Terramearths 20 million vehicles are scattered around

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TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US. Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles. You want to run this job on all the dat a. What is the most cost-effective way to run this job? A. Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job. B. Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job. C. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a multi region bucket and use a Dataproc cluster to finish the job. D. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a regional bucket and use a Cloud Dataproc cluster ….. Answer: C Explanation: Storageguarantees 2 replicates which are geo diverse (100 miles apart) which can get better remote latency and availability. More importantly, is that multiregional heavily leverages Edge caching and CDNs to provide the content to the end users. All this redundancy and caching means that Multiregional comes with overhead to sync and ensure consistency between geo-diverse areas. As such, it’s much better for write-once-read-many
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Questions & Answers PDF P-197 scenarios. This means frequently accessed (e.g. “hot” objects) around the world, such as website content, streaming videos, gaming or mobile applications. References: - performance-5c847ac8f9f2 Question: 132 For this question, refer to the TerramEarth case study. TerramEarth has equipped unconnected trucks with servers and sensors to collet telemetry dat a. Next year they want to use the data to train machine learning models. They want to store this data in the cloud while reducing costs. What should they do? A. Have the vehicle’ 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 dataflow job that compresses the data, and store it in Google BigQuery. C. Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Cloud Bigtable. D. Have the vehicle's computer compress the data in hourly snapshots, a Store it in a GCS Coldline bucket. Answer: D Explanation: Storage is the best choice for data that you plan to access at most once a year, due to its slightly lower availability, 90-day minimum storage duration, costs for data access, and higher per-operation costs. For example: Cold Data Storage - Infrequently accessed data, such as data stored for legal or regulatory reasons, can be stored at low cost as Coldline Storage, and be available when you need it.
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