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NEW QUESTION # 20
A project uses Jenkins to implement CI/CD process. It was observed that each Mule package contains some of the Jenkins files and folders for configurations of CI/CD jobs.
As these files and folders are not part of the actual package, expectation is that these should not be part of deployed archive.
Which file can be used to exclude these files and folders from the deployed archive?
Answer: C
NEW QUESTION # 21
To implement predictive maintenance on its machinery equipment, ACME Tractors has installed thousands of IoT sensors that will send data for each machinery asset as sequences of JMS messages, in near real-time, to a JMS queue named SENSOR_DATA on a JMS server. The Mule application contains a JMS Listener operation configured to receive incoming messages from the JMS servers SENSOR_DATA JMS queue. The Mule application persists each received JMS message, then sends a transformed version of the corresponding Mule event to the machinery equipment back-end systems.
The Mule application will be deployed to a multi-node, customer-hosted Mule runtime cluster. Under normal conditions, each JMS message should be processed exactly once.
How should the JMS Listener be configured to maximize performance and concurrent message processing of the JMS queue?
Set primaryNodeOnly = trueB. Set numberOfConsumers to a value greater than one
Set primaryNodeOnly = falseC. Set numberOfConsumers = 1
Set primaryNodeOnly = trueD. Set numberOfConsumers = 1
Set primaryNodeOnly = false
Answer: B
NEW QUESTION # 22
An insurance provider is implementing Anypoint platform to manage its application infrastructure and is using the customer hosted runtime for its business due to certain financial requirements it must meet. It has built a number of synchronous API's and is currently hosting these on a mule runtime on one server These applications make use of a number of components including heavy use of object stores and VM queues.
Business has grown rapidly in the last year and the insurance provider is starting to receive reports of reliability issues from its applications.
The DevOps team indicates that the API's are currently handling too many requests and this is over loading the server. The team has also mentioned that there is a significant downtime when the server is down for maintenance.
As an integration architect, which option would you suggest to mitigate these issues?
Answer: B
NEW QUESTION # 23
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?
Answer: D
NEW QUESTION # 24
A Mule application is being designed To receive nightly a CSV file containing millions of records from an external vendor over SFTP, The records from the file need to be validated, transformed. And then written to a database. Records can be inserted into the database in any order.
In this use case, what combination of Mule components provides the most effective and performant way to write these records to the database?
Answer: D
Explanation:
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
NEW QUESTION # 25
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