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MCPA-Level-1 Exam Labs | Exam MCPA-Level-1 Pattern

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MuleSoft Certified Platform Architect - Level 1 Sample Questions (Q134-Q139):

NEW QUESTION # 134
A Rate Limiting policy is applied to an API implementation to protect the back-end system. Recently, there have been surges in demand that cause some API client POST requests to the API implementation to be rejected with policy-related errors, causing delays and complications to the API clients.
How should the API policies that are applied to the API implementation be changed to reduce the frequency of errors returned to API clients, while still protecting the back-end system?

A. Keep the Rate Limiting policy and add an SLA-based Spike Control policy
B. Keep the Rate Limiting policy and add 9 Client ID Enforcement policy
C. Remove the Rate Limiting policy and add an HTTP Caching policy
D. Remove the Rate Limiting policy and add a Spike Control policy

Answer: A

Explanation:
When managing high traffic to an API, especially with POST requests, it is crucial to ensure the API's policies both protect the back-end systems and provide a smooth client experience. Here's the approach to reducing errors:
* Rate Limiting Policy: This policy enforces a limit on the number of requests within a defined time period. However, rate limiting alone may cause clients to hit limits during demand surges, leading to errors.
* Adding an SLA-based Spike Control Policy:
* Spike Control is designed to handle sudden increases in traffic by smoothing out bursts of requests, which is particularly useful during high-demand periods.
* By configuring SLA-based Spike Control, you can define thresholds for specific client tiers. For instance, premium clients might have higher limits or more flexibility in traffic bursts than standard clients.
* Why Option D is Correct:
* Keeping the Rate Limiting policy continues to provide baseline protection for the back-end.
* Adding the SLA-based Spike Control policy allows for differentiated control, where requests are queued or delayed during bursts rather than outright rejected. This approach significantly reduces error responses to clients while still controlling overall traffic.
* Explanation of Incorrect Options:
* Option A (adding Client ID Enforcement) would not reduce errors related to traffic surges.
* Option B (HTTP Caching) is not applicable as caching is generally ineffective for non- idempotent requests like POST.
* Option C (only Spike Control without Rate Limiting) may leave the back-end system vulnerable to sustained high traffic levels, reducing protection.
ReferencesFor more information on configuring Rate Limiting and SLA-based Spike Control policies, refer to MuleSoft documentation on API Policies and Rate Limiting.

NEW QUESTION # 135
An operations team is analyzing the effort needed to set up monitoring of their application network. They are looking at which API invocation metrics can be used to identify and predict trouble without having to write custom scripts or install additional analytics software or tools.
Which type of metrics can satisfy this goal of directly identifying and predicting failures?

A. The number and types of past API invocations across the application network
B. The number and types of API policy violations per day
C. The ROI from each APT invocation
D. The effectiveness of the application network based on the level of reuse

Answer: B

Explanation:
To monitor an application network and predict issues without custom scripts, policy violation metrics are critical. They provide insights into potential problems by tracking instances where API usage does not conform to defined policies. Here's why this approach is suitable:
* Predictive Monitoring:
* Tracking API policy violations (such as rate limits or spike controls being hit) can indicate surges in traffic or misuse, which may lead to throttling or service degradation if not addressed.
* By monitoring these violations, teams can proactively adjust limits or optimize API handling to prevent actual failures.
* No Custom Scripting Needed:
* Policy violation metrics are available within MuleSoft's Anypoint Monitoring, meaning there's no need to implement custom solutions or external tools to gather and interpret this data.
* Explanation of Incorrect Options:
* Option B (effectiveness based on reuse) does not directly predict failures.
* Option C (past invocation counts) offers historical usage data but does not inherently identify issues.
* Option D (ROI from API invocation) is a business metric and does not provide technical insights for failure prediction.
ReferencesFor more details on leveraging policy violation metrics for proactive monitoring, refer to MuleSoft documentation on Anypoint Monitoring.

NEW QUESTION # 136
A company wants to move its Mule API implementations into production as quickly as possible. To protect access to all Mule application data and metadata, the company requires that all Mule applications be deployed to the company's customer-hosted infrastructure within the corporate firewall. What combination of runtime plane and control plane options meets these project lifecycle goals?

