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Answer: Configure the data acquisition devices to publish data to Cloud Pub/Sub.
Option A suggests deploying small Kafka clusters in data centers to buffer events. While Kafka can help buffer events and improve reliability, it requires additional infrastructure and maintenance costs, which may not be the most cost-effective solution. Option D suggests establishing a Cloud Interconnect between all remote data centers and Google. While this can improve connectivity, it may not necessarily address the issue of unpredictable latency and may require additional costs and maintenance. Option A suggests writing a Cloud Dataflow pipeline that aggregates all data in session windows. While this can help manage data processing, it may not necessarily address the issue of unreliable leased lines and may require additional infrastructure and maintenance costs. Therefore, based on the specific issue described in the scenario and the requirement to address it in the most cost-effective way, the most suitable solution is to configure the data acquisition devices to publish data to Cloud Pub/Sub.
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As the operator of a logistics company, you aim to enhance the reliability of event delivery from vehicle-based sensors. Currently, your setup includes small data centers globally for event capture, but the leased lines connecting your event collection to processing infrastructure are unreliable, causing unpredictable latency. What is the most cost-effective solution to this problem?
A
Develop a Cloud Dataflow pipeline that aggregates all data in session windows.
B
Implement small Kafka clusters in your data centers to buffer events.
C
Configure the data acquisition devices to publish data to Cloud Pub/Sub.
D
Establish a Cloud Interconnect between all remote data centers and Google.