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Answer: Use Bigtable with Looker.
To address the requirements of designing inspection routines, device repair, and replacement schedules based on real-time data from thousands of IoT devices, a managed solution that is highly scalable, supports a multi-cloud strategy, and offers low latency is needed. Among the options provided, Bigtable with Looker (Option D) stands out as the most suitable choice. Google Cloud Bigtable is a highly scalable, fully managed NoSQL database service that is designed for low latency and high throughput, making it ideal for IoT applications that require real-time data processing. Looker, on the other hand, is a powerful data analytics platform that can provide the necessary insights from the data stored in Bigtable. While Firestore (Option A) and Cloud Spanner (Option B) are also managed services, they may not offer the same level of performance and scalability for IoT use cases as Bigtable. MongoDB Atlas with Charts (Option C) is a viable option but may not integrate as seamlessly with Google Cloud services or support a multi-cloud strategy as effectively as Bigtable.
Author: LeetQuiz Editorial Team
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How can you design a highly scalable, low-latency, managed solution supporting a multi-cloud strategy to analyze IoT device maintenance data for optimizing inspection routines, repairs, and replacement schedules in the oil and gas industry?
A
Use Firestore with Looker.
B
Use Cloud Spanner with Data Studio.
C
Use MongoD8 Atlas with Charts.
D
Use Bigtable with Looker.
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