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  1. Home
  2. MuleSoft Certification
  3. MCIA-Level-1 Exam
  4. MuleSoft.MCIA-Level-1.v2022-07-26.q109 Dumps
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Question 106

An integration Mule application consumes and processes a list of rows from a CSV file. Each row must be read from the CSV file, validated, and the row data sent to a JMS queue, in the exact order as in the CSV file.
If any processing step for a row fails, then a log entry must be written for that row, but processing of other rows must not be affected.
What combination of Mule components is most idiomatic (used according to their intended purpose) when implementing the above requirements?

Correct Answer: B
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Question 107

What comparison is true about a CloudHub Dedicated Load Balancer (DLB) vs. the CloudHub Shared Load Balancer (SLB)?

Correct Answer: A
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Question 108

Refer to the exhibit. A business process involves two APIs that interact with each other asynchronously over HTTP. Each API is implemented as a Mule application. API 1 receives the initial HTTP request and invokes API 2 (in a fire and forget fashion) while API 2, upon completion of the processing, calls back into API 1 to notify about completion of the asynchronous process.
Each API is deployed to multiple redundant Mule runtimes and a separate load balancer, and is deployed to a separate network zone.
In the network architecture, how must the firewall rules be configured to enable the above interaction between API 1 and API 2?

Correct Answer: D
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Question 109

An organization is designing an integration solution to replicate financial transaction data from a legacy system into a data warehouse (DWH).
The DWH must contain a daily snapshot of financial transactions, to be delivered as a CSV file. Daily transaction volume exceeds tens of millions of records, with significant spikes in volume during popular shopping periods.
What is the most appropriate integration style for an integration solution that meets the organization's current requirements?

Correct Answer: D
Correct answer is Batch-triggered ETL Within a Mule application, batch processing provides a construct for asynchronously processing larger-than-memory data sets that are split into individual records. Batch jobs allow for the description of a reliable process that automatically splits up source data and stores it into persistent queues, which makes it possible to process large data sets while providing reliability. In the event that the application is redeployed or Mule crashes, the job execution is able to resume at the point it stopped.
insert code
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