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Pass Guaranteed Google - Authoritative Professional-Cloud-DevOps-Engineer - Google Cloud Certified - Professional Cloud DevOps Engineer Exam Examcollection Dumps

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Google Professional-Cloud-DevOps-Engineer (Google Cloud Certified - Professional Cloud DevOps Engineer) Certification Exam is a valuable certification for cloud DevOps engineers who want to validate their skills and knowledge in designing, developing, and implementing cloud solutions using GCP services and tools. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam is challenging and requires candidates to have a good understanding of cloud computing, software development, and DevOps practices. Passing the certification exam can enhance the candidate's career prospects and demonstrate their expertise in cloud DevOps engineering.

The Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam consists of multiple-choice questions, scenario-based questions, and hands-on tasks. Professional-Cloud-DevOps-Engineer Exam Duration is two hours, and the passing score is 70%. Professional-Cloud-DevOps-Engineer exam fee is $200 USD, and it is available in multiple languages, including English, Japanese, and Spanish. Candidates can take the exam online or at a test center.

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Google Professional-Cloud-DevOps-Engineer certification exam is designed for professionals who want to demonstrate their expertise in using Google Cloud Platform to build and deploy highly scalable and reliable applications. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is ideal for DevOps engineers, site reliability engineers, and other IT professionals who are responsible for managing and deploying software applications in the cloud. Professional-Cloud-DevOps-Engineer Exam Tests your knowledge of various cloud technologies, tools, and best practices that are essential for DevOps professionals to master.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q69-Q74):

NEW QUESTION # 69
You are running a real-time gaming application on Compute Engine that has a production and testing environment. Each environment has their own Virtual Private Cloud (VPC) network. The application frontend and backend servers are located on different subnets in the environment's VPC. You suspect there is a malicious process communicating intermittently in your production frontend servers. You want to ensure that network traffic is captured for analysis. What should you do?

  • A. Enable VPC Flow Logs on the production VPC network frontend and backend subnets only with a sample volume scale of 1.0.
  • B. Enable VPC Flow Logs on the testing and production VPC network frontend and backend subnets with a volume scale of 0.5. Apply changes in testing before production.
  • C. Enable VPC Flow Logs on the testing and production VPC network frontend and backend subnets with a volume scale of 1.0. Apply changes in testing before production.
  • D. Enable VPC Flow Logs on the production VPC network frontend and backend subnets only with a sample volume scale of 0.5.

Answer: A


NEW QUESTION # 70
As a Site Reliability Engineer, you support an application written in GO that runs on Google Kubernetes Engine (GKE) in production. After releasing a new version Of the application, you notice the application runs for about 15 minutes and then restarts. You decide to add Cloud Profiler to your application and now notice that the heap usage grows constantly until the application restarts. What should you do?

  • A. Add high memory compute nodes to the cluster.
  • B. Increase the CPU limit in the application deployment.
  • C. Add Cloud Trace to the application, and redeploy.
  • D. Increase the memory limit in the application deployment.

Answer: D

Explanation:
The correct answer is B, Increase the memory limit in the application deployment.
The application is experiencing a memory leak, which means that it is allocating memory that is not freed or reused. This causes the heap usage to grow constantly until it reaches the memory limit of the pod, which triggers a restart by Kubernetes. Increasing the memory limit in the application deployment can help mitigate the problem by allowing the application to run longer before reaching the limit. However, this is not a permanent solution, as the memory leak will still occur and eventually exhaust the available memory. The best solution is to identify and fix the source of the memory leak in the application code, using tools like Cloud Profiler and pprof12.
Reference:
Using Cloud Profiler with Go, Troubleshooting memory leaks. Profiling Go Programs, Heap profiles.


NEW QUESTION # 71
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. Apply the conditional role binding resource.name.extract("locations/global/buckets/(bucket)/") ==
    "_Default" to the _Default bucket.
  • C. Apply a jsonPayload.user_email restricted field to the _Default bucket. Grant the Log Field Accessor role to the security team members.
  • D. 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.

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 # 72
You are deploying a Cloud Build job that deploys Terraform code when a Git branch is updated. While testing, you noticed that the job fails. You see the following error in the build logs:
Initializing the backend. ..
Error: Failed to get existing workspaces : querying Cloud Storage failed: googleapi : Error
403
You need to resolve the issue by following Google-recommended practices. What should you do?

  • A. Change the Terraform code to use local state.
  • B. Grant the roles/ owner Identity and Access Management (IAM) role to the Cloud Build service account on the project.
  • C. Create a storage bucket with the name specified in the Terraform configuration.
  • D. Grant the roles/ storage. objectAdmin Identity and Access Management (IAM) role to the Cloud Build service account on the state file bucket.

Answer: D


NEW QUESTION # 73
You support a high-traffic web application with a microservice architecture. The home page of the application displays multiple widgets containing content such as the current weather, stock prices, and news headlines. The main serving thread makes a call to a dedicated microservice for each widget and then lays out the homepage for the user. The microservices occasionally fail; when that happens, the serving thread serves the homepage with some missing content. Users of the application are unhappy if this degraded mode occurs too frequently, but they would rather have some content served instead of no content at all. You want to set a Service Level Objective (SLO) to ensure that the user experience does not degrade too much. What Service Level Indicator {SLI) should you use to measure this?

  • A. An availability SLI: the ratio of healthy microservices to the total number of microservices
  • B. A quality SLI: the ratio of non-degraded responses to total responses
  • C. A freshness SLI: the proportion of widgets that have been updated within the last 10 minutes
  • D. A latency SLI: the ratio of microservice calls that complete in under 100 ms to the total number of microservice calls

Answer: D


NEW QUESTION # 74
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