configured correctly, and it may lead to non-statistical analysis if the sample rate is not representative of actual traffic. - Not ideal because it would increase traffic and may lead to biased data if the rate is not carefully configured. 3. C) Set a daily...

Author: Mia · Last updated May 11, 2026

HOTSPOT - You have an Azure Function app named App1 written in C# and an Application Insights workspace named Workspace1. App is implemented with Application Insights enabled and is configured to send its telemetry to Workspace1. You observe that App1 telemetry collection regularly exceeds monthly quotas of Workspace1. You need to ensure that the telemetry volume remains within t...

Author: Grace · Last updated May 11, 2026

You have an Azure subscription that contains an Application Insights resource named AI1 and an Azure App Service web app named App1. You create a Standard availability test in AI1. You set its URL to point to App1. You need to ensure tha...

Analysis of the Scenario: You have an Application Insights resource (AI1) and an Azure App Service web app (App1). - You have configured a Standard availability test in AI1 with the URL pointing to App1. - You need to ensure email notifications are sent to the owners of the subscription whenever the test fails. Explanation of the options: 1. A) Create an action group: - An action group is a collection of notification preferences, such as email, SMS, and webhook, that can be used to trigger actions when an alert is fired. However, creating an action group alone does not define the condition for when the action should occur. It needs to be associated with an alert rule that defines the conditions (such as the failure of the availability test). - Not enough by itself because it does not define the condition for triggering the notification. You still need an alert rule to trigger the action group. 2. B) Create an alert rule: - An alert rule defines the conditions under which the system should trigger a notification. You would typically configure an alert rule to monitor the availability test's result in AI1 and then specify that any failed tests trigger an email notification. - This is the correct approach. The alert rule will use the availability test’s results to determine when a failure occurs, and you can link it to an...

Author: Nathan · Last updated May 11, 2026

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are developing an Azure solution to collect point-of-sale (POS) device data from 2,000 stores located throughout the world. A single device can produce 2 megabytes (MB) of data every 24 hours. Each store location has one to five devices that send data. You must store the device data in Azure Blob storage. Devic...

Solution Evaluation: Let's break down the solution in question: Scenario Breakdown: - Data Source: 2,000 stores around the world, each with 1 to 5 POS devices. - Data Volume: Each device sends 2 MB of data every 24 hours, totaling 4 MB (min) to 10 MB (max) of data per store per day. - Requirement: The data must be stored in Azure Blob Storage, and the data must be correlated based on a device identifier. - Future Expansion: More stores will open in the future, so scalability is needed. - Goal: Implement a solution to collect and process data from POS devices. The Proposed Solution: - Provisioning an Azure Service Bus: Azure Service Bus provides messaging capabilities, but this solution is more oriented for message queuing and handling, not directly for storing large amounts of data like Azure Blob Storage. Service Bus is more suited for smaller message payloads (in the KB range). - Topic with Correlation Filter: Service Bus topics allow filtering messages, and using a correlation filter could help in correlating data based on the device identifier. However, it’s not optimized for storing large files or large amounts of data, like the 2 MB from each device every day...

Author: Charlotte · Last updated May 11, 2026

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are developing an Azure solution to collect point-of-sale (POS) device data from 2,000 stores located throughout the world. A single device can produce 2 megabytes (MB) of data every 24 hours. Each store location has one to five devices that send data. You must store the device data in Azure Blob sto...

Solution Evaluation: Let's analyze the scenario and the proposed solution in detail: Scenario Breakdown: - Data Source: 2,000 stores worldwide, with each store having 1 to 5 POS devices. - Data Volume: Each device produces 2 MB of data every 24 hours, totaling 4 MB to 10 MB of data per store daily. - Storage Requirement: The data needs to be stored in Azure Blob Storage. - Correlation Requirement: The device data needs to be correlated based on a device identifier. - Future Expansion: More stores will open in the future, which means the solution should be scalable. The Proposed Solution: - Provisioning an Azure Event Grid: Event Grid is an event-routing service that facilitates the delivery of events from event sources to event handlers. It is ideal for event-driven architectures and real-time event processing. - Event Filtering Based on Device Identifier: Event Grid allows event filtering and can evaluate specific event properties, such as a device identifier. This filtering capability can ensure that the right device data is processed based on the identifier. Why This Solution Might Not Meet the Goal: - Event Grid is Designed for Event Notifications: Event Grid is built for handling events, not for storing large amounts of data. It’s more suitable for managing notifications and triggering actions in real-time. In this scenario, Event Grid could be used to send notifications when new data is available, but it is not intended to hold or store large datasets like th...

