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The Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam consists of multiple-choice questions and simulations that test the candidate's ability to apply their knowledge in real-world scenarios. Candidates must demonstrate their ability to design and implement solutions using Google Cloud Platform services such as App Engine, Kubernetes, Cloud Functions, and Cloud Storage. They must also demonstrate their ability to use tools such as Stackdriver, Cloud Logging, and Cloud Monitoring to manage and monitor their applications and services.
Google Professional-Cloud-DevOps-Engineer certification is an excellent choice for professionals who are interested in developing their skills and knowledge in the field of cloud DevOps engineering. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification program is designed to help professionals gain a deeper understanding of cloud computing concepts, DevOps principles, and best practices for deploying and maintaining applications on GCP.
NEW QUESTION # 95
You support a high-traffic web application and want to ensure that the home page loads in a timely manner. As a first step, you decide to implement a Service Level Indicator (SLI) to represent home page request latency with an acceptable page load time set to 100 ms. What is the Google-recommended way of calculating this SLI?
- A. Bucketize the request latencies into ranges, and then compute the median and 90th percentiles.
- B. Count the number of home page requests that load in under 100 ms, and then divide by the total number of home page requests.
- C. Count the number of home page requests that load in under 100 ms. and then divide by the total number of all web application requests.
- D. Buckelize Ihe request latencies into ranges, and then compute the percentile at 100 ms.
Answer: D
NEW QUESTION # 96
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. Create an Agent Policy to automatically install Ops Agent in all VMs
- B. Review the Cloud Monitoring dashboard for the VM and choose the machine type with the lowest CPU utilization
- C. Install the Ops Agent in a fleet of VMs by using the gcloud CLI
- D. Use the Recommender API and apply the suggested recommendations
Answer: D
Explanation:
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 # 97
You need to deploy a new service to production. The service needs to automatically scale using a Managed Instance Group (MIG) and should be deployed over multiple regions. The service needs a large number of resources for each instance and you need to plan for capacity. What should you do?
- A. Deploy the service in one region and use a global load balancer to route traffic to this region.
- B. Validate that the resource requirements are within the available quota limits of each region.
- C. Use the n1-highcpu-96 machine type in the configuration of the MIG.
- D. Monitor results of Stackdriver Trace to determine the required amount of resources.
Answer: A
NEW QUESTION # 98
You are working with a government agency that requires you to archive application logs for seven years. You need to configure Stackdriver to export and store the logs while minimizing costs of storage. What should you do?
- A. Create a Cloud Storage bucket and develop your application to send logs directly to the bucket.
- B. Develop an App Engine application that pulls the logs from Stackdriver and saves them in BigQuery.
- C. Create an export in Stackdriver and configure Cloud Pub/Sub to store logs in permanent storage for seven years.
- D. Create a sink in Stackdriver, name it, create a bucket on Cloud Storage for storing archived logs, and then select the bucket as the log export destination.
Answer: D
Explanation:
https://cloud.google.com/logging/docs/routing/overview
NEW QUESTION # 99
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. Convert the instances to preemptible virtual machines.
- B. Purchase Committed Use Discounts.
- C. Migrate the instances to a Managed Instance Group.
- D. Create an Unmanaged Instance Group for the instances used to run the workload.
Answer: B
NEW QUESTION # 100
You support a multi-region web service running on Google Kubernetes Engine (GKE) behind a Global HTTP'S Cloud Load Balancer (CLB). For legacy reasons, user requests first go through a third-party Content Delivery Network (CDN). which then routes traffic to the CLB. You have already implemented an availability Service Level Indicator (SLI) at the CLB level. However, you want to increase coverage in case of a potential load balancer misconfiguration. CDN failure, or other global networking catastrophe. Where should you measure this new SLI?
Choose 2 answers
- A. Instrumentation coded directly in the client
- B. Your application servers' logs
- C. A synthetic client that periodically sends simulated user requests
- D. Metrics exported from the application servers
- E. GKE health checks for your application servers
Answer: D,E
NEW QUESTION # 101
Your organization stores all application logs from multiple Google Cloud projects in a central Cloud Logging project. Your security team wants to enforce a rule that each project team can only view their respective logs, and only the operations team can view all the logs. You need to design a solution that meets the security team's requirements, while minimizing costs. What should you do?
- A. Create log views for each project team, and only show each project team their application logs. Grant the operations team access to the _ Al Il-jogs View in the central logging project.
- B. Create Identity and Access Management (IAM) roles for each project team and restrict access to the _ Default log view in their individual Google Cloud project. Grant viewer access to the operations team in the central logging project.
- C. Grant each project team access to the project _ Default view in the central logging project. Grant logging viewer access to the operations team in the central logging project.
- D. Export logs to BigQuery tables for each project team. Grant project teams access to their tables. Grant logs writer access to the operations team in the central logging project.
Answer: A
Explanation:
Explanation
Create log views for each project team, and only show each project team their application logs. Grant the operations team access to the _AllLogs View in the central logging project1.
