Mulesoft MCPA-Level-1 Exam Questions

151 Questions


Updation Date : 1-Dec-2025



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An API implementation is updated. When must the RAML definition of the API also be updated?


A.

When the API implementation changes the structure of the request or response messages


B.

When the API implementation changes from interacting with a legacy backend system deployed on-premises to a modern, cloud-based (SaaS) system


C.

When the API implementation is migrated from an older to a newer version of the Mule runtime


D.

When the API implementation is optimized to improve its average response time





A.
  

When the API implementation changes the structure of the request or response messages



Explanation: Explanation
Correct Answer: When the API implementation changes the structure of the request or
response messages
*****************************************
>> RAML definition usually needs to be touched only when there are changes in the
request/response schemas or in any traits on API.
>> It need not be modified for any internal changes in API implementation like performance
tuning, backend system migrations etc

Due to a limitation in the backend system, a system API can only handle up to 500
requests per second. What is the best type of API policy to apply to the system API to avoid overloading the backend system?


A.

Rate limiting


B.

HTTP caching


C.

Rate limiting - SLA based


D.

Spike control





D.
  

Spike control



Explanation: Explanation
Correct Answer: Spike control
*****************************************
>> First things first, HTTP Caching policy is for purposes different than avoiding the
backend system from overloading. So this is OUT.
>> Rate Limiting and Throttling/ Spike Control policies are designed to limit API access, but
have different intentions.
>> Rate limiting protects an API by applying a hard limit on its access.
>> Throttling/ Spike Control shapes API access by smoothing spikes in traffic.
That is why, Spike Control is the right option

Select the correct Owner-Layer combinations from below options


A.

1. App Developers owns and focuses on Experience Layer APIs
2. Central IT owns and focuses on Process Layer APIs
3. LOB IT owns and focuses on System Layer APIs


B.

1. Central IT owns and focuses on Experience Layer APIs
2. LOB IT owns and focuses on Process Layer APIs
3. App Developers owns and focuses on System Layer APIs


C.

1. App Developers owns and focuses on Experience Layer APIs
2. LOB IT owns and focuses on Process Layer APIs
3. Central IT owns and focuses on System Layer APIs





C.
  

1. App Developers owns and focuses on Experience Layer APIs
2. LOB IT owns and focuses on Process Layer APIs
3. Central IT owns and focuses on System Layer APIs



Explanation: Explanation
Correct Answer:
1. App Developers owns and focuses on Experience Layer APIs
2. LOB IT owns and focuses on Process Layer APIs
3. Central IT owns and focuses on System Layer APIs

References:
https://blogs.mulesoft.com/biz/api/experience-api-ownership/
https://blogs.mulesoft.com/biz/api/process-api-ownership/
https://blogs.mulesoft.com/biz/api/system-api-ownership

Which statement is true about identity management and client management on Anypoint Platform?


A. If an external identity provider is configured, the SAML 2.0 bearer tokens issued by the identity provider cannot be used for invocations of the Anypoint Platform web APIs


B. If an external client provider is configured, it must be configured at the Anypoint Platform organization level and cannot be assigned to individual business groups and environments


C. Anypoint Platform supports configuring one external identity provider


D. Both client management and identity management require an identity provider





C.
  Anypoint Platform supports configuring one external identity provider

Explanation:
Anypoint Platform allows organizations to integrate one external identity provider (IdP) for identity and access management (IAM), supporting SSO and centralized user authentication.

  • Identity Provider Limit:
  • Explanation of Correct Answer (C):
  • Explanation of Incorrect Options:
References:
For further details on identity management options, consult MuleSoft documentation on Anypoint Platform’s IAM capabilities.

How can the application of a rate limiting API policy be accurately reflected in the RAML definition of an API?


A.

By refining the resource definitions by adding a description of the rate limiting policy behavior


B.

By refining the request definitions by adding a remaining Requests query parameter with description, type, and example


C.

By refining the response definitions by adding the out-of-the-box Anypoint Platform ratelimit-
enforcement securityScheme with description, type, and example


D.

By refining the response definitions by adding the x-ratelimit-* response headers with
description, type, and example





D.
  

By refining the response definitions by adding the x-ratelimit-* response headers with
description, type, and example



Explanation: Explanation
Correct Answer: By refining the response definitions by adding the x-ratelimit-* response
headers with description, type, and example
*****************************************

An organization makes a strategic decision to move towards an IT operating model that emphasizes consumption of reusable IT assets using modern APIs (as defined by MuleSoft). What best describes each modern API in relation to this new IT operating model?


A.

Each modern API has its own software development lifecycle, which reduces the need for documentation and automation


B.

