Google PROFESSIONAL-CLOUD-DEVOPS-ENGINEER Exam (page: 7)
Google Professional Cloud DevOps Engineer
Updated on: 29-Mar-2026

You currently store the virtual machine (VM) utilization logs in Stackdriver. You need to provide an easy-to-share interactive VM utilization dashboard that is updated in real time and contains information aggregated on a quarterly basis. You want to use Google Cloud Platform solutions.
What should you do?

  1. 1. Export VM utilization logs from Stackdriver to BigOuery.
    2. Create a dashboard in Data Studio.
    3. Share the dashboard with your stakeholders.
  2. 1. Export VM utilization logs from Stackdriver to Cloud Pub/Sub.
    2. From Cloud Pub/Sub, send the logs to a Security Information and Event Management (SIEM) system.
    3. Build the dashboards in the SIEM system and share with your stakeholders.
  3. 1. Export VM utilization logs (rom Stackdriver to BigQuery.
    2. From BigQuery. export the logs to a CSV file.
    3. Import the CSV file into Google Sheets.
    4. Build a dashboard in Google Sheets and share it with your stakeholders.
  4. 1. Export VM utilization logs from Stackdriver to a Cloud Storage bucket.
    2. Enable the Cloud Storage API to pull the logs programmatically.
    3. Build a custom data visualization application.

    4. Display the pulled logs in a custom dashboard.

Answer(s): A



You are performing a semiannual capacity planning exercise for your flagship service. You expect a service user growth rate of 10% month-over-month over the next six months. Your service is fully containerized and runs on Google Cloud Platform (GCP). using a Google Kubernetes Engine (GKE) Standard regional cluster on three zones with cluster autoscaler enabled. You currently consume about 30% of your total deployed CPU capacity, and you require resilience against the failure of a zone. You want to ensure that your users experience minimal negative impact as a result of this growth or as a result of zone failure, while avoiding unnecessary costs. How should you prepare to handle the predicted growth?

  1. Verity the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verity your expected resource needs.
  2. Because you are deployed on GKE and are using a cluster autoscaler. your GKE cluster will scale automatically, regardless of growth rate.
  3. Because you are at only 30% utilization, you have significant headroom and you won't need to add any additional capacity for this rate of growth.
  4. Proactively add 60% more node capacity to account for six months of 10% growth rate, and then perform a load test to make sure you have enough capacity.

Answer(s): A

Explanation:

https://cloud.google.com/kubernetes-engine/docs/concepts/horizontalpodautoscaler The Horizontal Pod Autoscaler changes the shape of your Kubernetes workload by automatically increasing or decreasing the number of Pods in response to the workload's CPU or memory consumption



You are managing an application that exposes an HTTP endpoint without using a load balancer. The latency of the HTTP responses is important for the user experience. You want to understand what

HTTP latencies all of your users are experiencing. You use Stackdriver Monitoring.
What should you do?

  1. · In your application, create a metric with a metricKind set to DELTA and a valueType set to DOUBLE.
    · In Stackdriver's Metrics Explorer, use a Slacked Bar graph to visualize the metric.
  2. · In your application, create a metric with a metricKind set to CUMULATIVE and a valueType set to DOUBLE.
    · In Stackdriver's Metrics Explorer, use a Line graph to visualize the metric.
  3. · In your application, create a metric with a metricKind set to gauge and a valueType set to distribution.
    · In Stackdriver's Metrics Explorer, use a Heatmap graph to visualize the metric.
  4. · In your application, create a metric with a metricKind. set toMETRlc_KIND_UNSPECIFIEDanda valueType set to INT64.
    · In Stackdriver's Metrics Explorer, use a Stacked Area graph to visualize the metric.

Answer(s): C

Explanation:

https://sre.google/workbook/implementing-slos/
https://cloud.google.com/architecture/adopting-slos/

Latency is commonly measured as a distribution. Given a distribution, you can measure various percentiles. For example, you might measure the number of requests that are slower than the historical 99th percentile.



You are responsible for creating and modifying the Terraform templates that define your Infrastructure. Because two new engineers will also be working on the same code, you need to define a process and adopt a tool that will prevent you from overwriting each other's code. You also want to ensure that you capture all updates in the latest version.
What should you do?

  1. · Store your code in a Git-based version control system.
    · Establish a process that allows developers to merge their own changes at the end of each day.
    · Package and upload code lo a versioned Cloud Storage bucket as the latest master version.
  2. · Store your code in a Git-based version control system.
    · Establish a process that includes code reviews by peers and unit testing to ensure integrity and functionality before integration of code.
    · Establish a process where the fully integrated code in the repository becomes the latest master version.
  3. · Store your code as text files in Google Drive in a defined folder structure that organizes the files.
    · At the end of each day. confirm that all changes have been captured in the files within the folder structure.
    · Rename the folder structure with a predefined naming convention that increments the version.
  4. · Store your code as text files in Google Drive in a defined folder structure that organizes the files.
    · At the end of each day, confirm that all changes have been captured in the files within the folder structure and create a new .zip archive with a predefined naming convention.
    · Upload the .zip archive to a versioned Cloud Storage bucket and accept it as the latest version.

Answer(s): B



You are running an experiment to see whether your users like a new feature of a web application. Shortly after deploying the feature as a canary release, you receive a spike in the number of 500 errors sent to users, and your monitoring reports show increased latency. You want to quickly minimize the negative impact on users.
What should you do first?

  1. Roll back the experimental canary release.
  2. Start monitoring latency, traffic, errors, and saturation.
  3. Record data for the postmortem document of the incident.
  4. Trace the origin of 500 errors and the root cause of increased latency.

Answer(s): A



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