Salesforce Mule-Arch-202 : Salesforce Certified MuleSoft Platform Integration Architect

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Salesforce Mule-Arch-202 Exam Syllabus Topics:

Salesforce Certified MuleSoft Platform Integration Architect Sample Questions:

1. Which approach is most effective for processing large streams of messages in a performance-sensitive environment?

A) Processing each message individually and immediately storing results.
B) Sending each message to multiple processors for redundancy.
C) Increasing the concurrency level of each flow to the maximum.
D) Aggregating messages into batches before processing.

2. An organization will deploy Mule applications to CloudHub. Business requirements mandate that all application logs be stored only in an external Splunk consolidated logging service and not in CloudHub.
In order to most easily store Mule application logs only in Splunk, how must Mule application logging be configured in Runtime Manager, and where should the log4j2 Splunk appender be defined?

A) Keep the default logging configuration in Runtime Manager.
B) Disable CloudHub logging in Runtime Manager.
C) Disable CloudHub logging in Runtime Manager.
D) Disable CloudHub logging in Runtime Manager.

3. What is an advantage of utilizing MUnit for designing unit test suites in Mule applications?

A) It requires minimal setup and configuration.
B) It eliminates the need for any manual testing.
C) It only supports static analysis of applications.
D) It provides tools for mocking and spying on components.

4. Refer to the exhibit.

In this Mule application, the retrieveFile flow's event source reads a CSV file from a remote SFTP server and then publishes each record in the CSV file to a VM queue. The processCustomerRecord flow's VM Listener receives messages from the same VM queue and then processes each message separately. This Mule application is deployed to multiple CloudHub workers with persistent queues enabled. How are messages routed to the CloudHub workers as messages are received by the VM Listener?

A) Each message is routed to one of the available CloudHub workers in a non-deterministic, non-round-robin fashion, thereby approximately balancing messages among the CloudHub workers
B) Each message is routed to the same CloudHub worker that retrieved the file, thereby binding all messages to only that one CloudHub worker
C) Each message is duplicated to all of the CloudHub workers, thereby sharing each message with all the CloudHub workers
D) Each message is routed to one of the CloudHub workers in a deterministic round-robin fashion, thereby exactly balancing messages among the CloudHub workers

5. Refer to the exhibit.

A shopping cart checkout process consists of a web store back end that sends a sequence of HTTPS POST requests to an Experience API, which in turn invokes a Process API using HTTPS. The web store back end executes in a Java EE application server. All API implementations are Mule applications executing in a customer-hosted Mule runtime. End-to-end correlation of all HTTP requests and responses belonging to each checkout instance is required. This is to be done through a common correlation ID so that all log entries written by the web store back end, Experience API implementation, and Process API implementation include the same correlation ID for all requests and responses belonging to the same checkout instance. What is the most efficient way (using the least amount of custom coding or configuration) for the web store back end and the implementations of the Experience API and Process API to participate in end-to-end correlation of the API invocations for each checkout instance?

A) The Experience API implementation generates a correlation ID for each incoming HTTP request and passes it to the web store back end in the HTTP response, which includes it in all subsequent API invocations to the Experience API.
B) The web store back end generates a new correlation ID value at the start of checkout and sets it on the X-Correlation-ID HTTP request header in each API invocation belonging to that checkout.
C) The web store back end, being a Java EE application, automatically uses the thread-local correlation ID generated by the Java EE application server and automatically transmits that to the Experience API using standard HTTP headers.
D) The web store back end sends a correlation ID value in the HTTP request body in the way required by the Experience API.

Solutions: