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Answer: Use Amazon Kinesis Data Firehose and an AWS Lambda function to transform the data and deliver the transformed data to OpenSearch Service.
Option A is CORRECT because using Amazon Kinesis Data Firehose with an AWS Lambda function provides a serverless and managed solution to transform and ingest data into Amazon OpenSearch Service. Kinesis Data Firehose automatically scales to handle large volumes of data and can deliver data directly to OpenSearch Service with minimal operational overhead. The Lambda function can be used to transform the data as it flows through Firehose, making this solution ideal for real-time data transformation and ingestion without needing to manage servers or complex infrastructure.
Author: Ritesh Yadav
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Question 11/58
A media company wants to use Amazon OpenSearch Service to analyze rea-time data about popular musical artists and songs. The company expects to ingest millions of new data events every day. The new data events will arrive through an Amazon Kinesis data stream. The company must transform the data and then ingest the data into the OpenSearch Service domain.
Which method should the company use to ingest the data with the LEAST operational overhead?
A
Use Amazon Kinesis Data Firehose and an AWS Lambda function to transform the data and deliver the transformed data to OpenSearch Service.
B
Use a Logstash pipeline that has prebuilt filters to transform the data and deliver the transformed data to OpenSearch Service.
C
Use an AWS Lambda function to call the Amazon Kinesis Agent to transform the data and deliver the transformed data OpenSearch Service.
D
Use the Kinesis Client Library (KCL) to transform the data and deliver the transformed data to OpenSearch Service.
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