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Answer: Use Amazon Kinesis for real-time data streaming, AWS Lambda for serverless computing, and Amazon Elasticsearch for data analysis. Configure Kinesis to capture user-generated content in real-time, Lambda to process the content, and Elasticsearch to store and analyze the processed data.
Option A is the most suitable choice for the given scenario. Amazon Kinesis can handle high throughput and low latency for real-time data streaming of user-generated content. AWS Lambda can be used for serverless computing to process the content as it arrives. Amazon Elasticsearch can be used for real-time data analysis. By configuring Kinesis to capture user-generated content in real-time, Lambda to process the content, and Elasticsearch to store and analyze the processed data, the pipeline can meet the requirements of the social media analytics company.
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You are tasked with designing an ETL pipeline for a social media analytics company that needs to process and analyze user-generated content in real-time. The pipeline should be able to handle high throughput and low latency. Which AWS services would you use to create this pipeline, and how would you configure them to meet the requirements?
A
Use Amazon Kinesis for real-time data streaming, AWS Lambda for serverless computing, and Amazon Elasticsearch for data analysis. Configure Kinesis to capture user-generated content in real-time, Lambda to process the content, and Elasticsearch to store and analyze the processed data.
B
Use Amazon S3 for data storage, AWS Glue for ETL processing, and Amazon Redshift for data warehousing. Configure Glue to process user-generated content as it arrives, and Redshift to store and analyze the processed data.
C
Use Amazon Kinesis Data Firehose for real-time data ingestion, AWS Glue for ETL processing, and Amazon Elasticsearch for data analysis. Configure Firehose to capture user-generated content in real-time, Glue to process the content, and Elasticsearch to store and analyze the processed data.
D
Use Amazon S3 for data storage, AWS Step Functions for workflow management, and AWS Lambda for serverless computing. Configure Step Functions to manage the workflow, Lambda to process user-generated content, and store the processed data in S3 for further analysis.