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Google Professional-Cloud-DevOps-Engineer is a prestigious certification designed for IT professionals who are interested in pursuing a career in cloud-based DevOps engineering. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is intended for experienced IT professionals who have an in-depth understanding of DevOps practices and principles and who are skilled in implementing and managing cloud-based solutions. Google Professional-Cloud-DevOps-Engineer Certification is designed to validate the skills required to design, develop, and manage DevOps pipelines that leverage Google Cloud technologies.
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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q152-Q157):
NEW QUESTION # 152
You are creating a CI/CD pipeline to perform Terraform deployments of Google Cloud resources Your CI/CD tooling is running in Google Kubernetes Engine (GKE) and uses an ephemeral Pod for each pipeline run You must ensure that the pipelines that run in the Pods have the appropriate Identity and Access Management (1AM) permissions to perform the Terraform deployments You want to follow Google-recommended practices for identity management What should you do?
Choose 2 answers
- A. Create a new Google service account, and assign the appropriate 1AM permissions
- B. Assign the appropriate 1AM permissions to the Google service account associated with the Compute Engine VM instances that run the Pods
- C. Create a new JSON service account key for the Google service account store the key in the secret management store for the CI/CD tool and configure Terraform to use this key for authentication
- D. Create a new Kubernetes service account, and assign the service account to the Pods Use Workload Identity to authenticate as the Google service account
- E. Create a new JSON service account key for the Google service account store the key as a Kubernetes secret, inject the key into the Pods, and set the boogle_application_credentials environment variable
Answer: A,D
NEW QUESTION # 153
Your CTO has asked you to implement a postmortem policy on every incident for internal use. You want to define what a good postmortem is to ensure that the policy is successful at your company. What should you do?
Choose 2 answers
- A. Ensure that all postmortems include what caused the incident, identify the person or team responsible for causing the incident. and how to prevent a future occurrence of the incident.
- B. Ensure that all postmortems include all incident participants in postmortem authoring and share postmortems as widely as possible,
- C. Ensure that all postmortems include the severity of the incident, how to prevent a future occurrence of the incident. and what caused the incident without naming internal system components.
- D. Ensure that all postmortems include what caused the incident, how the incident could have been worse, and how to prevent a future occurrence of the incident.
- E. Ensure that all postmortems include how the incident was resolved and what caused the incident without naming customer information.
Answer: B,D
Explanation:
The correct answers are B and E.
A good postmortem should include what caused the incident, how the incident could have been worse, and how to prevent a future occurrence of the incident1. This helps to identify the root cause of the problem, the impact of the incident, and the actions to take to mitigate or eliminate the risk of recurrence.
A good postmortem should also include all incident participants in postmortem authoring and share postmortems as widely as possible2. This helps to foster a culture of learning and collaboration, as well as to increase the visibility and accountability of the incident response process.
Answer A is incorrect because it assigns blame to a person or team, which goes against the principle of blameless postmortems2. Blameless postmortems focus on finding solutions rather than pointing fingers, and encourage honest and constructive feedback without fear of punishment.
Answer C is incorrect because it omits how the incident could have been worse, which is an important factor to consider when evaluating the severity and impact of the incident1. It also avoids naming internal system components, which makes it harder to understand the technical details and root cause of the problem.
Answer D is incorrect because it omits how to prevent a future occurrence of the incident, which is the main goal of a postmortem1. It also avoids naming customer information, which may be relevant for understanding the impact and scope of the incident.
NEW QUESTION # 154
You need to run a business-critical workload on a fixed set of Compute Engine instances for several months.
The workload is stable with the exact amount of resources allocated to it. You want to lower the costs for this workload without any performance implications. What should you do?
- A. Purchase Committed Use Discounts.
- B. Create an Unmanaged Instance Group for the instances used to run the workload.
- C. Convert the instances to preemptible virtual machines.
- D. Migrate the instances to a Managed Instance Group.
Answer: C
Explanation:
Explanation/Reference: https://cloud.google.com/compute/docs/faq
NEW QUESTION # 155
You use Cloud Build to build your application. You want to reduce the build time while minimizing cost and development effort. What should you do?
- A. Use Cloud Storage to cache intermediate artifacts.
- B. Run multiple Jenkins agents to parallelize the build.
- C. Use multiple smaller build steps to minimize execution time.
- D. Use larger Cloud Build virtual machines (VMs) by using the machine-type option.
Answer: C
Explanation:
Explanation
https://cloud.google.com/storage/docs/best-practices
https://cloud.google.com/build/docs/speeding-up-builds#caching_directories_with_google_cloud_storage Caching directories with Google Cloud Storage To increase the speed of a build, reuse the results from a previous build. You can copy the results of a previous build to a Google Cloud Storage bucket, use the results for faster calculation, and then copy the new results back to the bucket. Use this method when your build takes a long time and produces a small number of files that does not take time to copy to and from Google Cloud Storage.
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NEW QUESTION # 156
Your company processes IOT data at scale by using Pub/Sub, App Engine standard environment, and an application written in GO. You noticed that the performance inconsistently degrades at peak load. You could not reproduce this issue on your workstation. You need to continuously monitor the application in production to identify slow paths in the code. You want to minimize performance impact and management overhead. What should you do?
- A. Configure Cloud Profiler, and initialize the [email protected]/go/profiler library in the application.
- B. Periodically run the go tool pprof command against the application instance. Analyze the results by using flame graphs.
- C. Use Cloud Monitoring to assess the App Engine CPU utilization metric.
- D. Install a continuous profiling tool into Compute Engine. Configure the application to send profiling data to the tool.
Answer: A
Explanation:
The correct answer is C. Configure Cloud Profiler, and initialize the cloud.google.com/go/profiler library in the application.
According to the Google Cloud documentation, Cloud Profiler is a statistical, low-overhead profiler that continuously gathers CPU usage and memory-allocation information from your production applications1. Cloud Profiler can help you identify slow paths in your code and optimize the performance of your applications. Cloud Profiler supports applications written in Go that run on App Engine standard environment2. To use Cloud Profiler, you need to configure it in your Google Cloud project and initialize the cloud.google.com/go/profiler library in your application code3. You can then use the Cloud Profiler interface to analyze the profiling data and visualize the results by using flame graphs4. Cloud Profiler has minimal performance impact and management overhead, as it only samples a small fraction of the application activity and does not require any additional infrastructure or agents.
The other options are incorrect because they do not meet the requirements of minimizing performance impact and management overhead. Option A is incorrect because it requires installing a continuous profiling tool into Compute Engine, which is an additional infrastructure that needs to be managed and maintained. Option B is incorrect because it requires periodically running the go tool pprof command against the application instance, which is a manual and disruptive process that can affect the application performance. Option D is incorrect because it only uses Cloud Monitoring to assess the App Engine CPU utilization metric, which is not enough to identify slow paths in the code or optimize the application performance.
Reference:
Cloud Profiler documentation, Overview. Profiling Go applications, Supported environments. Profiling Go applications, Using Cloud Profiler. Analyzing data, Analyzing data.
NEW QUESTION # 157
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