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| Section | Objectives |
|---|---|
| Integration Architecture Strategy | - System, process, and experience APIs - API-led connectivity principles - Designing enterprise integration architecture |
| Performance and Scalability | - Scaling Mule applications - High availability design patterns |
| Security and Compliance | - Secure API exposure and threat protection - Authentication and authorization mechanisms |
| API Management and Governance | - API lifecycle management - API security policies and enforcement - Governance frameworks and best practices |
| Data Integration and Transformation | - Batch vs real-time integration patterns - Data mapping and transformation strategies |
| Anypoint Platform Architecture | - Anypoint Platform components and capabilities - Runtime Fabric architecture overview - Deployment models (CloudHub, hybrid, on-premises) |
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NEW QUESTION # 51
An online store's marketing team has noticed an increase in customers leaving online baskets without checking out. They suspect a technology issue is at the root cause of the baskets being left behind. They approach the Center for Enablement to ask for help identifying the issue. Multiple APIs from across all the layers of their application network are involved in the shopping application.
Which feature of the Anypoint Platform can be used to view metrics from all involved APIs at the same time?
Answer: C
Explanation:
Understanding the Need for Cross-API Monitoring:
The Center for Enablement (C4E) needs to investigate potential technical issues across multiple APIs in the application network that may be causing customers to abandon their carts.
This requires a solution that allows viewing metrics across several APIs in real-time to identify any performance issues or bottlenecks.
Evaluating Anypoint Platform Features:
Built-in Dashboards: Anypoint Platform provides built-in dashboards in Anypoint Monitoring, allowing teams to view metrics from multiple APIs in a single interface. This feature is designed to monitor API performance, latency, errors, and throughput, and is ideal for tracking performance across all layers of the application network.
Custom Dashboards: While custom dashboards allow for more tailored views, the built-in dashboards already aggregate metrics for multiple APIs, making it unnecessary to build a custom solution for this scenario.
Functional Monitoring: This feature is used to set up tests to monitor specific API functionality and uptime but is not suited for tracking metrics across multiple APIs in real-time.
API Manager: API Manager primarily focuses on managing API policies, contracts, and access control rather than providing detailed, real-time metrics across the entire application network.
Conclusion:
Option B (Built-in dashboards) is the best choice because it provides a comprehensive view of metrics from all APIs involved, enabling the C4E team to quickly identify any issues that may be contributing to abandoned shopping carts.
Refer to MuleSoft's documentation on Anypoint Monitoring and built-in dashboards for more details on configuring and using these dashboards effectively.
NEW QUESTION # 52
Several times a week, an API implementation shows several thousand requests per minute in an Anypoint Monitoring dashboard, Between these bursts, the dashboard shows between two and five requests per minute. The API implementation is running on Anypoint Runtime Fabric with two non-clustered replicas, reserved vCPU 1.0 and vCPU Limit 2.0.
An API consumer has complained about slow response time, and the dashboard shows the 99 percentile is greater than 120 seconds at the time of the complaint. It also shows greater than 90% CPU usage during these time periods.
In manual tests in the QA environment, the API consumer has consistently reproduced the slow response time and high CPU usage, and there were no other API requests at this time. In a brainstorming session, the engineering team has created several proposals to reduce the response time for requests.
Which proposal should be pursued first?
Answer: D
Explanation:
Scenario Analysis:
The API implementation is experiencing high CPU usage (over 90%) during bursts of requests, which correlates with slow response times, as indicated by a 99th percentile response time greater than 120 seconds.
The API implementation is running on Anypoint Runtime Fabric with two non-clustered replicas and has a reserved vCPU of 1.0 and a vCPU limit of 2.0.
The high CPU usage during bursts suggests that the current resources may not be sufficient to handle peak loads.
Evaluating the Options:
Option A (Correct Answer): Increasing the vCPU resources for each replica would provide more processing power to handle high traffic volumes, potentially reducing the response time during spikes. Since the CPU usage is consistently high during bursts, this option directly addresses the resource bottleneck.
Option B: Modifying the API client to split requests may reduce individual request load but could be complex to implement on the client side and may not fully address the high CPU issue.
Option C: Increasing the number of replicas could help distribute the load; however, with a high CPU load on each replica, adding more replicas without increasing CPU resources may not fully resolve the problem.
Option D: Throttling the client would reduce the number of requests, but this may not be acceptable if the client needs to maintain a high request rate. It also does not directly address the CPU limitations of the API implementation.
Conclusion:
Option A is the best choice as it addresses the root cause of high CPU usage by increasing the vCPU allocation, allowing the API to handle more requests efficiently. This should be pursued first before considering other options.
Refer to MuleSoft's documentation on Runtime Fabric and vCPU resource allocation for more details on optimizing API performance in high-demand environments.
NEW QUESTION # 53
A company has started to create an application network and is now planning to implement a Center for Enablement (C4E) organizational model. What key factor would lead the company to decide upon a federated rather than a centralized C4E?
Answer: C
Explanation:
Correct Answe r: When development is already organized into several independent initiatives or groups
*****************************************
>> It would require lot of process effort in an organization to have a single C4E team coordinating with multiple already organized development teams which are into several independent initiatives. A single C4E works well with different teams having at least a common initiative. So, in this scenario, federated C4E works well instead of centralized C4E.
NEW QUESTION # 54
The asset version 2.0.0 of the Order API is successfully published in Exchange and configured in API Manager with the Autodiscovery API ID correctly linked to the API implementation, A new GET method is added to the existing API specification, and after updates, the asset version of the Order API is 2.0.1, What happens to the Autodiscovery API ID when the new asset version is updated in API Manager?
Answer: B
Explanation:
Understanding API Autodiscovery in MuleSoft:
API Autodiscovery links an API implementation in Anypoint Platform with its configuration in API Manager. This is controlled by the API ID which is set in the API Autodiscovery element in the Mule application.
The API ID remains consistent across minor updates to the API asset version in Exchange (e.g., from 2.0.0 to 2.0.1) as long as it is the same API.
Effect of Asset Version Update on API Autodiscovery:
When the asset version is updated (e.g., from 2.0.0 to 2.0.1), the API ID remains the same. Therefore, no changes are needed in the Autodiscovery configuration within the Mule application. The Autodiscovery will continue to link the API implementation to the latest version in API Manager.
Evaluating the Options:
Option A: Incorrect, as the API ID does not automatically change with minor asset version updates.
Option B: Incorrect, as the API ID remains the same, so no update is needed in the API implementation.
Option C (Correct Answer): The API ID does not change, so no changes are necessary in the API implementation for the new asset version.
Option D: Incorrect, as there is no need to update the API implementation in the Autodiscovery global element for minor version changes.
Conclusion:
Option C is the correct answer, as the API ID remains unchanged with minor version updates, and no changes are needed in the API Autodiscovery configuration.
Refer to MuleSoft documentation on API Autodiscovery and version management for more details.
NEW QUESTION # 55
What CANNOT be effectively enforced using an API policy in Anypoint Platform?
Answer: A
Explanation:
Correct Answe r: Guarding against Denial of Service attacks
*****************************************
>> Backend system overloading can be handled by enforcing "Spike Control Policy"
>> Logging HTTP requests and responses can be done by enforcing "Message Logging Policy"
>> Credentials can be tamper-proofed using "Security" and "Compliance" Policies However, unfortunately, there is no proper way currently on Anypoint Platform to guard against DOS attacks.
NEW QUESTION # 56
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