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NEW QUESTION 44
An organization uses one specific CloudHub (AWS) region for all CloudHub deployments. How are CloudHub workers assigned to availability zones (AZs) when the organization's Mule applications are deployed to CloudHub in that region?
- A. Workers are randomly distributed across available AZs within that region.
- B. Workers belonging to a given environment are assigned to the same AZ within that region.
- C. AZs are selected as part of the Mule application's deployment configuration.
- D. An AZ is randomly selected for a Mule application, and all the Mule application's CloudHub workers are assigned to that one AZ
Answer: A
Explanation:
Explanation
Correct answer is Workers are randomly distributed across available AZs within that region. This ensure high availability for deployed mule applications Mulesoft documentation reference :
https://docs.mulesoft.com/runtime-manager/cloudhub-hadr
NEW QUESTION 45
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?
- A. Use a Parallel for Each scope to Insert records one by one into the database
- B. Use a Scatter-Gather to bulk insert records into the database
- C. Use a Batch job scope to bulk insert records into the database.
- D. Use a DataWeave map operation and an Async scope to insert records one by one into the database.
Answer: C
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 46
A stock broking company makes use of CloudHub VPC to deploy Mule applications. Mule application needs to connect to a database application in the customers on-premises corporate data center and also to a Kafka cluster running in AWS VPC.
How is access enabled for the API to connect to the database application and Kafka cluster securely?
- A. Set up a transit gateway to the customers on-premises corporate datacenter to AWS VPC
- B. Setup VPC peering with AWS VPC and the customers devices corporate data center
- C. Setup AnyPoint VPN to the customer's on-premise corporate data
center and VPC peering with AWS VPC - D. Setup VPC peering with the customers onto my service corporate data center and Anypoint VPN to AWS VPC
Answer: C
NEW QUESTION 47
An organization has chosen Mulesoft for their integration and API platform.
According to the Mulesoft catalyst framework, what would an integration architect do to create achievement goals as part of their business outcomes?
- A. build and publish foundational assets
- B. agree upon KPI's and help develop and overall success plan
- C. evangelize API's
- D. Measure the impact of the centre for enablement
Answer: B
NEW QUESTION 48
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