Author: Aria · Last updated May 11, 2026

DRAG DROP - You manage several existing Logic Apps. You need to change definitions, add new logic, and optimize these apps on a regular basis. What should you use? To answer, drag the appropriate tools to the correct functionalities. Each tool may be used once, more than once, or not at all. You may need...

Author: ThunderBear · Last updated May 11, 2026

A company is developing a solution that allows smart refrigerators to send temperature information to a central location. The solution must receive and store messages until they can be processed. You create an Azure Service Bus instance by providing a name, pricing tier, subscription, resource group, ...

Author: RadiantPhoenixX · Last updated May 11, 2026

HOTSPOT - You are developing an application that uses Azure Storage Queues. You have the following code: For each of the following statements, select Yes if the statement is true. O...

Author: Benjamin · Last updated May 11, 2026

A company is developing a solution that allows smart refrigerators to send temperature information to a central location. The solution must receive and store messages until they can be processed. You create an Azure Service Bus instance by providing a name, pricing tier, subscription, resource group, ...

Author: Madison · Last updated May 11, 2026

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are developing an Azure Service application that processes queue data when it receives a message from a mobile application. Messages may not be sent to the service consistently. You have the following requirements: * Queue size must not grow larger than 80 gigabytes (GB). * Use first-in-fi...

Solution Evaluation: Let's break down the requirements and the proposed solution: Requirements: 1. Queue size must not grow larger than 80 GB. 2. First-in-first-out (FIFO) ordering of messages. 3. Minimize Azure costs. The Proposed Solution: - Azure Storage Queue: Azure Storage Queue is a basic messaging service for storing large amounts of messages and is commonly used in scenarios where a simple, scalable, and reliable queue is required. It is well-suited for scenarios that don't demand advanced features like message prioritization or complex message handling. - Azure Function App with Storage Queue Trigger: The Azure Function App is designed to automatically process messages when they are added to the Azure Storage Queue. This would work well in a serverless model where the function processes messages as they come in, without the need for persistent server infrastructure. Analyzing the Requirements and Solution: 1. Queue Size (80 GB Limit): - Azure Storage Queue supports large volumes of messages and is cost-effective for storing message data. However, Storage Queues are not designed to enforce a strict queue size limit (e.g., 80 GB). While Azure Storage Queues can hold large amounts of data, there is no direct mechanism to ensure the queue size stays below 80 GB. You would need to implement custom logic to check the queue size and delete or archive old messages to meet this requirement, which could increase complexity and costs. 2. FIFO O...

Author: Maya · Last updated May 11, 2026

DRAG DROP - You develop software solutions for a mobile delivery service. You are developing a mobile app that users can use to order from a restaurant in their area. The app uses the following workflow: 1. A driver selects the restaurants for which they will deliver orders. 2. Orders are sent to all available drivers in an area. 3. Only orders for the selected restaurants will appear for the driver. 4. The first driver to accept an order removes it from the list of available orders. You need to implement an...

Author: Amira · Last updated May 11, 2026

HOTSPOT - You develop a news and blog content app for Windows devices. A notification must arrive on a user's device when there is a new article available for them to view. You need to implement push notifications. How should you complete the code segment? To answ...

Author: RadiantJaguar56 · Last updated May 11, 2026

You are developing an Azure messaging solution. You need to ensure that the solution meets the following requirements: * Provide transactional support. * Provide duplicate detection. * Store the messages for an unlimited period of time. Which two technologies will me...

