AWS Certified Machine Learning – Specialty — Question 361

A cybersecurity company is collecting on-premises server logs, mobile app logs, and IoT sensor data. The company backs up the ingested data in an Amazon S3 bucket and sends the ingested data to Amazon OpenSearch Service for further analysis. Currently, the company has a custom ingestion pipeline that is running on Amazon EC2 instances. The company needs to implement a new serverless ingestion pipeline that can automatically scale to handle sudden changes in the data flow.

Which solution will meet these requirements MOST cost-effectively?

Answer options

• A. Create two Amazon Data Firehose delivery streams to send data to the S3 bucket and OpenSearch Service. Configure the data sources to send data to the delivery streams.
• B. Create one Amazon Kinesis data stream. Create two Amazon Data Firehose delivery streams to send data to the S3 bucket and OpenSearch Service. Connect the delivery streams to the data stream. Configure the data sources to send data to the data stream.
• C. Create one Amazon Data Firehose delivery stream to send data to OpenSearch Service. Configure the delivery stream to back up the raw data to the S3 bucket. Configure the data sources to send data to the delivery stream.
• D. Create one Amazon Kinesis data stream. Create one Amazon Data Firehose delivery stream to send data to OpenSearch Service. Configure the delivery stream to back up the data to the S3 bucket. Connect the delivery stream to the data stream. Configure the data sources to send data to the data stream.

Correct answer: C

Explanation

Amazon Data Firehose natively supports delivering data to Amazon OpenSearch Service while simultaneously backing up the raw source data to an Amazon S3 bucket, making a single delivery stream the most cost-effective and simple solution. Options B and D are less cost-effective because they introduce Amazon Kinesis Data Streams, which adds unnecessary provisioning and shard management costs. Option A is also inefficient and more expensive because running two separate Firehose streams doubles the ingestion processing costs.