COMPATIBLE GOOGLE PROFESSIONAL-CLOUD-DEVOPS-ENGINEER DESKTOP BASED PRACTICE SOFTWARE

Compatible Google Professional-Cloud-DevOps-Engineer Desktop Based Practice Software

Compatible Google Professional-Cloud-DevOps-Engineer Desktop Based Practice Software

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To prepare for the exam, candidates will need to have a strong understanding of cloud computing, as well as experience with DevOps processes and tools. Google Cloud offers a range of training courses and resources to help candidates prepare for the exam, including online courses, hands-on labs, and practice exams. Candidates can also benefit from working with a study group or seeking the guidance of a certified professional.

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q67-Q72):

NEW QUESTION # 67
You use Cloud Build to build and deploy your application. You want to securely incorporate database credentials and other application secrets into the build pipeline. You also want to minimize the development effort. What should you do?

  • A. Use Cloud Key Management Service (Cloud KMS) to encrypt the secrets and include them in your Cloud Build deployment configuration. Grant Cloud Build access to the KeyRing.
  • B. Use client-side encryption to encrypt the secrets and store them in a Cloud Storage bucket. Store a decryption key in the bucket and grant Cloud Build access to the bucket.
  • C. Encrypt the secrets and store them in the application repository. Store a decryption key in a separate repository and grant Cloud Build access to the repository.
  • D. Create a Cloud Storage bucket and use the built-in encryption at rest. Store the secrets in the bucket and grant Cloud Build access to the bucket.

Answer: A


NEW QUESTION # 68
You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (Pll) is leaking into certain log entry fields. All Pll entries begin with the text userinfo. You want to capture these log entries in a secure location for later review and prevent them from leaking to Stackdriver Logging. What should you do?

  • A. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, and then copy the entries to a Cloud Storage bucket.
  • B. Create a basic log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
  • C. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, create an advanced log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
  • D. Create an advanced log filter matching userinfo, configure a log export in the Stackdriver console with Cloud Storage as a sink, and then configure a tog exclusion with userinfo as a filter.

Answer: A

Explanation:
https://medium.com/google-cloud/fluentd-filter-plugin-for-google-cloud-data-loss-prevention-api-
42bbb1308e76


NEW QUESTION # 69
You are designing a deployment technique for your applications on Google Cloud. As part Of your deployment planning, you want to use live traffic to gather performance metrics for new versions Of your applications. You need to test against the full production load before your applications are launched. What should you do?

  • A. Use A/B testing with blue/green deployment.
  • B. Use canary testing with rolling updates deployment,
  • C. Use shadow testing with continuous deployment.
  • D. Use canary testing with continuous deployment.

Answer: C

Explanation:
Explanation
The correct answer is B. Use shadow testing with continuous deployment.
Shadow testing is a deployment technique that involves routing a copy of the live traffic to a new version of the application, without affecting the production environment. This way, you can gather performance metrics and compare them with the current version, without exposing the new version to the users. Shadow testing can help you test against the full production load and identify any issues or bottlenecks before launching the new version. You can use continuous deployment to automate the process of deploying the new version after it passes the shadow testing.


NEW QUESTION # 70
You manage an application that runs in Google Kubernetes Engine (GKE) and uses the blue/green deployment methodology Extracts of the Kubernetes manifests are shown below

The Deployment app-green was updated to use the new version of the application During post-deployment monitoring you notice that the majority of user requests are failing You did not observe this behavior in the testing environment You need to mitigate the incident impact on users and enable the developers to troubleshoot the issue What should you do?

  • A. Update the Deployment ape-green to use the previous version of the application
  • B. Change the selector on the Service app-svc to app: my-app, version: blue
  • C. Update the Deployment app-blue to use the new version of the application
  • D. Change the selector on the Service app-2vc to app: my-app.

Answer: B

Explanation:
Explanation
The best option for mitigating the incident impact on users and enabling the developers to troubleshoot the issue is to change the selector on the Service app-svc to app: my-app, version: blue. A Service is a resource that defines how to access a set of Pods. A selector is a field that specifies which Pods are selected by the Service. By changing the selector on the Service app-svc to app: my-app, version: blue, you can ensure that the Service only routes traffic to the Pods that have both labels app: my-app and version: blue. These Pods belong to the Deployment app-blue, which uses the previous version of the application. This way, you can mitigate the incident impact on users by switching back to the working version of the application. You can also enable the developers to troubleshoot the issue with the new version of the application in the Deployment app-green without affecting users.


NEW QUESTION # 71
You are configuring Cloud Logging for a new application that runs on a Compute Engine instance with a public IP address. A user-managed service account is attached to the instance. You confirmed that the necessary agents are running on the instance but you cannot see any log entries from the instance in Cloud Logging. You want to resolve the issue by following Google-recommended practices. What should you do?

  • A. Enable Private Google Access on the subnet that the instance is in.
  • B. Add the Logs Writer role to the service account.
  • C. Export the service account key and configure the agents to use the key.
  • D. Update the instance to use the default Compute Engine service account.

Answer: B

Explanation:
Explanation
The correct answer is A. Add the Logs Writer role to the service account.
To use Cloud Logging, the service account attached to the Compute Engine instance must have the necessary permissions to write log entries. The Logs Writer role (roles/logging.logWriter) provides this permission. You can grant this role to the user-managed service account at the project, folder, or organization level1.
Private Google Access is not required for Cloud Logging, as it allows instances without external IP addresses to access Google APIs and services2. The default Compute Engine service account already has the Logs Writer role, but it is not a recommended practice to use it for user applications3. Exporting the service account key and configuring the agents to use the key is not a secure way of authenticating the service account, as it exposes the key to potential compromise4.
References:
1: Access control with IAM | Cloud Logging | Google Cloud
2: Private Google Access overview | VPC | Google Cloud
3: Service accounts | Compute Engine Documentation | Google Cloud
4: Best practices for securing service accounts | IAM Documentation | Google Cloud


NEW QUESTION # 72
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