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Answer: Transition the ingestion process to use Amazon Kinesis Data Firehose to store data in Amazon S3. Implement a script to nightly launch EC2 On-Demand Instances for batch processing of the S3 data, configured to terminate upon completion.
Option A is the most cost-effective solution. By using Amazon Kinesis Data Firehose to save the data to Amazon S3, you eliminate the need for constant EC2 instances running full-time for data ingestion. Instead, you can periodically launch EC2 On-Demand Instances to perform batch processing on the data stored in S3. This approach leverages the scalable and cost-effective nature of Amazon S3 for storage and allows for flexibility in compute resources, ensuring that instances are only running when necessary for batch processing. This significantly reduces costs compared to options that rely on long-term Reserved Instances or additional services like Redshift and EventBridge.
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A company is currently using a pool of Amazon EC2 Reserved Instances with 1-year reservations to ingest and store constant streaming market data on attached Amazon EBS volumes. They run a nightly batch process on EC2 On-Demand Instances that accesses this data via NFS shares to calculate aggregate statistics, which are not business-critical and can be processed in the next run if a failure occurs. With the Reserved Instance reservations expiring, the company seeks a cost-effective solution for both the continuous data ingestion and the nightly processing. Which of the following solutions would be the most economical?
A
Transition the ingestion process to use Amazon Kinesis Data Firehose to store data in Amazon S3. Implement a script to nightly launch EC2 On-Demand Instances for batch processing of the S3 data, configured to terminate upon completion.
B
Switch the ingestion process to utilize Amazon Kinesis Data Firehose for data storage in Amazon S3. Employ AWS Batch with Spot Instances for nightly processing, setting a maximum Spot price at 50% of the On-Demand rate.
C
Upgrade the ingestion process to operate with a fleet of EC2 Reserved Instances for 3 years behind a Network LoadBalancer. Utilize AWS Batch with Spot Instances for nightly processing, with a maximum Spot price set at 50% of the On-Demand rate.
D
Alter the ingestion process to leverage Amazon Kinesis Data Firehose for data storage in Amazon Redshift. Schedule an AWS Lambda function via Amazon EventBridge to nightly query Amazon Redshift for generating daily statistics.