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MuleSoft MCPA-Level-1 Exam Questions Dumps


Exam Code: MCPA-Level-1
Exam Name: MuleSoft Certified Platform Architect - Level 1

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MuleSoft MCPA-Level-1 Exam Questions


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MCPA-Level-1 Exam Sample Questions:



A Mule application exposes an HTTPS endpoint and is deployed to three CloudHub
workers that do not use static IP addresses. The Mule application expects a high volume of
client requests in short time periods. What is the most cost-effective infrastructure
component that should be used to serve the high volume of client requests?

 

A customer-hosted load balancer

 

The CloudHub shared load balancer

 

An API proxy

 

Runtime Manager autoscaling


The CloudHub shared load balancer


Explanation: Explanation
Correct Answer: The CloudHub shared load balancer
*****************************************
The scenario in this question can be split as below:
>> There are 3 CloudHub workers (So, there are already good number of workers to
handle high volume of requests)
>> The workers are not using static IP addresses (So, one CANNOT use customer loadbalancing
solutions without static IPs)
>> Looking for most cost-effective component to load balance the client requests among
the workers.
Based on the above details given in the scenario:
>> Runtime autoscaling is NOT at all cost-effective as it incurs extra cost. Most over, there
are already 3 workers running which is a good number.
>> We cannot go for a customer-hosted load balancer as it is also NOT most cost-effective
(needs custom load balancer to maintain and licensing) and same time the Mule App is not
having Static IP Addresses which limits from going with custom load balancing.
>> An API Proxy is irrelevant there as it has no role to play w.r.t handling high volumes or
load balancing.
So, the only right option to go with and fits the purpose of scenario being most costeffective
is - using a CloudHub Shared Load Balancer





A code-centric API documentation environment should allow API consumers to investigate
and execute API client source code that demonstrates invoking one or more APIs as part of
representative scenarios.
What is the most effective way to provide this type of code-centric API documentation
environment using Anypoint Platform?

 

Enable mocking services for each of the relevant APIs and expose them via their Anypoint Exchange entry

 

Ensure the APIs are well documented through their Anypoint Exchange entries and API Consoles and share these pages with all API consumers

 

Create API Notebooks and include them in the relevant Anypoint Exchange entries

 

Make relevant APIs discoverable via an Anypoint Exchange entry


Create API Notebooks and include them in the relevant Anypoint Exchange entries


Explanation: Explanation
Correct Answer: Create API Notebooks and Include them in the relevant Anypoint
exchange entries
*****************************************
>> API Notebooks are the one on Anypoint Platform that enable us to provide code-centric
API documentation
: https://docs.mulesoft.com/exchange/to-use-api-notebook
Bottom of Form
Top of Form





A system API has a guaranteed SLA of 100 ms per request. The system API is deployed to
a primary environment as well as to a disaster recovery (DR) environment, with different
DNS names in each environment. An upstream process API invokes the system API and
the main goal of this process API is to respond to client requests in the least possible time.
In what order should the system APIs be invoked, and what changes should be made in
order to speed up the response time for requests from the process API?

 

In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment, and ONLY use the first response

 

In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment using a scatter-gather configured with a timeout, and then merge the responses

 

Invoke the system API deployed to the primary environment, and if it fails, invoke the system API deployed to the DR environment

 

Invoke ONLY the system API deployed to the primary environment, and add timeout and retry logic to avoid intermittent failures


In parallel, invoke the system API deployed to the primary environment and the system API deployed to the DR environment, and ONLY use the first response


Explanation: Explanation
Correct Answer: In parallel, invoke the system API deployed to the primary environment
and the system API deployed to the DR environment, and ONLY use the first response.
*****************************************
>> The API requirement in the given scenario is to respond in least possible time.
>> The option that is suggesting to first try the API in primary environment and then
fallback to API in DR environment would result in successful response but NOT in least
possible time. So, this is NOT a right choice of implementation for given requirement.
>> Another option that is suggesting to ONLY invoke API in primary environment and to
add timeout and retries may also result in successful response upon retries but NOT in
least possible time. So, this is also NOT a right choice of implementation for given
requirement.
>> One more option that is suggesting to invoke API in primary environment and API in DR
environment in parallel using Scatter-Gather would result in wrong API response as it
would return merged results and moreover, Scatter-Gather does things in parallel which is
true but still completes its scope only on finishing all routes inside it. So again, NOT a right
choice of implementation for given requirement
The Correct choice is to invoke the API in primary environment and the API in DR
environment parallelly, and using ONLY the first response received from one of them





Version 3.0.1 of a REST API implementation represents time values in PST time using ISO
8601 hh:mm:ss format. The API implementation needs to be changed to instead represent
time values in CEST time using ISO 8601 hh:mm:ss format. When following the semver.org
semantic versioning specification, what version should be assigned to the updated API
implementation?

 

3.0.2

 

4.0.0

 

3.1.0

 

3.0.1


4.0.0


Explanation: Explanation
Correct Answer: 4.0.0
*****************************************
As per semver.org semantic versioning specification:
Given a version number MAJOR.MINOR.PATCH, increment the:
- MAJOR version when you make incompatible API changes.
- MINOR version when you add functionality in a backwards compatible manner.
- PATCH version when you make backwards compatible bug fixes.
As per the scenario given in the question, the API implementation is completely changing
its behavior. Although the format of the time is still being maintained as hh:mm:ss and there
is no change in schema w.r.t format, the API will start functioning different after this change
as the times are going to come completely different.
Example: Before the change, say, time is going as 09:00:00 representing the PST. Now on,
after the change, the same time will go as 18:00:00 as Central European Summer Time is
9 hours ahead of Pacific Time.
>> This may lead to some uncertain behavior on API clients depending on how they are
handling the times in the API response. All the API clients need to be informed that the API
functionality is going to change and will return in CEST format. So, this considered as a
MAJOR change and the version of API for this new change would be 4.0.0





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

 

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

 

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

 

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

 

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


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



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