Google Professional Cloud Database Engineer exam dumps

Google Professional Cloud Database Engineer practice question 119 of 259

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

Google Professional Cloud Database Engineer Question 119

Select 2Google Cloud Platform

You are managing a Cloud SQL instance for a transactional database and notice frequent performance degradation during peak traffic hours. You want to identify the root cause using Google Cloud's monitoring tools. Which combination of metrics should you analyze to determine the issue?

  1. A

    CPU utilization percentage and RAM utilization percentage

  2. B

    Disk I/O operations and Cloud Logging query logs

  3. C

    Database connection count and storage capacity usage

  4. D

    Network egress bandwidth and database replication lag

Show answer and explanation

Correct answers: A, B

Explanation

To identify the root cause of performance degradation during peak traffic hours, it is essential to analyze metrics related to the instance's compute (CPU and RAM) and storage (Disk I/O) usage. Additionally, Cloud Logging can help uncover inefficient queries or database errors that contribute to the issue. Together, these metrics provide a comprehensive view of potential bottlenecks impacting performance.

  • A. Correct.

    CPU utilization and RAM utilization are critical metrics to monitor as they indicate whether the instance has sufficient compute and memory resources to handle the workload during peak traffic hours.

  • B. Correct.

    Disk I/O operations help determine if the storage layer is a bottleneck, while Cloud Logging query logs can reveal inefficient queries or errors affecting performance.

  • C. Incorrect.

    Database connection count and storage capacity usage are important metrics but are less likely to directly reflect performance degradation during peak traffic if the instance is not hitting connection limits or storage thresholds.

  • D. Incorrect.

    Network egress bandwidth and replication lag are useful for identifying network-related issues or delays in replication, but they are not primary indicators of performance degradation caused by CPU, RAM, or I/O bottlenecks.

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