Exam AWS Certified Data Engineer - Associate DEA-C01 All Questions

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Exam AWS Certified Data Engineer - Associate DEA-C01 topic 1 question 120 discussion

Exam question from Amazon's AWS Certified Data Engineer - Associate DEA-C01

Question #: 120
Topic #: 1

[All AWS Certified Data Engineer - Associate DEA-C01 Questions]

A telecommunications company collects network usage data throughout each day at a rate of several thousand data points each second. The company runs an application to process the usage data in real time. The company aggregates and stores the data in an Amazon Aurora DB instance.

Sudden drops in network usage usually indicate a network outage. The company must be able to identify sudden drops in network usage so the company can take immediate remedial actions.

Which solution will meet this requirement with the LEAST latency?

A. Create an AWS Lambda function to query Aurora for drops in network usage. Use Amazon EventBridge to automatically invoke the Lambda function every minute.
B. Modify the processing application to publish the data to an Amazon Kinesis data stream. Create an Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) application to detect drops in network usage.
C. Replace the Aurora database with an Amazon DynamoDB table. Create an AWS Lambda function to query the DynamoDB table for drops in network usage every minute. Use DynamoDB Accelerator (DAX) between the processing application and DynamoDB table.
D. Create an AWS Lambda function within the Database Activity Streams feature of Aurora to detect drops in network usage.

Show Suggested Answer

Suggested Answer: B 🗳️

by Bmaster at June 30, 2024, 11:54 p.m.

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Comments

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youonebe

3 months ago

Selected Answer: B

If you choose D, lambda function still needs to get invoked which introduces latency. Kinesis Data Analytics is real-time

upvoted 1 times

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Adrifersilva

10 months ago

Selected Answer: B

Regarding D, Database Activity Streams in Aurora are primarily for auditing databases actities, not for analyzing app data.

upvoted 3 times

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antun3ra

1 year ago

Selected Answer: B

B is the correct answer

upvoted 2 times

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portland

1 year ago

Selected Answer: B

reduces latency because it is analyze before the data even gets to the Aurora DB

upvoted 2 times

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sdas1

1 year, 1 month ago

Option D is the optimal choice because it leverages Aurora's Database Activity Streams to enable real-time monitoring and immediate response to changes in network usage data. This approach ensures the least latency in detecting and responding to sudden drops in network usage, crucial for the telecommunications company to take immediate remedial actions during network outages.

upvoted 2 times

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sdas1

1 year, 1 month ago

Option D https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/DBActivityStreams.Overview.html In Amazon Aurora, you start a database activity stream at the cluster level. All DB instances within your cluster have database activity streams enabled. Your Aurora DB cluster pushes activities to an Amazon Kinesis data stream in near real time. The Kinesis stream is created automatically. From Kinesis, you can configure AWS services such as Amazon Data Firehose and AWS Lambda to consume the stream and store the data.

upvoted 2 times

LR2023

10 months, 3 weeks ago

The Database Activity Streams feature of Amazon Aurora can help monitor database activity, but it doesn't directly detect drops in network usage:

upvoted 1 times

altonh

8 months, 1 week ago

"Activity monitored includes the full SQL statement, the row count of affected rows from DML commands" You can still keep track of the row inserts to see if there is a drop in network usage.

upvoted 1 times

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Ja13

1 year, 1 month ago

Selected Answer: B

The best solution to identify sudden drops in network usage with the least latency is: B. Modify the processing application to publish the data to an Amazon Kinesis data stream. Create an Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) application to detect drops in network usage. This approach ensures real-time processing with minimal latency and allows immediate detection and response to network usage drops.

upvoted 3 times

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