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.

What correctly characterizes unit tests of Mule applications?

A.

They test the validity of input and output of source and target systems

B.

They must be run in a unit testing environment with dedicated Mule runtimes for the environment

C.

They must be triggered by an external client tool or event source

D.

They are typically written using MUnit to run in an embedded Mule runtime that does not require external connectivity

D.

They are typically written using MUnit to run in an embedded Mule runtime that does not require external connectivity

Explanation: Explanation
Correct Answer: They are typically written using MUnit to run in an embedded Mule runtime
that does not require external connectivity.
*****************************************
Below TWO are characteristics of Integration Tests but NOT unit tests:
>> They test the validity of input and output of source and target systems.
>> They must be triggered by an external client tool or event source.
It is NOT TRUE that Unit Tests must be run in a unit testing environment with dedicated
Mule runtimes for the environment.
MuleSoft offers MUnit for writing Unit Tests and they run in an embedded Mule Runtime
without needing any separate/ dedicated Runtimes to execute them. They also do NOT
need any external connectivity as MUnit supports mocking via stubs.
https://dzone.com/articles/munit-framework

When can CloudHub Object Store v2 be used?

A. To store an unlimited number of key-value pairs

B. To store payloads with an average size greater than 15MB

C. To store information in Mule 4 Object Store v1

D. To store key-value pairs with keys up to 300 characters

Explanation: CloudHub Object Store v2 is a managed key-value store provided by MuleSoft to support various use cases where temporary data storage is required. Here’s why Option D is correct:
Key Length Support: Object Store v2 allows storage of keys with a length of up to 300 characters, making it suitable for applications needing flexible and descriptive keys.
Limitations on Size:
Key-Value Limits: Object Store v2 is designed for moderate, transient storage needs, and does not support unlimited storage. Thus, Option A is incorrect.
Backward Compatibility: Object Store v2 does not support Mule 4 applications running Object Store v1. Option C is incorrect as Object Store v1 and v2 are distinct.

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:

Refer to the exhibit.

What is the best way to decompose one end-to-end business process into a collaboration of Experience, Process, and System APIs?
A) Handle customizations for the end-user application at the Process API level rather than the Experience API level
B) Allow System APIs to return data that is NOT currently required by the identified Process or Experience APIs
C) Always use a tiered approach by creating exactly one API for each of the 3 layers (Experience, Process and System APIs)
D) Use a Process API to orchestrate calls to multiple System APIs, but NOT to other Process APIs

A. Option A

B. Option B

C. Option C

D. Option D

B. Option B

Explanation:
Correct Answer: Allow System APIs to return data that is NOT currently required by the identified Process or Experience APIs.

All customizations for the end-user application should be handled in "Experience API" only. Not in Process API
We should use tiered approach but NOT always by creating exactly one API for each of the 3 layers. Experience APIs might be one but Process APIs and System APIs are often more than one. System APIs for sure will be more than one all the time as they are the smallest modular APIs built in front of end systems.
Process APIs can call System APIs as well as other Process APIs. There is no such anti-design pattern in API-Led connectivity saying Process APIs should not call other Process APIs.

So, the right answer in the given set of options that makes sense as per API-Led connectivity principles is to allow System APIs to return data that is NOT currently required by the identified Process or Experience APIs. This way, some future Process APIs can make use of that data from System APIs and we need NOT touch the System layer APIs again and again.

An API is protected with a Client ID Enforcement policy and uses the default configuration. Access is requested for the client application to the API, and an approved contract now exists between the client application and the API. How can a consumer of this API avoid a 401 error "Unauthorized or invalid client application credentials"?

A. Send the obtained token as a header in every call

B. Send the obtained: client_id and client_secret in the request body

C. Send the obtained clent_id and clent_secret as URI parameters in every call

D. Send the obtained clent_id and client_secret in the header of every API Request call

C. Send the obtained clent_id and clent_secret as URI parameters in every call

Explanation:
When using the Client ID Enforcement policy with default settings, MuleSoft expects the client_id and client_secret to be provided in the URI parameters of each request. This policy is typically used to control and monitor access by validating that each request has valid credentials. Here’s how to avoid a 401 Unauthorized error:

URI Parameters Requirement:
Why Option C is Correct:
Explanation of Incorrect Options:

References:
For more details, consult MuleSoft’s documentation on Client ID Enforcement policies and expected request configurations

Which APIs can be used with DataGraph to create a unified schema?

A. APIs 1, 3, 5

B. APIs 2, 4 ,6

C. APIs 1, 2, s5, 6

D. APIs 1, 2, 3, 4

Explanation:
To create a unified schema in MuleSoft's DataGraph, APIs must be exposed in a way that allows DataGraph to pull and consolidate data from these APIs into a single schema accessible to consumers. DataGraph provides a federated approach, combining multiple APIs to form a single, unified API endpoint.
In this setup:
APIs 1, 2, 3, and 4 are suitable candidates for DataGraph because they are hosted within the Customer VPC on CloudHub and are accessible either through a Shared Load Balancer (LB) or a Dedicated Load Balancer (DLB). Both of these load balancers provide public access, which is a necessary condition for DataGraph as it must access the APIs to aggregate data.
APIs 5 and 6 are hosted on Customer Hosted Server 2, which is explicitly marked as "Not public". Since DataGraph requires API access through a publicly reachable endpoint to aggregate them into a unified schema, APIs 5 and 6 cannot be used with DataGraph in this configuration.
APIs 3 and 4 on Customer Hosted Server 1 appear accessible through a Shared LB, implying public accessibility that meets DataGraph’s requirements.
By combining APIs 1, 2, 3, and 4 within DataGraph, you can create a unified schema that enables clients to query data seamlessly from all these APIs as if it were from a single source.
This setup allows for efficient data retrieval and can simplify API consumption by reducing the need to call multiple APIs individually, thus optimizing performance and developer experience.

When must an API implementation be deployed to an Anypoint VPC?

A.

When the API Implementation must invoke publicly exposed services that are deployed outside of CloudHub in a customer- managed AWS instance

B.

When the API implementation must be accessible within a subnet of a restricted customer-hosted network that does not allow public access

C.

When the API implementation must be deployed to a production AWS VPC using the Mule Maven plugin

D.

When the API Implementation must write to a persistent Object Store

A.

When the API Implementation must invoke publicly exposed services that are deployed outside of CloudHub in a customer- managed AWS instance