Google Professional Cloud Database Engineer exam dumps

Google Professional Cloud Database Engineer practice question 133 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 133

Select 2Google Cloud Platform

Your team is experiencing degraded performance in a Cloud SQL PostgreSQL database. You suspect resource contention is causing the issue. Which two actions should you take to investigate the resource contention and identify the root cause?

  1. A

    Use the Query Insights feature in Cloud SQL to analyze query execution time and resource usage.

  2. B

    Increase the instance size to temporarily address the performance issue without further investigation.

  3. C

    Examine the CPU and memory utilization metrics in Cloud Monitoring to identify resource bottlenecks.

  4. D

    Review the database's connection limits and active sessions to check for excessive concurrent connections.

  5. E

    Enable binary logging for the database to capture all transactions for further analysis.

Show answer and explanation

Correct answers: A, C

Explanation

Resource contention in a Cloud SQL database often arises from inefficient queries or inadequate resource allocation. Query Insights provides detailed query-level metrics, helping to identify inefficient queries. Monitoring CPU and memory utilization via Cloud Monitoring helps pinpoint resource bottlenecks. These two steps are key to diagnosing and resolving resource contention issues effectively.

  • A. Correct.

    Query Insights is a powerful tool in Cloud SQL that helps analyze query patterns, execution times, and resource usage, making it an ideal starting point for investigating resource contention.

  • B. Incorrect.

    While increasing the instance size might temporarily alleviate performance issues, it does not help identify the root cause of resource contention and is not a recommended first step.

  • C. Correct.

    CPU and memory utilization metrics in Cloud Monitoring can reveal resource bottlenecks, such as high CPU usage or memory exhaustion, which are common causes of resource contention.

  • D. Incorrect.

    Checking connection limits and active sessions can help identify issues with excessive connections, but it is not directly related to diagnosing overall resource contention in this scenario.

  • E. Incorrect.

    Enabling binary logging is primarily used for replication and point-in-time recovery and does not directly assist in investigating resource contention.

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