Salesforce Certified MuleSoft Platform Architect Exam Preparation Material | Salesforce Certified MuleSoft Platform Architect

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Question#1

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

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.

Question#2

A manufacturing company has deployed an API implementation to CloudHub and has not configured it to be automatically restarted by CloudHub when the worker is not responding.
Which statement is true when no API Client invokes that API implementation?

A. No alert on the API invocations and APT implementation can be raised
B. Alerts on the APT invocation and API implementation can be raised
C. No alert on the API invocations is raised but alerts on the API implementation can be raised
D. Alerts on the API invocations are raised but no alerts on the API implementation can be raised

Explanation:
When an API implementation is deployed on CloudHub without configuring automatic restarts in case of worker non-responsiveness, MuleSoft’s monitoring and alerting behavior is as follows: API Invocation Alerts:
If no clients are invoking the API, there will be no invocation alerts triggered, as alerts related to invocations depend on actual client requests.
Implementation-Level Alerts:
Even without invocation, CloudHub can still monitor the state of the API implementation. If the worker becomes unresponsive, an alert related to the API implementation's health or availability could still be raised.
Why Option C is Correct:
This option correctly identifies that no invocation-related alerts would be triggered in the absence of client requests, while implementation-level alerts could still be generated based on the worker's state.
Reference
For additional information, check MuleSoft documentation on CloudHub monitoring and alert configurations to understand worker status alerts versus invocation alerts.

Question#3

An organization has several APIs that accept JSON data over HTTP POST. The APIs are all publicly available and are associated with several mobile applications and web applications.
The organization does NOT want to use any authentication or compliance policies for these APIs, but at the same time, is worried that some bad actor could send payloads that could somehow compromise the applications or servers running the API implementations.
What out-of-the-box Anypoint Platform policy can address exposure to this threat?

A. Shut out bad actors by using HTTPS mutual authentication for all API invocations
B. Apply an IP blacklist policy to all APIs; the blacklist will Include all bad actors
C. Apply a Header injection and removal policy that detects the malicious data before it is used
D. Apply a JSON threat protection policy to all APIs to detect potential threat vectors

Explanation:
Correct Answer Apply a JSON threat protection policy to all APIs to detect potential threat vectors >> Usually, if the APIs are designed and developed for specific consumers (known consumers/customers) then we would IP Whitelist the same to ensure that traffic only comes from them.
>> However, as this scenario states that the APIs are publicly available and being used by so many mobile and web applications, it is NOT possible to identify and blacklist all possible bad actors.
>> So, JSON threat protection policy is the best chance to prevent any bad JSON payloads from such bad actors.

Question#4

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 rate-limit-enforcement security Scheme with description, type, and example
D. By refining the response definitions by adding the x-ratelimit-* response headers with description, type, and example

Explanation:
Correct Answer By refining the response definitions by adding the x-ratelimit-* response headers with description, type, and example
Reference:
https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling#response-headers
https://docs.mulesoft.com/api-manager/2.x/rate-limiting-and-throttling-sla-based-policies#response-headers

Question#5

Refer to the exhibit.



An organization uses one specific CloudHub (AWS) region for all CloudHub deployments.
How are CloudHub workers assigned to availability zones (AZs) when the organization's Mule applications are deployed to CloudHub in that region?

A. Workers belonging to a given environment are assigned to the same AZ within that region
B. AZs are selected as part of the Mule application's deployment configuration
C. Workers are randomly distributed across available AZs within that region
D. An AZ is randomly selected for a Mule application, and all the Mule application's CloudHub workers are assigned to that one AZ

Explanation:
Correct Answer Workers are randomly distributed across available AZs within that region.
>> Currently, we only have control to choose which AWS Region to choose but there is no control at all using any configurations or deployment options to decide what Availability Zone (AZ) to assign to what worker.
>> There are NO fixed or implicit rules on platform too w.r.t assignment of AZ to workers based on environment or application.
>> They are completely assigned in random. However, cloudhub definitely ensures that HA is achieved by assigning the workers to more than on AZ so that all workers are not assigned to same AZ for same application.
Reference: https://help.mulesoft.com/s/question/0D52T000051rqDj/one-cloudhub-aws-region-how-cloudhub-workers-are-assigned-to-availability-zones-azs-



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Exam Code: Salesforce Certified MuleSoft Platform Architect
Q & A: 152 Q&As
Updated:  Nov 02,2026

 

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