Solution Evaluation: Let's break down the requirements and analyze which Azure messaging technologies meet them: Requirements: 1. Transactional Support: The ability to perform multiple operations (send, receive, etc.) in a single, all-or-nothing transaction. This ensures consistency across operations. 2. Duplicate Detection: The system should be able to detect and avoid processing the same message more than once, preventing the delivery of duplicate messages. 3. Unlimited Message Storage: The ability to store messages for an indefinite period, without a predefined retention limit. Options: A) Azure Service Bus Topic: - Transactional Support: Azure Service Bus supports transactional operations using message sessions and atomic transactions. You can use it to ensure that multiple operations within a transaction are committed or rolled back together. - Duplicate Detection: Azure Service Bus also supports duplicate detection. By enabling this feature, you can ensure that duplicate messages with the same MessageId are not processed. - Unlimited Message Storage: Azure Service Bus allows you to configure message retention for up to 7 days. However, this is not unlimited storage. For long-term message storage, you would need to use a different solution like Blob Storage. - Conclusion: Service Bus Topics can meet transactional support and duplicate detection requirements but do not provide unlimited storage. B) Azure Service Bus Queue: - Transactional Support: Like topics, Service Bus Queues also provide transactional support and message sessions. - Duplicate Detection: It supports duplicate detection based on the MessageId, ensuring that duplicate messages are not delivered. - Unlimited Message Storage: Similar to topics, Azure Service Bus Queues can store messages for up to 7 days, so they do not offer unlimited storage. - Conclusion: Service Bus Queues meet transactional support and duplicate detection but do not provide unlimited storage. C) Azure Storage Queue: - Transact...

Author: Kunal · Last updated May 11, 2026

DRAG DROP - You develop a gateway solution for a public facing news API. The news API back end is implemented as a RESTful service and hosted in an Azure App Service instance. You need to configure back-end authentication for the API Management service instance. Which target and gateway credential type should you use? To answer, drag the appropriate values to the correct parameters. Each value may be used on...

Author: Kai · Last updated May 11, 2026

HOTSPOT - You are creating an app that uses Event Grid to connect with other services. Your app's event data will be sent to a serverless function that checks compliance. This function is maintained by your company. You write a new event subscription at the scope of your resource. The event must be invalidated after a specific period of time. You need to configu...

Author: Emma Brown · Last updated May 11, 2026

HOTSPOT - You are working for Contoso, Ltd. You define an API Policy object by using the following XML markup: For each of the following statements, select Yes if the statement is true. ...

Author: Lina Zhang · Last updated May 11, 2026

You are developing a solution that will use Azure messaging services. You need to ensure that the solution uses a publish-subscribe model and eliminates the need for constant polling. What are two possible ways to achieve the goal?...

Solution Evaluation: Let's analyze the requirements and evaluate each option: Goal: - Publish-Subscribe Model: A messaging pattern where multiple subscribers can receive messages published by a single producer. - Eliminate Constant Polling: The solution should use push-based mechanisms rather than requiring constant polling by the consumers. Options: A) Service Bus: - Publish-Subscribe Model: Azure Service Bus Topics support the publish-subscribe model. A publisher can send messages to a topic, and multiple subscribers (using subscriptions) can receive copies of the messages. - Polling Elimination: Service Bus supports push-based notifications to subscribers using Azure Service Bus triggers (like Azure Functions or other listeners). This eliminates the need for constant polling. - Conclusion: Azure Service Bus meets both requirements: it supports the publish-subscribe model, and subscribers do not need to poll but can listen for new messages through push-based notifications. B) Event Hub: - Publish-Subscribe Model: Event Hub supports the publish-subscribe model in a way that multiple consumers (event processors) can read the stream of events. However, it is typically used for event streaming rather than discrete message processing. - Polling Elimination: Event Hub uses consumer groups to allow multiple consumers to read the same event stream, but it doesn’t directly offer push-based delivery to subscribers. It still requires consumers to pull or poll for new events. So, constant polling may still be required for consumers to fetch events. - Conclusion: Event Hub is more focused on streaming and event processing rather than a direct publish-subscribe messaging pattern, and it does...

Author: Benjamin · Last updated May 11, 2026

A company is implementing a publish-subscribe (Pub/Sub) messaging component by using Azure Service Bus. You are developing the first subscription application. In the Azure portal you see that messages are being sent to the subscription for each topic. You create and initialize a subscription client object by supplying the correct details, but the subscription a...

