MuleSoft MCIA-Level-1 Exam With Confidence Using Practice Dumps

To ensure that the Java Invoke static connector in a Mule 4 application can access a static method in a dependency jar file, you need to make the dependency visible to the connector's class loader. Here are the two effective methods to achieve this:

• Using Maven Command:

com.example example-library 1.0.0

• uk.co.certification.simulator.questionpool.PList@18be75a0

mvn clean package

• Configuring Dependency as a Shared Library:

xml

com.example example-library 1.0.0 provided

• Steps for Java Invoke Configuration:
• Benefits:

References:

• MuleSoft Documentation on Java Module
• Maven Documentation on Dependency Management

When multiple Mule applications need to listen on the same port (e.g., port 443), configuring them individually will cause a conflict because only one application can bind to a specific port on a server at a time. To resolve this, you can use a Mule domain project, which allows multiple Mule applications to share configurations, including HTTP listeners. Here’s how you can do it:

• Create a Mule Domain Project:
• Configure the Shared HTTP Listener:

• Reference the Shared HTTP Listener in Mule Applications:

• Deploy the Domain Project and Applications:

By using a domain project to centralize the HTTP listener configuration, you ensure that both APIs can listen on port 443 without conflicts, allowing customers to access both APIs through the same port.

References

• MuleSoft Documentation: Domain Projects
• MuleSoft Documentation: HTTP Listener Configuration

Explanation

Correct answer is Use a Batch job scope to bulk insert records into the database

* Batch Job is most efficient way to manage millions of records.

A few points to note here are as follows :

Reliability: If you want reliabilty while processing the records, i.e should the processing survive a runtime crash or other unhappy scenarios, and when restarted process all the remaining records, if yes then go for batch as it uses persistent queues.

Error Handling: In Parallel for each an error in a particular route will stop processing the remaining records in that route and in such case you'd need to handle it using on error continue, batch process does not stop during such error instead you can have a step for failures and have a dedicated handling in it.

Memory footprint: Since question said that there are millions of records to process, parallel for each will aggregate all the processed records at the end and can possibly cause Out Of Memory.

Batch job instead provides a BatchResult in the on complete phase where you can get the count of failures and success. For huge file processing if order is not a concern definitely go ahead with Batch Job