Your company is in the process of developing a next generation pet collar that collects biometric information
to assist families with promoting healthy lifestyles for their pets Each collar will push 30kb of biometric data In
JSON format every 2 seconds to a collection platform that will process and analyze the data providing health
trending information back to the pet owners and veterinarians via a web portal Management has tasked you
to architect the collection platform ensuring the following requirements are met.
Provide the ability for real-time analytics of the inbound biometric data
Ensure processing of the biometric data is highly durable. Elastic and parallel
The results of the analytic processing should be persisted for data mining
Which architecture outlined below win meet the initial requirements for the collection platform?
A.
Utilize S3 to collect the inbound sensor data analyze the data from S3 with a daily scheduled Data Pipeline
and save the results to a Redshift Cluster.
B.
Utilize Amazon Kinesis to collect the inbound sensor data, analyze the data with Kinesis clients and save the
results to a Redshift cluster using EMR.
C.
Utilize SQS to collect the inbound sensor data analyze the data from SQS with Amazon Kinesis and save the
results to a Microsoft SQL Server RDS instance.
D.
Utilize EMR to collect the inbound sensor data, analyze the data from EUR with Amazon Kinesis and save me
results to DynamoDB.
B
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answer b
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I agree, B.
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Input incoming data into a Kinesis Stream.
If analytics/calculations are relatively basic, such as SQL queries, and data is structured (which JSON would be), then:
Use that Kinesis Stream as the input stream for Kinesis Analytics.
Perform SQL queries on data to analyze (can do so in real-time, milliseconds)
Output via Kinesis Firehose to Redshift for future data mining.
If analytics/calculations are more complex, and data is unstructured (binary data, media, images, text, all mixed together, which would not be the case in this example), then:
Use that Kinesis Stream to feed an Elastic Map Reduce cluster.
Perform analysis on data.
Feed data to Redshift for future data mining.
So really that closer scenario with Kinesis Analytics isn’t represented in the choices above. But B is pretty close, even though it’s probably overkill for structured JSON data.
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thanks thorough answer
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Answer is B
https://aws.amazon.com/about-aws/whats-new/2014/02/20/analyze-streaming-data-from-amazon-kinesis-with-amazon-elastic-mapreduce/
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