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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q96-Q101):

NEW QUESTION # 96
Your company experiences bugs, outages, and slowness in its production systems. Developers use the production environment for new feature development and bug fixes. Configuration and experiments are done in the production environment, causing outages for users. Testers use the production environment for load testing, which often slows the production systems. You need to redesign the environment to reduce the number of bugs and outages in production and to enable testers to load test new features. What should you do?

A. Create a development environment with smaller server capacity and give access only to developers and testers.
B. Secure the production environment to ensure that developers can't change it and set up one controlled update per year.
C. Create an automated testing script in production to detect failures as soon as they occur.
D. Create a development environment for writing code and a test environment for configurations, experiments, and load testing.

Answer: C

NEW QUESTION # 97
Your application images are built and pushed to Google Container Registry (GCR). You want to build an automated pipeline that deploys the application when the image is updated while minimizing the development effort. What should you do?

A. Use Cloud Pub/Sub to trigger a custom deployment service running in Google Kubernetes Engine (GKE).
B. Use Cloud Pub/Sub to bigger a Spinnaker pipeline.
C. Use Cloud Build to trigger a Spinnaker pipeline.
D. Use a custom builder in Cloud Build to trigger Jenkins pipeline.

Answer: A

NEW QUESTION # 98
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?
Install a continuous profiling tool into Compute Engine. Configure the application to send profiling data to the tool.

A. Configure Cloud Profiler, and initialize the cloud.go@gle.com/go/profiler library in the application.
B. Use Cloud Monitoring to assess the App Engine CPU utilization metric.
C. Periodically run the go tool pprof command against the application instance. Analyze the results by using flame graphs.

Answer: B

Explanation:
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.

NEW QUESTION # 99
You work for a global organization and are running a monolithic application on Compute Engine You need to select the machine type for the application to use that optimizes CPU utilization by using the fewest number of steps You want to use historical system metncs to identify the machine type for the application to use You want to follow Google-recommended practices What should you do?

A. Review the Cloud Monitoring dashboard for the VM and choose the machine type with the lowest CPU utilization
B. Use the Recommender API and apply the suggested recommendations
C. Install the Ops Agent in a fleet of VMs by using the gcloud CLI
D. Create an Agent Policy to automatically install Ops Agent in all VMs

Answer: B

Explanation:
The best option for selecting the machine type for the application to use that optimizes CPU utilization by using the fewest number of steps is to use the Recommender API and apply the suggested recommendations.
The Recommender API is a service that provides recommendations for optimizing your Google Cloud resources, such as Compute Engine instances, disks, and firewalls. You can use the Recommender API to get recommendations for changing the machine type of your Compute Engine instances based on historical system metrics, such as CPU utilization. You can also apply the suggested recommendations by using the Recommender API or Cloud Console. This way, you can optimize CPU utilization by using the most suitable machine type for your application with minimal effort.

NEW QUESTION # 100
You recently noticed that one Of your services has exceeded the error budget for the current rolling window period. Your company's product team is about to launch a new feature. You want to follow Site Reliability Engineering (SRE) practices.
What should you do?

A. Notify the team that their error budget is used up. Negotiate with the team for a launch freeze or tolerate a slightly worse user experience.
B. Escalate the situation and request additional error budget.
C. Notify the team about the lack of error budget and ensure that all their tests are successful so the launch will not further risk the error budget.
D. Look through other metrics related to the product and find SLOs with remaining error budget.
Reallocate the error budgets and allow the feature launch.

Answer: A

Explanation:
The correct answer is A. Notify the team that their error budget is used up. Negotiate with the team for a launch freeze or tolerate a slightly worse user experience.
According to the Site Reliability Engineering (SRE) practices, an error budget is the amount of unreliability that a service can tolerate without harming user satisfaction1.An error budget is derived from the service-level objectives (SLOs), which are the measurable goals for the service quality2. When a service exceeds its error budget, it means that it has violated its SLOs and may have negatively impacted the users.In this case, the SRE team should notify the product team that their error budget is used up and negotiate with them for a launch freeze or a lower SLO3. A launch freeze means that no new features are deployed until the service reliability is restored. A lower SLO means that the product team accepts a slightly worse user experience in exchange for launching new features. Both options require a trade-off between reliability and innovation, and should be agreed upon by both teams.
The other options are incorrect because they do not follow the SRE practices.Option B is incorrect because it violates the principle of error budget autonomy, which means that each service should have its own error budget and SLOs, and should not borrow or reallocate them from other services4. Option C is incorrect because it does not address the root cause of the error budget overspend, and may create unrealistic expectations for the service reliability. Option D is incorrect because it does not prevent the possibility of introducing new errors or bugs with the feature launch, which may further degrade the service quality and user satisfaction.
Reference:
Error Budgets, Error Budgets.Service Level Objectives, Service Level Objectives.Error Budget Policies, Error Budget Policies.Error Budget Autonomy, Error Budget Autonomy.

NEW QUESTION # 101
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