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Answer: Utilize Amazon CloudWatch metric streams with Amazon Kinesis Data Firehose to stream and store EC2 Auto Scaling status data in Amazon S3.
Option A is the correct answer because using Amazon CloudWatch metric streams with Amazon Kinesis Data Firehose to stream and store EC2 Auto Scaling status data in Amazon S3 is a fully serverless solution that efficiently handles the data transfer. This approach ensures that there is no impact on the speed of EC2 instance launches, as the data is streamed in real-time without the need for intermediate processing or additional infrastructure. Options B, C, and D involve additional processes or components that could potentially introduce delays or complexity, which can affect the quick launch of EC2 instances.
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How can a company implement a serverless solution to store EC2 Auto Scaling status data in Amazon S3 for near-real-time dashboard updates without impacting EC2 instance launch speeds?
A
Utilize Amazon CloudWatch metric streams with Amazon Kinesis Data Firehose to stream and store EC2 Auto Scaling status data in Amazon S3.
B
Deploy an Amazon EMR cluster to aggregate EC2 Auto Scaling status data, then use Amazon Kinesis Data Firehose to store it in Amazon S3.
C
Establish an Amazon EventBridge rule to trigger an AWS Lambda function, which sends EC2 Auto Scaling status data to Amazon S3 on a scheduled basis.
D
Employ a bootstrap script for EC2 instance launches to deploy Amazon Kinesis Agent, which collects and forwards EC2 Auto Scaling status data to Amazon Kinesis Data Firehose and Amazon S3.
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