Question 1

The ABC company has an Anypoint Runtime Fabric on VMs/Bare Metal (RTF-VM) appliance installed on its own customer-hosted AWS infrastructure. Mule applications are deployed to this RTF-VM appliance. As part of the company standards, the Mule application logs must be forwarded to an external log management tool (LMT). Given the company's current setup and requirements, what is the most idiomatic (used for its intended purpose) way to send Mule application logs to the external LMT?

Options :

A : In RTF-VM, install and configure the external LTM-s log-forwarding agent

B : In RTF-VM, edit the pod configuration to automatically install and configure an Anypoint Monitoring agent

C : In each Mule application, configure custom Log4j settings

D : In RTF-VM. configure the out-of-the-box external log forwarder

Answer: A

Question 2

During a planning session with the executive leadership, the development team director presents plans for a new API to expose the data in the company’s order database. An earlier effort to build an API on top of this data failed, so the director is recommending a design-first approach. Which characteristics of a design-first approach will help make this API successful?

Options :

A : Building MUnit tests so administrators can confirm code coverage percentage during deployment

B : Publishing the fully implemented API to Exchange so all developers can reuse the API

C : Adding global policies to the API so all developers automatically secure the implementation before coding anything

D : Developing a specification so consumers can test before the implementation is built

Answer: D

Question 3

What Anypoint Connectors support transactions?

Options :

A : Database, JMS, VM

B : Database, 3MS, HTTP

C : Database, JMS, VM, SFTP

D : Database, VM, File

Answer: A

Question 4

An external web UI application currently accepts occasional HTTP requests from client web browsers to change (insert, update, or delete) inventory pricing information in an inventory system's database. Each inventory pricing change must be transformed and then synchronized with multiple customer experience systems in near real-time (in under 10 seconds). New customer experience systems are expected to be added in the future. The database is used heavily and limits the number of SELECT queries that can be made to the database to 10 requests per hour per user. What is the most scalable, idiomatic (used for its intended purpose), decoupled. reusable, and maintainable integration mechanism available to synchronize each inventory pricing change with the various customer experience systems in near real-time?

Options :

A : Write a Mule application with a Database On Table Row event source configured for the inventory pricing database, with the watermark attribute set to an appropriate database column In the same now, use a Scatter-Gather to call each customer experience system-s REST API with transformed inventory-pricing records

B : Add a trigger to the inventory-pricing database table so that for each change to the inventory pricing database, a stored procedure is called that makes a REST call to a Mule application Write the Mule application to publish each Mule event as a message to an Anypoint MQ exchange Write other Mule applications to subscribe to the Anypoint MQ exchange, transform each received message, and then update the Mule application-s corresponding customer experience system(s)

C : Replace the external web UI application with a Mule application to accept HTTP requests from client web browsers In the same Mule application, use a Batch Job scope to test if the database request will succeed, aggregate pricing changes within a short time window, and then update both the inventory pricing database and each customer experience system using a Parallel For Each scope

D : Write a Mule application with a Database On Table Row event source configured for the inventory pricing database, with the ID attribute set to an appropriate database column In the same flow, use a Batch Job scope to publish transformed Inventory-pricing records to an Anypoint MQ queue Write other Mule applications to subscribe to the Anypoint MQ queue, transform each received message, and then update the Mule application-s corresponding customer experience system(s)

Answer: B

Question 5

An external REST client periodically sends an array of records in a single POST request to a Mule application API endpoint. The Mule application must validate each record of the request against a JSON schema before sending it to a downstream system in the same order that it was received in the array Record processing will take place inside a router or scope that calls a child flow. The child flow has its own error handling defined. Any validation or communication failures should not prevent further processing of the remaining records. To best address these requirements what is the most idiomatic(used for it intended purpose) router or scope to used in the parent flow, and what type of error handler should be used in the child flow?

Options :

A : First Successful router in the parent flow On Error Continue error handler in the child flow

B : For Each scope in the parent flow On Error Continue error handler in the child flow

C : Parallel For Each scope in the parent flow On Error Propagate error handler in the child flow

D : Until Successful router in the parent flow On Error Propagate error handler in the child flow

Answer: B

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