Mulesoft MCPA-Level-1 Exam Questions

Refer to the exhibit.

Three business processes need to be implemented, and the implementations need to communicate with several different SaaS applications.
These processes are owned by separate (siloed) LOBs and are mainly independent of each other, but do share a few business entities. Each LOB has one development team and their own budget.
In this organizational context, what is the most effective approach to choose the API data models for the APIs that will implement these business processes with minimal redundancy of the data models?
A) Build several Bounded Context Data Models that align with coherent parts of the business processes and the definitions of associated business entities.
B) Build distinct data models for each API to follow established micro-services and Agile API-centric practices
C) Build all API data models using XML schema to drive consistency and reuse across the organization
D) Build one centralized Canonical Data Model (Enterprise Data Model) that unifies all the data types from all three business processes, ensuring the data model is consistent and non-redundant

A. Option A

B. Option B

C. Option C

D. Option D

A. Option A

Explanation:

Correct Answer: Build several Bounded Context Data Models that align with coherent parts of the business processes and the definitions of associated business entities.

The options w.r.t building API data models using XML schema/ Agile API-centric practices are irrelevant to the scenario given in the question. So these two are INVALID.
Building EDM (Enterprise Data Model) is not feasible or right fit for this scenario as the teams and LOBs work in silo and they all have different initiatives, budget etc.. Building EDM needs intensive coordination among all the team which evidently seems not possible in this scenario.

So, the right fit for this scenario is to build several Bounded Context Data Models that align with coherent parts of the business processes and the definitions of associated business entities.

A retail company with thousands of stores has an API to receive data about purchases and
insert it into a single database. Each individual store sends a batch of purchase data to the
API about every 30 minutes. The API implementation uses a database bulk insert
command to submit all the purchase data to a database using a custom JDBC driver
provided by a data analytics solution provider. The API implementation is deployed to a
single CloudHub worker. The JDBC driver processes the data into a set of several
temporary disk files on the CloudHub worker, and then the data is sent to an analytics
engine using a proprietary protocol. This process usually takes less than a few minutes.
Sometimes a request fails. In this case, the logs show a message from the JDBC driver
indicating an out-of-file-space message. When the request is resubmitted, it is successful.
What is the best way to try to resolve this throughput issue?

A.

se a CloudHub autoscaling policy to add CloudHub workers

B.

Use a CloudHub autoscaling policy to increase the size of the CloudHub worker

C.

Increase the size of the CloudHub worker(s)

D.

Increase the number of CloudHub workers

D.

Increase the number of CloudHub workers

Explanation: Explanation
Correct Answer: Increase the size of the CloudHub worker(s)
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The key details that we can take out from the given scenario are:
>> API implementation uses a database bulk insert command to submit all the purchase
data to a database
>> JDBC driver processes the data into a set of several temporary disk files on the
CloudHub worker
>> Sometimes a request fails and the logs show a message indicating an out-of-file-space
message
Based on above details:
>> Both auto-scaling options does NOT help because we cannot set auto-scaling rules
based on error messages. Auto-scaling rules are kicked-off based on CPU/Memory usages
and not due to some given error or disk space issues.
>> Increasing the number of CloudHub workers also does NOT help here because the
reason for the failure is not due to performance aspects w.r.t CPU or Memory. It is due to
disk-space.
>> Moreover, the API is doing bulk insert to submit the received batch data. Which means,
all data is handled by ONE worker only at a time. So, the disk space issue should be
tackled on "per worker" basis. Having multiple workers does not help as the batch may still
fail on any worker when disk is out of space on that particular worker.
Therefore, the right way to deal this issue and resolve this is to increase the vCore size of
the worker so that a new worker with more disk space will be provisioned.

A TemperatureSensors API instance is defined in API Manager in the PROD environment of the CAR_FACTORY business group. An AcmelemperatureSensors Mule application implements this API instance and is deployed from Runtime Manager to the PROD environment of the CAR_FACTORY business group. A policy that requires a valid client ID and client secret is applied in API Manager to the API instance.
Where can an API consumer obtain a valid client ID and client secret to call the AcmeTemperatureSensors Mule application?

A. In secrets manager, request access to the Shared Secret static username/password

B. In API Manager, from the PROD environment of the CAR_FACTORY business group

C. In access management, from the PROD environment of the CAR_FACTORY business group

D. In Anypoint Exchange, from an API client application that has been approved for the TemperatureSensors API instance

Explanation:
When an API policy requiring a client ID and client secret is applied to an API instance in API Manager, API consumers must obtain these credentials through a registered client application. Here’s how it works:

Anypoint Exchange and Client Applications:
Why Option D is Correct:
Explanation of Incorrect Options:

A large organization with an experienced central IT department is getting started using MuleSoft. There is a project to connect a siloed back-end system to a new Customer Relationship Management (CRM) system. The Center for Enablement is coaching them to use API-led connectivity. What action would support the creation of an application network using API-led connectivity?

