Google Professional Cloud DevOps Engineer exam dumps

Google Professional Cloud DevOps Engineer practice question 165 of 268

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

Google Professional Cloud DevOps Engineer Question 165

Select 4Google Cloud Platform

Your team has deployed a microservices-based application on Google Kubernetes Engine (GKE). Recently, users have reported that some requests to the application are taking longer than expected. You have been tasked to identify and resolve the performance bottleneck. How can you use Cloud Trace to accomplish this task?

  1. A

    Enable Cloud Trace in your project and review the latency distributions for each service to pinpoint slow requests.

  2. B

    Instrument your application code with Trace SDK to collect and report traces from custom spans within your services.

  3. C

    Use Cloud Trace's latency heatmaps to identify which specific endpoints or services are experiencing high latency.

  4. D

    Rely solely on Cloud Trace without integrating any other monitoring tools, as it provides all the required insights to fix the issue.

  5. E

    Integrate Cloud Trace with Cloud Monitoring to correlate traces with infrastructure metrics for a deeper understanding of the issue.

Show answer and explanation

Correct answers: A, B, C, E

Explanation

Cloud Trace is a powerful tool for diagnosing and resolving latency issues in distributed applications. By enabling it in your project, instrumenting your code, and using features like latency heatmaps, you can identify high-latency areas. However, integrating it with Cloud Monitoring provides additional context by correlating trace data with infrastructure metrics, ensuring a more thorough understanding of the root cause. Relying solely on Cloud Trace without other monitoring tools limits your troubleshooting capabilities.

  • A. Correct.

    Correct: Reviewing latency distributions in Cloud Trace helps identify patterns of slow requests across services.

  • B. Correct.

    Correct: By instrumenting your application code with the Trace SDK, you can gain visibility into custom spans and identify specific areas responsible for latency.

  • C. Correct.

    Correct: Cloud Trace provides latency heatmaps, which are useful for visualizing and pinpointing high-latency endpoints or services.

  • D. Incorrect.

    Incorrect: While Cloud Trace is powerful, relying on it solely without integrating other tools like Cloud Monitoring may limit your ability to identify root causes tied to infrastructure or external factors.

  • E. Correct.

    Correct: Integrating Cloud Trace with Cloud Monitoring allows you to correlate trace data with metrics like CPU usage, memory, or network activity, offering a comprehensive view of the issue.

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