Solution Evaluation: The scenario involves a publish-subscribe (Pub/Sub) messaging system using Azure Service Bus, where the subscription application is not consuming messages despite the subscription receiving them. The task is to ensure that the subscription client processes all messages. Let’s go through each code segment to identify the correct solution: Key Concepts: - SubscriptionClient: This is the client object used to receive messages from a Service Bus subscription. - Message Handler: In a Pub/Sub model with Azure Service Bus, messages are processed by registering a message handler, which retrieves and processes the messages as they arrive. Evaluating Each Option: A) `await subscriptionClient.AddRuleAsync(new RuleDescription(RuleDescription.DefaultRuleName, new TrueFilter()));` - Explanation: This code creates a new rule for the subscription. A rule allows filtering messages in the subscription. By default, Azure Service Bus applies the default rule which allows all messages to be delivered to the subscription. However, adding a new rule or modifying the default rule is typically not required unless you are customizing how messages are filtered before being processed. - Why It’s Incorrect: This doesn’t directly impact the process of consuming messages from the subscription. The issue in the scenario seems to be related to consuming messages, not filtering them. B) `subscriptionClient = new SubscriptionClient(ServiceBusConnectionString, TopicName, SubscriptionName);` - Explanation: This code initializes the `SubscriptionClient` with the required connection details. While this is essential for creating the `SubscriptionClient` object, it does not deal with the actual process of receiving or handling mes...

Author: Isabella1 · Last updated May 11, 2026

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are developing an Azure Service application that processes queue data when it receives a message from a mobile application. Messages may not be sent to the service consistently. You have the following requirements: * Queue size must not grow larger than 80 gigabytes (GB). * Use first-in-f...

Let's break down the requirements and analyze the proposed solution: Requirements: 1. Queue size must not grow larger than 80 GB. 2. Use first-in-first-out (FIFO) ordering of messages. 3. Minimize Azure costs. Proposed Solution: - Use the .NET API to add a message to an Azure Storage Queue from the mobile application. - Create an Azure VM that is triggered from Azure Storage Queue events. Analysis: - Azure Storage Queue: - FIFO Ordering: Azure Storage Queue, by default, does not guarantee FIFO (First In, First Out) ordering. Azure Storage Queues typically use a best-effort approach for message delivery order. To guarantee FIFO ordering, Azure Service Bus Queues would be a better choice, as it explicitly supports FIFO. - Queue Size: Azure Storage Queues have a maximum message size of 64 KB and can support up to 500 TB of data. However, monitoring the queue size to not exceed 80 GB is something you would need to manage yourself. Using Storage Queues means you would have to actively manage your data to prevent exceeding the size limit. You would also need to monitor the VM’s performance to ensure that it processes messages in a timely fashion. - Azure VM: - Using an Azure VM trig...

Author: Isabella1 · Last updated May 11, 2026

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are developing an Azure Service application that processes queue data when it receives a message from a mobile application. Messages may not be sent to the service consistently. You have the following requirements: * Queue size must not grow larger than 80 gigabytes (GB). * Use first-in-first-o...

Let's analyze the requirements and the proposed solution: Requirements: 1. Queue size must not grow larger than 80 GB. 2. Use first-in-first-out (FIFO) ordering of messages. 3. Minimize Azure costs. Proposed Solution: - Use the .NET API to add a message to an Azure Service Bus Queue from the mobile application. - Create an Azure Windows VM that is triggered from Azure Service Bus Queue events. Analysis: - Azure Service Bus Queue: - FIFO Ordering: Azure Service Bus Queues support FIFO (First-In-First-Out) message ordering when configured with a Session-enabled queue. This is a key advantage because the requirements explicitly call for FIFO message ordering. Azure Service Bus ensures that messages are processed in the same order they were sent if they are grouped by sessions. - Queue Size Management: Service Bus Queues support up to 80 GB of data by default, which meets the requirement that the queue size should not grow beyond 80 GB. If the queue grows too large, older messages are automatically removed, and this can be managed via dead-letter queues for further processing. - Azure Windows VM: - The proposed solution uses an Azure Windows VM that is triggered by Service Bus Queue events. While this is technically feasible, using a VM in ...