A. Invite the business analyst to create a business process model to specify the canonical data model between the two systems

B. Determine if the new CRM system supports the creation of custom: REST APIs, establishes 4 private network with CloudHub, and supports GAuth 2.0 authentication

C. To expedite this project, central IT should extend the CRM system and back-end systems to connect to one another using built in integration interfaces

D. Create a System API to unlock the data on the back-end system using a REST API

Explanation:
For an organization starting with API-led connectivity to integrate a siloed back-end system with a new CRM, the following approach aligns with best practices and MuleSoft’s Center for Enablement (C4E) guidance:
API-led Connectivity: This model organizes APIs into distinct layers (System, Process, and Experience) to improve reusability, modularity, and manageability.

Step to Support Application Network:
Why Option D is Correct:
Explanation of Incorrect Options:

Refer to the exhibit. An organization needs to enable access to their customer data from
both a mobile app and a web application, which each need access to common fields as
well as certain unique fields.
The data is available partially in a database and partially in a 3rd-party CRM system.
What APIs should be created to best fit these design requirements?

A.

Option A

B.

Option B

C.

Option C

D.

Option D

C.

Option C

Explanation: Explanation
Correct Answer: Separate Experience APIs for the mobile and web app, but a common
Process API that invokes separate System APIs created for the database and CRM system
*****************************************
As per MuleSoft's API-led connectivity:

>> Experience APIs should be built as per each consumer needs and their experience.
>> Process APIs should contain all the orchestration logic to achieve the business
functionality.
>> System APIs should be built for each backend system to unlock their data.
Reference: https://blogs.mulesoft.com/dev/api-dev/what-is-api-led-connectivity

Refer to the exhibit.

A developer is building a client application to invoke an API deployed to the STAGING
environment that is governed by a client ID enforcement policy.
What is required to successfully invoke the API?

A.

The client ID and secret for the Anypoint Platform account owning the API in the STAGING environment

B.

The client ID and secret for the Anypoint Platform account's STAGING environment

C.

The client ID and secret obtained from Anypoint Exchange for the API instance in the
STAGING environment

D.

A valid OAuth token obtained from Anypoint Platform and its associated client ID and
secret

C.

The client ID and secret obtained from Anypoint Exchange for the API instance in the
STAGING environment

Explanation: Explanation
Correct Answer: The client ID and secret obtained from Anypoint Exchange for the API
instance in the STAGING environment
*****************************************
>> We CANNOT use the client ID and secret of Anypoint Platform account or any individual
environments for accessing the APIs
>> As the type of policy that is enforced on the API in question is "Client ID Enforcment
Policy", OAuth token based access won't work.
Right way to access the API is to use the client ID and secret obtained from Anypoint
Exchange for the API instance in a particular environment we want to work on.
References:
Managing API instance Contracts on API Manager
https://docs.mulesoft.com/api-manager/1.x/request-access-to-api-task
https://docs.mulesoft.com/exchange/to-request-access
https://docs.mulesoft.com/api-manager/2.x/policy-mule3-client-id-based-policies

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 9 Client ID Enforcement policy

B. Remove the Rate Limiting policy and add an HTTP Caching policy

C. Remove the Rate Limiting policy and add a Spike Control policy

D. Keep the Rate Limiting policy and add an SLA-based Spike Control policy

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:
Why Option D is Correct:
Explanation of Incorrect Options:

An organization wants to make sure only known partners can invoke the organization's
APIs. To achieve this security goal, the organization wants to enforce a Client ID
Enforcement policy in API Manager so that only registered partner applications can invoke
the organization's APIs. In what type of API implementation does MuleSoft recommend
adding an API proxy to enforce the Client ID Enforcement policy, rather than embedding
the policy directly in the application's JVM?

A.

A Mule 3 application using APIkit

B.

A Mule 3 or Mule 4 application modified with custom Java code

C.

A Mule 4 application with an API specification

D.

A Non-Mule application

D.

A Non-Mule application

Explanation: Explanation
Correct Answer: A Non-Mule application
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>> All type of Mule applications (Mule 3/ Mule 4/ with APIkit/ with Custom Java Code etc)
running on Mule Runtimes support the Embedded Policy Enforcement on them.
>> The only option that cannot have or does not support embedded policy enforcement
and must have API Proxy is for Non-Mule Applications.
So, Non-Mule application is the right answer