Refer to the exhibit.
A Mule application is being designed to be deployed to several CIoudHub workers. The Mule application's integration logic is to replicate changed Accounts from Satesforce to a backend system every 5 minutes.
A watermark will be used to only retrieve those Satesforce Accounts that have been modified since the last time the integration logic ran.
What is the most appropriate way to implement persistence for the watermark in order to support the required data replication integration logic?

• A.Persistent VM Queue
• B.Persistent Object Store
• C.Persistent Anypoint MQ Queue
• D.Persistent Cache Scope

Comment: *

Name: *

Email: *

Verification: *

An Integration Mule application is being designed to synchronize customer data between two systems. One system is an IBM Mainframe and the other system is a Salesforce Marketing Cloud (CRM) instance. Both systems have been deployed in their typical configurations, and are to be invoked using the native protocols provided by Salesforce and IBM.
What interface technologies are the most straightforward and appropriate to use in this Mute application to interact with these systems, assuming that Anypoint Connectors exist that implement these interface technologies?

• A.IBM: REST CRM:REST
• B.IBM: DB access CRM:gRPC
• C.IBM: ActiveMQ CRM: REST
• D.IBM:QCS CRM: SOAP

Comment: *

Name: *

Email: *

Verification: *

A Mule application uses the Database connector.
What condition can the Mule application automatically adjust to or recover from without needing to restart or redeploy the Mule application?

• A.One of the stored procedures being called by the Mule application has been renamed
• B.The database server was unavailable for four hours due to a major outage but is now fully operational again
• C.The credentials for accessing the database have been updated and the previous credentials are no longer valid
• D.The database server has been updated and hence the database driver library/JAR needs a minor version upgrade

Comment: *

Name: *

Email: *

Verification: *

Refer to the exhibit.

One of the backend systems invoked by an API implementation enforces rate limits on the number of requests a particular client can make. Both the backend system and the API implementation are deployed to several non-production environments in addition to production.
Rate limiting of the backend system applies to all non-production environments. The production environment, however, does NOT have any rate limiting.
What is the most effective approach to conduct performance tests of the API implementation in a staging (non-production) environment?

• A.Conduct scaled-down performance tests in the staging environment against the rate limited backend system then upscale performance results to full production scale
• B.Use MUnit to simulate standard responses from the backend system then conduct performance tests to identify other bottlenecks in the system
• C.Include logic within the API implementation that bypasses invocations of the backend system in a performance test situation. Instead invoking local stubs that replicate typical backend system responses then conduct performance tests using this API Implementation
• D.Create a mocking service that replicates the backend system's production performance characteristics. Then configure the API implementation to use the mocking service and conduct the performance tests

Comment: *

Name: *

Email: *

Verification: *

Mule application A receives a request Anypoint MQ message REQU with a payload containing a variable-length list of request objects. Application A uses the For Each scope to split the list into individual objects and sends each object as a message to an Anypoint MQ queue.
Service S listens on that queue, processes each message independently of all other messages, and sends a response message to a response queue.
Application A listens on that response queue and must in turn create and publish a response Anypoint MQ message RESP with a payload containing the list of responses sent by service S in the same order as the request objects originally sent in REQU.
Assume successful response messages are returned by service S for all request messages.
What is required so that application A can ensure that the length and order of the list of objects in RESP and REQU match, while at the same time maximizing message throughput?

• A.Use a Scatter-Gather within the For Each scope to ensure response message order Configure the Scatter-Gather with a persistent object store
• B.Perform all communication involving service S synchronously from within the For Each scope, so objects in RESP are in the exact same order as request objects in REQU
• C.Use an Async scope within the For Each scope and collect response messages in a second For Each scope in the order In which they arrive, then send RESP using this list of responses
• D.Keep track of the list length and all object indices in REQU, both in the For Each scope and in all communication involving service Use persistent storage when creating RESP

Comment: *

Name: *

Email: *

Verification: *