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Professional-Cloud-DevOps-Engineer Pass4sure Guide & Professional-Cloud-DevOps-Engineer Exam Preparation & Professional-Cloud-DevOps-Engineer Study Materials

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Google Professional-Cloud-DevOps-Engineer Certification Exam is a highly coveted credential for professionals who want to demonstrate their expertise in cloud DevOps engineering. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam is designed to test the candidate's knowledge and skills in various cloud-based DevOps tools and technologies, including infrastructure automation, continuous integration and delivery, monitoring and logging, and security and compliance.

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How to book Google Professional Cloud DevOps Engineer Exams

The registration for the Google Professional Cloud DevOps Engineer exam follows the steps given below.

Step 1: Visit the Google Cloud Webassessor Website
Step 2: Sign-in or sign up to your Google Cloud Webassessor account
Step 3: Search for the exam name Google Professional Cloud DevOps Engineer
Step 4: Take the date of the exam, choose the exam center, and make further payment using payment methods like credit/debit, etc.

After registering for the exam, prepare from the Professional Cloud DevOps Engineer exam dumps and make sure to take Professional Cloud DevOps Engineer practice exam so you know the exam format in advance. This will give you an advantage over other candidates.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q123-Q128):

NEW QUESTION # 123
You need to enforce several constraint templates across your Google Kubernetes Engine (GKE) clusters. The constraints include policy parameters, such as restricting the Kubernetes API. You must ensure that the policy parameters are stored in a GitHub repository and automatically applied when changes occur. What should you do?

A. Configure Config Sync with the GitHub repository. When there is a change in the repository, use Config Sync to apply the change.
B. When there is a change in GitHub, use a webhook to send a request to Cloud Service Mesh, and apply the change.
C. Set up a GitHub action to trigger Cloud Build when there is a parameter change. In Cloud Build, run a gcloud CLI command to apply the change.
D. Configure Config Connector with the GitHub repository. When there is a change in the repository, use Config Connector to apply the change.

Answer: A

NEW QUESTION # 124
You support a web application that is hosted on Compute Engine. The application provides a booking service for thousands of users. Shortly after the release of a new feature, your monitoring dashboard shows that all users are experiencing latency at login. You want to mitigate the impact of the incident on the users of your service. What should you do first?

A. Review the Stackdriver monitoring.
B. Deploy a new release to see whether it fixes the problem.
C. Upsize the virtual machines running the login services.
D. Roll back the recent release.

Answer: C

NEW QUESTION # 125
You are the on-call Site Reliability Engineer for a microservice that is deployed to a Google Kubernetes Engine (GKE) Autopilot cluster. Your company runs an online store that publishes order messages to Pub/Sub and a microservice receives these messages and updates stock information in the warehousing system. A sales event caused an increase in orders, and the stock information is not being updated quickly enough. This is causing a large number of orders to be accepted for products that are out of stock You check the metrics for the microservice and compare them to typical levels.

You need to ensure that the warehouse system accurately reflects product inventory at the time orders are placed and minimize the impact on customers What should you do?

A. Add a virtual queue to the online store that allows typical traffic levels
B. Increase the number of Pod replicas
C. Increase the Pod CPU and memory limits
D. Decrease the acknowledgment deadline on the subscription

Answer: B

Explanation:
The best option for ensuring that the warehouse system accurately reflects product inventory at the time orders are placed and minimizing the impact on customers is to increase the number of Pod replicas.
Increasing the number of Pod replicas will increase the scalability and availability of your microservice, which will allow it to handle more Pub/Sub messages and update stock information faster. This way, you can reduce the backlog of undelivered messages and oldest unacknowledged message age, which are causing delays in updating product inventory. You can use Horizontal Pod Autoscaler or Cloud Monitoring metrics- based autoscaling to automatically adjust the number of Pod replicas based on load or custom metrics.

NEW QUESTION # 126
You are using Stackdriver to monitor applications hosted on Google Cloud Platform (GCP). You recently deployed a new application, but its logs are not appearing on the Stackdriver dashboard.
You need to troubleshoot the issue. What should you do?

A. Confirm that port 25 has been opened in the firewall to allow messages through to Stackdriver.
B. Confirm that the application is using the required client library and the service account key has proper permissions.
C. Confirm that your account has the proper permissions to use the Stackdriver dashboard.
D. Confirm that the Stackdriver agent has been installed in the hosting virtual machine.

Answer: D

Explanation:
Explanation
https://cloud.google.com/monitoring/agent/monitoring/troubleshooting#checklist

NEW QUESTION # 127
Your company runs an e-commerce business. The application responsible for payment processing has structured JSON logging with the following schema:
Capture and access of logs from the payment processing application is mandatory for operations, but the jsonPayload.user_email field contains personally identifiable information (PII). Your security team does not want the entire engineering team to have access to PII. You need to stop exposing PII to the engineering team and restrict access to security team members only. What should you do?

A. Apply a jsonPayload.user_email exclusion filter to the _Default bucket.
B. Modify the application to toggle inclusion of user_email when the log_user_email environment variable is set to true. Restrict the engineering team members who can change the production environment variable by using the CODEOWNERS file.
C. Apply a jsonPayload.user_email restricted field to the _Default bucket. Grant the Log Field Accessor role to the security team members.
D. Apply the conditional role binding resource.name.extract("locations/global/buckets/(bucket)/") ==
"_Default" to the _Default bucket.

Answer: C

Explanation:
To restrict access to specific sensitive log fields (e.g. PII), Google Cloud offers Log field-level access control
. You can apply field-level restrictions and then assign the Log Field Accessor role only to trusted personnel.
"You can use field-level access control to restrict access to certain fields in your logs. For example, you can restrict access to jsonPayload.user_email."
- Cloud Logging Field-Level Access
"Grant the roles/logging.fieldAccessor role to principals that require access to these restricted fields."
- Log Field Accessor Role
This lets your operations team continue using logs while ensuring that PII is only visible to the security team
, fulfilling your compliance obligations.

NEW QUESTION # 128
......

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