Google Professional Cloud Developer exam dumps

Google Professional Cloud Developer practice question 186 of 481

Professional Cloud Developer. Professional level, Google Cloud. Free question with the correct answer and a full explanation.

Google Professional Cloud Developer Question 186

Select 2Google Cloud Platform

You are designing a serverless data processing pipeline on Google Cloud to handle real-time streaming data from IoT devices. The data volume is expected to grow significantly over time, reaching terabytes per day. Which combination of Google Cloud services is the most appropriate for efficiently handling this volume while ensuring scalability and low latency?

  1. A

    Cloud Pub/Sub for ingestion and Dataflow for processing

  2. B

    Cloud Storage for ingestion and BigQuery for real-time processing

  3. C

    Cloud Pub/Sub for ingestion and Cloud Functions for processing

  4. D

    Cloud Pub/Sub for ingestion and BigQuery for batch analysis

  5. E

    Cloud SQL for ingestion and Dataflow for processing

Show answer and explanation

Correct answers: A, D

Explanation

In a scenario with high-volume streaming data, Cloud Pub/Sub is the best choice for ingestion due to its scalability and ability to handle real-time data. For processing, Dataflow is recommended for real-time processing, and BigQuery is suited for batch analysis of the processed data. Combining these services ensures scalability, low latency, and cost-effectiveness when working with large data volumes.

  • A. Correct.

    Correct: Cloud Pub/Sub is ideal for real-time ingestion of high-volume streaming data, and Dataflow provides scalable real-time processing capabilities.

  • B. Incorrect.

    Incorrect: Cloud Storage is suited for batch file-based ingestion, not for real-time streaming data, and BigQuery is optimized for analytical queries, not streaming data processing.

  • C. Incorrect.

    Incorrect: While Cloud Pub/Sub is suitable for ingestion, Cloud Functions is not designed for handling high-volume, continuous data streams as efficiently as Dataflow.

  • D. Correct.

    Correct: Cloud Pub/Sub can handle real-time ingestion, and BigQuery is suitable for batch analysis on large datasets generated from the streaming data.

  • E. Incorrect.

    Incorrect: Cloud SQL is not designed for high-volume ingestion of streaming data, and it does not scale as well as Cloud Pub/Sub and Dataflow for this use case.

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