An XA transaction is being configured that involves a JMS connector listening for incoming JMS messages.
What is the meaning of the timeout attribute of the XA transaction, and what happens after the timeout expires?

• A.The time that is allowed to pass between receiving JMS messages on the same JMS connection After the timeout, a new JMS connection is established
• B.The time that is allowed to pass without the transaction being ended explicitly After the timeout, the transaction is forcefully rolled-back
• C.The time that is allowed to pass between committing the transaction and the completion of the Mule flow After the timeout, flow processing triggers an error
• D.The time that is allowed to pass for stale JMS consumer threads to be destroyed After the timeout, a new JMS consumer thread is created

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Refer to the exhibit.

A business process involves the receipt of a file from an external vendor over SFTP. The file needs to be parsed and its content processed, validated, and ultimately persisted to a database. The delivery mechanism is expected to change in the future as more vendors send similar files using other mechanisms such as file transfer or HTTP POST.
What is the most effective way to design for these requirements in order to minimize the impact of future change?

• A.Use a MuleSoft Scatter-Gather and a MuleSoft Batch Job to handle the different files coming from different sources
• B.Create a Process API to receive the file and process it using a MuleSoft Batch Job while delegating the data save process to a System API
• C.Create an API that receives the file and invokes a Process API with the data contained In the file, then have the Process API process the data using a MuleSoft Batch Job and other System APIs as needed
• D.Use a composite data source so files can be retrieved from various sources and delivered to a MuleSoft Batch Job for processing

Correct Answer: C

* Scatter-Gather is used for parallel processing, to improve performance. In this scenario, input files are coming from different vendors so mostly at different times. Goal here is to minimize the impact of future change. So scatter Gather is not the correct choice.
* If we use 1 API to receive all files from different Vendors, any new vendor addition will need changes to that 1 API to accommodate new requirements. So Option A and C are also ruled out.
* Correct answer is Create an API that receives the file and invokes a Process API with the data contained in the file, then have the Process API process the data using a MuleSoft Batch Job and other System APIs as needed. Answer to this question lies in the API led connectivity approach.
* API-led connectivity is a methodical way to connect data to applications through a series of reusable and purposeful modern APIs that are each developed to play a specific role - unlock data from systems, compose data into processes, or deliver an experience. System API : System API tier, which provides consistent, managed, and secure access to backend systems. Process APIs : Process APIs take core assets and combines them with some business logic to create a higher level of value. Experience APIs : These are designed specifically for consumption by a specific end-user app or device.
So in case of any future plans , organization can only add experience API on addition of new Vendors, which reuse the already existing process API. It will keep impact minimal.

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Refer to the exhibit.

An organization uses a 2-node Mute runtime cluster to host one stateless API implementation. The API is accessed over HTTPS through a load balancer that uses round-robin for load distribution.
Two additional nodes have been added to the cluster and the load balancer has been configured to recognize the new nodes with no other change to the load balancer.
What average performance change is guaranteed to happen, assuming all cluster nodes are fully operational?

• A.100% increase in the throughput of the API
• B.50% reduction In the JVM heap memory consumed by each node
• C.50% reduction in the response time of the API
• D.50% reduction In the number of requests being received by each node

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