Mulesoft MCPA-Level-1 Exam Questions

151 Questions


Updation Date : 29-Jan-2026



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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)
*****************************************
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.

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

A circuit breaker strategy is planned in order to meet the goal of improved response time and demand on a downstream API.

  • Circuit Open: More than 10 errors per minute for three minutes
  • Circuit Half-Open: One error per minute
  • Circuit Closed: Less than one error per minute for five minutes
Out of several proposals from the engineering team, which option will meet this goal?


A. Create a custom policy that implements the circuit breaker and includes policy template expressions for the required settings


B. Create Anypoint Monitoring alerts for Circuit Open/Closed configurations, and then implement a retry strategy for Circuit Half-Open configuration


C. Add the Circuit Breaker policy to the API instance, and configure the required settings


D. Implement the strategy in a Mule application, and provide the settings in the YAML configuration





C.
  Add the Circuit Breaker policy to the API instance, and configure the required settings

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?


A. Custom dashboards


B. Built-in dashboards


C. Functional monitoring


D. API Manager





B.
  Built-in dashboards

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 best explains the use of auto-discovery in API implementations?


A. It makes API Manager aware of API implementations and hence enables it to enforce policies


B. It enables Anypoint Studio to discover API definitions configured in Anypoint Platform


C. It enables Anypoint Exchange to discover assets and makes them available for reuse


D. It enables Anypoint Analytics to gain insight into the usage of APIs





A.
  It makes API Manager aware of API implementations and hence enables it to enforce policies

Explanation: Explanation
Correct Answer: It makes API Manager aware of API implementations and hence enables it
to enforce policies.
*****************************************
>> API Autodiscovery is a mechanism that manages an API from API Manager by pairing
the deployed application to an API created on the platform.
>> API Management includes tracking, enforcing policies if you apply any, and reporting
API analytics.
>> Critical to the Autodiscovery process is identifying the API by providing the API name
and version.
References:
https://docs.mulesoft.com/api-manager/2.x/api-auto-discovery-new-concept
https://docs.mulesoft.com/api-manager/1.x/api-auto-discovery
https://docs.mulesoft.com/api-manager/2.x/api-auto-discovery-new-concept

A client has several applications running on the Salesforce service cloud. The business requirement for integration is to get daily data changes from Account and Case Objects. Data needs to be moved to the client's private cloud AWS DynamoDB instance as a single JSON and the business foresees only wanting five attributes from the Account object, which has 219 attributes (some custom) and eight attributes from the Case Object. What design should be used to support the API/ Application data model?


A. Create separate entities for Account and Case Objects by mimicking all the attributes in SAPI, which are combined by the PAPI and filtered to provide JSON output containing 13 attributes.


B. Request client’s AWS project team to replicate all the attributes and create Account and Case JSON table in DynamoDB. Then create separate entities for Account and Case Objects by mimicking all the attributes in SAPI to transfer ISON data to DynamoD for respective Objects


C. Start implementing an Enterprise Data Model by defining enterprise Account and Case Objects and implement SAPI and DynamoDB tables based on the Enterprise Data Model,


D. Create separate entities for Account with five attributes and Case with eight attributes in SAPI, which are combined by the PAPI to provide JSON output containing 13 attributes.





D.
  Create separate entities for Account with five attributes and Case with eight attributes in SAPI, which are combined by the PAPI to provide JSON output containing 13 attributes.

Refer to the exhibit. An organization is running a Mule standalone runtime and has
configured Active Directory as the Anypoint Platform external Identity Provider. The organization does not have budget for other system components.

What policy should be applied to all instances of APIs in the organization to most
effecuvelyKestrict access to a specific group of internal users?


A.

Apply a basic authentication - LDAP policy; the internal Active Directory will be
configured as the LDAP source for authenticating users


B.

Apply a client ID enforcement policy; the specific group of users will configure their client applications to use their specific client credentials


C.

Apply an IP whitelist policy; only the specific users' workstations will be in the whitelist


D.

Apply an OAuth 2.0 access token enforcement policy; the internal Active Directory will be configured as the OAuth server





A.
  

Apply a basic authentication - LDAP policy; the internal Active Directory will be
configured as the LDAP source for authenticating users



Explanation: Explanation
Correct Answer: Apply a basic authentication - LDAP policy; the internal Active Directory
will be configured as the LDAP source for authenticating users.
*****************************************
>> IP Whitelisting does NOT fit for this purpose. Moreover, the users workstations may not
necessarily have static IPs in the network.
>> OAuth 2.0 enforcement requires a client provider which isn't in the organizations system
components.
>> It is not an effective approach to let every user create separate client credentials and
configure those for their usage.
The effective way it to apply a basic authentication - LDAP policy and the internal Active
Directory will be configured as the LDAP source for authenticating users.
Reference: https://docs.mulesoft.com/api-manager/2.x/basic-authentication-ldap-concept


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