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Question 64 - DVA-C02 discussion

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A company is using an AWS Lambda function to process records from an Amazon Kinesis data stream. The company recently observed slow processing of the records. A developer notices that the iterator age metric for the function is increasing and that the Lambda run duration is constantly above normal.

Which actions should the developer take to increase the processing speed? (Choose two.)

A.
Increase the number of shards of the Kinesis data stream.
Answers
A.
Increase the number of shards of the Kinesis data stream.
B.
Decrease the timeout of the Lambda function.
Answers
B.
Decrease the timeout of the Lambda function.
C.
Increase the memory that is allocated to the Lambda function.
Answers
C.
Increase the memory that is allocated to the Lambda function.
D.
Decrease the number of shards of the Kinesis data stream.
Answers
D.
Decrease the number of shards of the Kinesis data stream.
E.
Increase the timeout of the Lambda function.
Answers
E.
Increase the timeout of the Lambda function.
Suggested answer: A, C

Explanation:

Increasing the number of shards of the Kinesis data stream will increase the throughput and parallelism of the data processing. Increasing the memory that is allocated to the Lambda function will also increase the CPU and network performance of the function, which will reduce the run duration and improve the processing speed. Option B is not correct because decreasing the timeout of the Lambda function will not affect the processing speed, but may cause some records to fail if they exceed the timeout limit. Option D is not correct because decreasing the number of shards of the Kinesis data stream will decrease the throughput and parallelism of the data processing, which will slow down the processing speed. Option E is not correct because increasing the timeout of the Lambda function will not affect the processing speed, but may increase the cost of running the function.

Reference: [Amazon Kinesis Data Streams Scaling], [AWS Lambda Performance Tuning]

asked 16/09/2024
J. Cuylits
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