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Google Professional-Cloud-DevOps-Engineer Exam Tests the candidate’s knowledge in several areas, including cloud architecture, containerization, automation, monitoring, and security. Professional-Cloud-DevOps-Engineer exam is intended for professionals who have experience in designing and implementing DevOps solutions on the Google Cloud Platform. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam is designed to validate the candidates’ knowledge and skills in deploying and managing applications on the Google Cloud Platform using DevOps methodologies. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is highly valued in the industry and is an excellent way for professionals to demonstrate their expertise in Google Cloud technologies.

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Earning the Google Professional-Cloud-DevOps-Engineer Certification can demonstrate to employers that an individual has the skills and knowledge needed to effectively manage cloud technologies with DevOps practices. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification can also lead to better job opportunities and higher salaries for cloud professionals.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q122-Q127):

NEW QUESTION # 122
You manage an application that is writing logs to Stackdriver Logging. You need to give some team members the ability to export logs. What should you do?

Answer: D

Explanation:
Explanation
https://cloud.google.com/logging/docs/access-control
The logging.configWriter role grants permissions to create, update, and delete log exports. This is the correct role to give team members who need to export logs2.


NEW QUESTION # 123
You need to create a Cloud Monitoring SLO for a service that will be published soon. You want to verify that requests to the service will be addressed in fewer than 300 ms at least 90% Of the time per calendar month.
You need to identify the metric and evaluation method to use. What should you do?

Answer: B

Explanation:
The correct answer is A. Select a latency metric for a request-based method of evaluation.
A latency metric measures how responsive your service is to users.For example, you can use thecloud.
googleapis.com/http/server/response_latenciesmetric to measure the latency of HTTP requests to your service1. A request-based method of evaluation counts the number of successful requests that meet a certain criterion, such as being below a latency threshold, and compares it to the number of all requests.For example, you can define an SLI as the ratio of requests with latency below 300 ms to all requests2. A request-based method of evaluation is suitable for measuring performance over time, such as per calendar month.You can set an SLO for the SLI to be at least 90%, which means that you expect 90% of the requests to have latency below 300 ms in a month3.


NEW QUESTION # 124
You are designing a new Google Cloud organization for a client. Your client is concerned with the risks associated with long-lived credentials created in Google Cloud. You need to design a solution to completely eliminate the risks associated with the use of JSON service account keys while minimizing operational overhead. What should you do?

Answer: B

Explanation:
The correct answer is B. Apply the constraints/iam.disableServiceAccountKeyCreation constraint to the organization.
According to the Google Cloud documentation, the constraints/iam.disableServiceAccountKeyCreation constraint is an organization policy constraint that prevents the creation of user-managed service account keys1.User-managed service account keys are long-lived credentials that can be downloaded as JSON or P12 files and used to authenticate as a service account2.These keys pose severe security risks if they are leaked, stolen, or misused by unauthorized entities34.By applying this constraint to the organization, you can completely eliminate the risks associated with the use of JSON service account keys and enforce a more secure alternative for authentication, such as Workload Identity or short-lived access tokens12. This also minimizes operational overhead by avoiding the need to manage, rotate, or revoke user-managed service account keys.
The other options are incorrect because they do not completely eliminate the risks associated with the use of JSON service account keys. Option A is incorrect because it only restricts the IAM permissions to create, list, get, delete, or sign service account keys, but it does not prevent existing keys from being used or leaked.
Option C is incorrect because it only disables the upload of user-managed service account keys, but it does not prevent the creation or download of such keys. Option D is incorrect because it only limits the IAM role that can create and manage service account keys, but it does not prevent the keys from being distributed or exposed to unauthorized entities.
Reference:
Disable user-managed service account key creation, Disable user-managed service account key creation.
Service accounts, User-managed service accounts.Help keep your Google Cloud service account keys safe, Help keep your Google Cloud service account keys safe.Stop Downloading Google Cloud ServiceAccount Keys!, Stop Downloading Google Cloud Service Account Keys! [Service Account Keys], Service Account Keys. [Disable user-managed service account key upload], Disable user-managed service account key upload.
[Granting roles to service accounts], Granting roles to service accounts.


NEW QUESTION # 125
You are configuring your CI/CD pipeline natively on Google Cloud. You want builds in a pre-production Google Kubernetes Engine (GKE) environment to be automatically load-tested before being promoted to the production GKE environment. You need to ensure that only builds that have passed this test are deployed to production. You want to follow Google-recommended practices. How should you configure this pipeline with Binary Authorization?

Answer: B

Explanation:
Explanation
The correct answer is B. Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) authenticated through Workload Identity.
According to the Google Cloud documentation, Binary Authorization is a deploy-time security control that ensures only trusted container images are deployed on Google Kubernetes Engine (GKE) or Cloud Run1.
Binary Authorization uses attestations to certify that a specific image has completed a previous stage in the CI/CD pipeline, such as passing a load test2. Attestations are signed by private keys that are associated with attestors, which are entities that verify the attestations3. To follow Google-recommended practices, you should store your private keys in Cloud Key Management Service (Cloud KMS), which is a secure and scalable service for managing cryptographic keys4. You should also use Workload Identity, which is a feature that allows Kubernetes service accounts to act as Google service accounts, to authenticate to Cloud KMS and sign attestations without having to manage or expose service account keys5.
The other options are incorrect because they do not follow Google-recommended practices. Option A and option D require human intervention to sign the attestations, which is not scalable or automated. Option C exposes the service account JSON key as a Kubernetes Secret, which is less secure than using Workload Identity.


NEW QUESTION # 126
Your organization wants to increase the availability target of an application from 99 9% to 99 99% for an investment of $2 000 The application's current revenue is S1,000,000 You need to determine whether the increase in availability is worth the investment for a single year of usage What should you do?

Answer: A

Explanation:
The best option for determining whether the increase in availability is worth the investment for a single year of usage is to calculate the value of improved availability to be $900, and determine that the increase in availability is not worth the investment. To calculate the value of improved availability, we can use the following formula:
Value of improved availability = Revenue * (New availability - Current availability) Plugging in the given numbers, we get:
Value of improved availability = $1,000,000 * (0.9999 - 0.999) = $900
Since the value of improved availability is less than the investment of $2,000, we can conclude that the increase in availability is not worth the investment.


NEW QUESTION # 127
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