A. MuleSoft-hosted runtime plane and customer-hosted control plane
B. Manually provisioned customer-hosted runtime plane and MuleSoft-hosted control plane
C. Manually provisioned customer-hosted runtime plane and customer-hosted control plane
D. iPaaS provisioned customer-hosted runtime plane and MuleSoft-hosted control plane

Answer: C

Explanation:
Manually provisioned customer-hosted runtime plane and customer-hosted control plane
*****************************************
There are two key factors that are to be taken into consideration from the scenario given in the question.
>> Company requires both data and metadata to be resided within the corporate firewall
>> Company would like to go with customer-hosted infrastructure.
Any deployment model that is to deal with the cloud directly or indirectly (Mulesoft-hosted or Customer's own cloud like Azure, AWS) will have to share atleast the metadata.
Application data can be controlled inside firewall by having Mule Runtimes on customer hosted runtime plane. But if we go with Mulsoft-hosted/ Cloud-based control plane, the control plane required atleast some minimum level of metadata to be sent outside the corporate firewall.
As the customer requirement is pretty clear about the data and metadata both to be within the corporate firewall, even though customer wants to move to production as quickly as possible, unfortunately due to the nature of their security requirements, they have no other option but to go with manually provisioned customer-hosted runtime plane and customer-hosted control plane.

NEW QUESTION # 137
Which three tools automate the deployment of Mule applications?
Choose 3 answers

A. Anypoint Platform CLI
B. Runtime Manager
C. Mule Mayen plugin
D. Platform APIs
E. Anypoint Studio
F. API Community Manager

Answer: A,B,D

Explanation:
MuleSoft offers various tools to automate the deployment of Mule applications, which can streamline deployment and management processes. Here's how each tool supports automated deployment:
* Runtime Manager:
* Anypoint Runtime Manager is MuleSoft's web-based interface that allows users to deploy, manage, and monitor applications directly. It provides deployment automation through its user- friendly interface.
* Anypoint Platform CLI:
* The Anypoint CLI enables scripting of deployment and management tasks, making it possible to automate deployments via command-line scripts. This tool is ideal for CI/CD pipelines as it integrates with automated processes.
* Platform APIs:
* MuleSoft's Platform APIs allow programmatic access to deployment functions, enabling integration with external automation tools and CI/CD systems. These APIs facilitate deployment through RESTful calls, which can be automated for continuous delivery.
* Explanation of Incorrect Options:
* Option D (Anypoint Studio) is primarily for development and does not support deployment automation.
* Option E (Maven Plugin) can be used for building and deploying Mule applications but isn't classified as a platform tool for deployment.
* Option F (API Community Manager) is unrelated to deployment and instead focuses on managing API communities.
ReferencesFor detailed steps on automating deployments with these tools, refer to MuleSoft documentation on Runtime Manager, CLI, and Platform APIs.

NEW QUESTION # 138
When designing an upstream API and its implementation, the development team has been advised to NOT set timeouts when invoking a downstream API, because that downstream API has no SLA that can be relied upon. This is the only downstream API dependency of that upstream API.
Assume the downstream API runs uninterrupted without crashing. What is the impact of this advice?

A. A toad-dependent timeout of less than 1000 ms will be applied by the Mule runtime in which the downstream API implementation executes
B. A default timeout of 500 ms will automatically be applied by the Mule runtime in which the upstream API implementation executes
C. An SLA for the upstream API CANNOT be provided
D. The invocation of the downstream API will run to completion without timing out

Answer: C

Explanation:
An SLA for the upstream API CANNOT be provided.
*****************************************
>> First thing first, the default HTTP response timeout for HTTP connector is 10000 ms (10 seconds). NOT
500 ms.
>> Mule runtime does NOT apply any such "load-dependent" timeouts. There is no such behavior currently in Mule.
>> As there is default 10000 ms time out for HTTP connector, we CANNOT always guarantee that the invocation of the downstream API will run to completion without timing out due to its unreliable SLA times.
If the response time crosses 10 seconds then the request may time out.
The main impact due to this is that a proper SLA for the upstream API CANNOT be provided.

NEW QUESTION # 139
......

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