Author: StarlightBear · Last updated May 11, 2026

DRAG DROP - You are developing a REST web service. Customers will access the service by using an Azure API Management instance. The web service does not correctly handle conflicts. Instead of returning an HTTP status code of 409, the service returns a status code of 500. The body of the status message contains only the word conflict. You need to ensure that conflicts produce the correct response. How should you complete the policy? To answer, drag the appropriate code segments to the correct locat...

Author: ThunderBear · Last updated May 11, 2026

DRAG DROP - You are a developer for a Software as a Service (SaaS) company. You develop solutions that provide the ability to send notifications by using Azure Notification Hubs. You need to create sample code that customers can use as a reference for how to send raw notifications to Windows Push Notification Services (WNS) devices. The sample code must not use external packages. How should you complete the code segment? To answer, drag the appropriate code segments to the correct location...

Author: StarlightBear · Last updated May 11, 2026

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are developing an Azure solution to collect point-of-sale (POS) device data from 2,000 stores located throughout the world. A single device can produce 2 megabytes (MB) of data every 24 hours. Each store location has one to five devices that send data. You must store the device data in Azure Blob storage. De...

Let's break down the requirements and the proposed solution: Requirements: 1. Store device data in Azure Blob storage. 2. Device data must be correlated based on a device identifier. 3. Each store has one to five devices producing data, and additional stores will be added. 4. Device data comes from 2,000 stores worldwide. 5. Each device produces 2 MB of data every 24 hours. Proposed Solution: - Provision an Azure Event Hub. - Configure the machine identifier as the partition key. - Enable capture. Analysis: - Azure Event Hub: - Event Hub as a data streaming service is designed to handle high-throughput data ingestion, which suits the large volume of data coming from 2,000 stores. However, it primarily focuses on real-time data processing rather than persistent storage. - Partitioning by Machine Identifier: By using the machine identifier as the partition key, the data from each device can be kept in distinct partitions, making it easier to correlate the device data. This ensures that data from the same device is processed together in the same partition. - Capture feature: The Capture feature of Event Hub allows you to automatically store incoming event data to Azure Blob Storage in a structur...

Author: Leah · Last updated May 11, 2026

DRAG DROP - You are developing an Azure solution to collect inventory data from thousands of stores located around the world. Each store location will send the inventory data hourly to an Azure Blob storage account for processing. The solution must meet the following requirements: * Begin processing when data is saved to Azure Blob storage. * Filter data based on store location information. * Trigger an Azure Logic App to process the data for output to Azure Cosmos DB. * Enable high availability and geographic distribution. * Allow 24-hours for retries. ...

Author: Matthew · Last updated May 11, 2026

You are creating an app that will use CosmosDB for data storage. The app will process batches of relational data. You need t...

Let's analyze the options based on the given requirement: Requirement: - The app will use CosmosDB for data storage and will process batches of relational data. Option A: MongoDB API - The MongoDB API allows you to use CosmosDB with a MongoDB-compatible interface. - MongoDB is a NoSQL database, which is designed for document-based storage (JSON-like documents). - Relational Data is not the best fit for MongoDB since it's designed for flexible, schema-less data structures. - Rejection Reason: This API is not ideal for relational data processing since it does not natively support relational concepts like tables, joins, or structured schemas. Option B: Table API - The Table API in CosmosDB provides a key-value store (similar to Azure Table Storage). - It is typically used for non-relational data with simple key-value access patterns and is best for storing large amounts of non-relational data. - Rejection Reason: The Table API is not suitable for relational data because it doesn't support relational features like joins or foreign keys, which are necessary for processing relational data. Option C: SQL API - The SQL API in CosmosDB is a document-based API but it provides support for SQL-like querying, which is useful for querying and processing data in a structured format. - Although Cosmo...

Author: Noah · Last updated May 11, 2026

HOTSPOT - You are developing a .NET application that communicates with Azure Storage. A message must be stored when the application initializes. You need to implement the message. How should you complete the code segment? To answer, select...

Author: Emily · Last updated May 11, 2026

HOTSPOT - A software as a service (SaaS) company provides document management services. The company has a service that consists of several Azure web apps. All Azure web apps run in an Azure App Service Plan named PrimaryASP. You are developing a new web service by using a web app named ExcelParser. The web app contains a third-party library for processing Microsoft Excel files. The license for the third-party library stipulates that you can only run a single instance of t...

