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Answer: Have the vehicle's computer compress the data in hourly snapshots, and store it in a GCS Coldline bucket
The correct answer is D: 'Have the vehicle's computer compress the data in hourly snapshots, and store it in a GCS Coldline bucket.' This option is the most cost-effective because Coldline storage is designed for data that is accessed infrequently and has a lower cost compared to other storage options. Since TerramEarth plans to use the data next year, storing it in Coldline ensures that the storage costs are minimized until the data needs to be accessed. Nearline would be more expensive, and options involving real-time data flow and BigQuery or Bigtable are less suitable for long-term storage and cost-saving purposes.
Author: LeetQuiz Editorial Team
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TerramEarth manufactures heavy equipment for the mining and agricultural industries, with 20 million vehicles in operation globally. These vehicles collect 120 fields of telemetry data per second, which is stored locally and partially transmitted via a cellular network. The company wants to use this data next year to train machine learning models and aims to store it in the cloud while reducing costs. What should they do?
A
Have the vehicle's computer compress the data in hourly snapshots, and store it in a Google Cloud Storage (GCS) Nearline bucket
B
Push the telemetry data in real-time to a streaming data flow job that compresses the data, and store it in Google BigQuery
C
Push the telemetry data in real-time to a streaming data flow job that compresses the data, and store it in Cloud Bigtable
D
Have the vehicle's computer compress the data in hourly snapshots, and store it in a GCS Coldline bucket
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