Each modem API must be treated like a product and designed for a particular target audience (for instance, mobile app developers)


C.

Each modern API must be easy to consume, so should avoid complex authentication mechanisms such as SAML or JWT D


D.

Each modern API must be REST and HTTP based





B.
  

Each modem API must be treated like a product and designed for a particular target audience (for instance, mobile app developers)



Explanation: Explanation
Correct Answers:
1. Each modern API must be treated like a product and designed for a particular target
audience (for instance mobile app developers)
*****************************************


A retail company is using an Order API to accept new orders. The Order API uses a JMS
queue to submit orders to a backend order management service. The normal load for
orders is being handled using two (2) CloudHub workers, each configured with 0.2 vCore.
The CPU load of each CloudHub worker normally runs well below 70%. However, several
times during the year the Order API gets four times (4x) the average number of orders.
This causes the CloudHub worker CPU load to exceed 90% and the order submission time
to exceed 30 seconds. The cause, however, is NOT the backend order management
service, which still responds fast enough to meet the response SLA for the Order API.
What is the MOST resource-efficient way to configure the Mule application's CloudHub
deployment to help the company cope with this performance challenge?


A.

Permanently increase the size of each of the two (2) CloudHub workers by at least four
times (4x) to one (1) vCore


B.

Use a vertical CloudHub autoscaling policy that triggers on CPU utilization greater than
70%


C.

Permanently increase the number of CloudHub workers by four times (4x) to eight (8)
CloudHub workers


D.

Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater
than 70%





D.
  

Use a horizontal CloudHub autoscaling policy that triggers on CPU utilization greater
than 70%



Explanation: Explanation
Correct Answer: Use a horizontal CloudHub autoscaling policy that triggers on CPU
utilization greater than 70%
*****************************************
The scenario in the question is very clearly stating that the usual traffic in the year is pretty
well handled by the existing worker configuration with CPU running well below 70%. The
problem occurs only "sometimes" occasionally when there is spike in the number of orders
coming in.
So, based on above, We neither need to permanently increase the size of each worker nor
need to permanently increase the number of workers. This is unnecessary as other than
those "occasional" times the resources are idle and wasted.
We have two options left now. Either to use horizontal Cloudhub autoscaling policy to
automatically increase the number of workers or to use vertical Cloudhub autoscaling
policy to automatically increase the vCore size of each worker.
Here, we need to take two things into consideration:
1. CPU
2. Order Submission Rate to JMS Queue
>> From CPU perspective, both the options (horizontal and vertical scaling) solves the
issue. Both helps to bring down the usage below 90%.
>> However, If we go with Vertical Scaling, then from Order Submission Rate perspective,
as the application is still being load balanced with two workers only, there may not be much
improvement in the incoming request processing rate and order submission rate to JMS
queue. The throughput would be same as before. Only CPU utilization comes down.
>> But, if we go with Horizontal Scaling, it will spawn new workers and adds extra hand to
increase the throughput as more workers are being load balanced now. This way we can
address both CPU and Order Submission rate.
Hence, Horizontal CloudHub Autoscaling policy is the right and best answer.

An API with multiple API implementations (Mule applications) is deployed to both CloudHub and customer-hosted Mule runtimes. All the deployments are managed by the MuleSoft-hosted control plane. An alert needs to be triggered whenever an API implementation stops responding to API requests, even if no API clients have called the API implementation for some time. What is the most effective out-of-the-box solution to create these alerts to monitor the API implementations?


A. Create monitors in Anypoint Functional Monitoring for the API implementations, where each monitor repeatedly invokes an API implementation endpoint


B. Add code to each API client to send an Anypoint Platform REST API request to generate a custom alert in Anypoint Platform when an API invocation times out


C. Handle API invocation exceptions within the calling API client and raise an alert from that API client when such an exception is thrown


D. Configure one Worker Not Responding alert.in Anypoint Runtime Manager for all API implementations that will then monitor every API implementation





A.
  Create monitors in Anypoint Functional Monitoring for the API implementations, where each monitor repeatedly invokes an API implementation endpoint

Explanation:
In scenarios where multiple API implementations are deployed across different environments (CloudHub and customer-hosted runtimes), Anypoint Functional Monitoring is the most effective tool to monitor API availability and trigger alerts when an API implementation becomes unresponsive. Here’s how it works:

  • Using Anypoint Functional Monitoring:
  • Why Option A is Correct:
  • Explanation of Incorrect Options:
References:
For further information, refer to MuleSoft documentation on Anypoint Functional Monitoring setup and usage for API availability monitoring.


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