Author: Ryan · Last updated May 11, 2026

DRAG DROP - You have an application that provides weather forecasting data to external partners. You use Azure API Management to publish APIs. You must change the behavior of the API to meet the following requirements: * Support alternative input parameters * Remove formatting text from responses * Provide additional context to back-end services Which types of policies should you implement? To answer, drag the policy types to the correct requirements. Each p...

Author: Rahul · Last updated May 11, 2026

You are developing an e-commerce solution that uses a microservice architecture. You need to design a communication backplane for communicating transactional messages between various parts of the solution...

When designing an e-commerce solution using a microservice architecture and requiring FIFO (First-In-First-Out) message ordering, the choice of communication backplane is critical. Let's examine each option: A) Azure Storage Queue - Pros: - FIFO support: Azure Storage Queues support FIFO behavior, making it suitable for scenarios where the order of processing is important. - Low cost: It is relatively inexpensive for simple message queues with moderate throughput requirements. - Cons: - Limited features: It has fewer features compared to other options (e.g., lacks message routing, dead-letter queues, and does not support message ordering for multiple consumers). - Scalability: While it can scale, it is not as robust as Azure Service Bus in handling high throughput with more advanced features. - Best use case: Suitable for simple use cases where low cost and FIFO order are essential, and the advanced features of other services are not needed. B) Azure Event Hub - Pros: - High throughput: Designed for handling large-scale streaming and event ingestion scenarios (millions of events per second). - Scalability: Highly scalable and suited for big data and telemetry use cases. - Cons: - No FIFO ordering: Event Hubs do not guarantee FIFO message ordering. - Not transactional: It is more for stream processing rather than transactional messages. - Best use case: Ideal for real-time analytics, telemetry data ingestion, or high-throughput event streaming, but not suitable for transactional messages where order is crucial. C) Azure Service Bus - Pros: - FIFO support: Azure Service Bus supports FIFO message ordering, especially when using queues (message order can be preserved as long as a single consumer is reading the messages). - Advanced features: It supports messa...

Author: VioletCheetah55 · Last updated May 11, 2026

DRAG DROP - A company backs up all manufacturing data to Azure Blob Storage. Admins move blobs from hot storage to archive tier storage every month. You must automatically move blobs to Archive tier after they have not been modified within 180 days. The path for any item that is not archived must be placed in an existing queue. This operation must be performed automatically once a month. You set the value of TierAgeInDays to -180. How should you configure the Logic App? To answer, drag the appropriate triggers or action blocks to the correct trigger...

Author: NightmareDragon2025 · Last updated May 11, 2026

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are developing an Azure Service application that processes queue data when it receives a message from a mobile application. Messages may not be sent to the service consistently. You have the following requirements: * Queue size must not grow larger than 80 gigabytes (GB). * Use first-in-first-o...

Evaluation of the Solution: The proposed solution involves using an Azure Service Bus Queue triggered by an Azure Function App. Let’s analyze this approach with respect to the requirements: Queue Size Limitation: - Azure Service Bus Queue supports a maximum size of 80 GB for a standard tier. This aligns with the stated requirement of not exceeding 80 GB for the queue size. However, keep in mind that this solution should avoid creating a queue that would potentially grow beyond this size, which could require monitoring and implementing some auto-scaling or cleanup strategy. FIFO Ordering: - Azure Service Bus does support FIFO (First-In-First-Out) message ordering, but it is only guaranteed under certain conditions. FIFO order is maintained as long as messages are processed by a single consumer or the same session is used to process messages. If the queue is used in this manner (i.e., one consumer or with sessions enabled), the FIFO requirement would be met. - However, if there are multiple consumers, FIFO ordering may not be guaranteed across them unless session-based queues are used. But since the solution does not specify multiple consumers, we can assume FIFO can be maintained if used correctly. Minimize Azure Costs: - Azure Service Bus is more expensive than Azure Storage Queues, especially for standard messaging scenarios. While Azure Service Bus provides the required FIFO functionality and other advanced features (like message sessions, dead-lette...

Author: Daniel · Last updated May 11, 2026