This approach aligns with the Google Cloud's recommended methodologies for Professional Cloud DevOps Engineers1. Log views allow you to create and manage access control at a finer granularity for your logs. By creating a separate log view for each project team, you can ensure that they only have access to their respective logs. The operations team, on the other hand, can be granted access to the _AllLogs view in the central logging project, allowing them to view all logs as required.
This solution not only meets the security team's requirements but also minimizes costs as it leverages built-in features of Google Cloud's logging and does not require exporting logs to another service like BigQuery (as suggested in option A), which could incur additional costs1.
NEW QUESTION # 102
Some of your production services are running in Google Kubernetes Engine (GKE) in the eu-west-1 region. Your build system runs in the us-west-1 region. You want to push the container images from your build system to a scalable registry to maximize the bandwidth for transferring the images to the cluster. What should you do?
- A. Push the images to Google Container Registry (GCR) using the eu.gcr.io hostname.
- B. Push the images to Google Container Registry (GCR) using the gcr.io hostname.
- C. Push the images to Google Container Registry (GCR) using the us.gcr.io hostname.
- D. Push the images to a private image registry running on a Compute Engine instance in the eu-west-1 region.
Answer: A
Explanation:
Hostname Storage location gcr.io Stores images in data centers in the United States asia.gcr.io Stores images in data centers in Asia eu.gcr.io Stores images in data centers within member states of the European Union us.gcr.io Stores images in data centers in the United States
NEW QUESTION # 103
Your team of Infrastructure DevOps Engineers is growing, and you are starting to use Terraform to manage infrastructure. You need a way to implement code versioning and to share code with other team members. What should you do?
- A. Store the Terraform code in a network shared folder with child folders for each version release. Ensure that everyone works on different files.
- B. Store the Terraform code in a Cloud Storage bucket using object versioning. Give access to the bucket to every team member so they can download the files.
- C. Store the Terraform code in a version-control system. Establish procedures for pushing new versions and merging with the master.
- D. Store the Terraform code in a shared Google Drive folder so it syncs automatically to every team member's computer. Organize files with a naming convention that identifies each new version.
Answer: C
Explanation:
https://www.terraform.io/docs/cloud/guides/recommended-practices/part3.3.html
NEW QUESTION # 104
You are responsible for the reliability of a high-volume enterprise application. A large number of users report that an important subset of the application's functionality - a data intensive reporting feature - is consistently failing with an HTTP 500 error. When you investigate your application's dashboards, you notice a strong correlation between the failures and a metric that represents the size of an internal queue used for generating reports. You trace the failures to a reporting backend that is experiencing high I/O wait times. You quickly fix the issue by resizing the backend's persistent disk (PD). How you need to create an availability Service Level Indicator (SLI) for the report generation feature. How would you define it?
- A. As the reporting backend PD throughout capacity compared to a known-good threshold
- B. As the proportion of report generation requests that result in a successful response
- C. As the I/O wait times aggregated across all report generation backends
- D. As the application's report generation queue size compared to a known-good threshold
Answer: B
Explanation:
According to SRE Workbook, one of potential SLI is as below:
* Type of service: Request-driven
* Type of SLI: Availability
* Description: The proportion of requests that resulted in a successful response.
https://sre.google/workbook/implementing-slos/
NEW QUESTION # 105
You support a multi-region web service running on Google Kubernetes Engine (GKE) behind a Global HTTP'S Cloud Load Balancer (CLB). For legacy reasons, user requests first go through a third-party Content Delivery Network (CDN). which then routes traffic to the CLB. You have already implemented an availability Service Level Indicator (SLI) at the CLB level. However, you want to increase coverage in case of a potential load balancer misconfiguration. CDN failure, or other global networking catastrophe. Where should you measure this new SLI?
Choose 2 answers
- A. Metrics exported from the application servers
- B. Instrumentation coded directly in the client
- C. Your application servers' logs
- D. A synthetic client that periodically sends simulated user requests
- E. GKE health checks for your application servers
Answer: B,D
NEW QUESTION # 106
You support an application running on App Engine. The application is used globally and accessed from various device types. You want to know the number of connections. You are using Stackdriver Monitoring for App Engine. What metric should you use?
- A. flex/instance/connections/current
- B. tcp_ssl_proxy/new_connections
- C. flex/connections/current
- D. tcp_ssl_proxy/open_connections
Answer: C
Explanation:
https://cloud.google.com/monitoring/api/metrics_gcp#gcp-appengine
NEW QUESTION # 107
Your team is designing a new application for deployment into Google Kubernetes Engine (GKE). You need to set up monitoring to collect and aggregate various application-level metrics in a centralized location. You want to use Google Cloud Platform services while minimizing the amount of work required to set up monitoring.
What should you do?
- A. Emit all metrics in the form of application-specific log messages, pass these messages from the containers to the Stackdriver logging collector, and then observe metrics in Stackdriver.
- B. Install the OpenTelemetry client libraries in the application, configure Stackdriver as the export destination for the metrics, and then observe the application's metrics in Stackdriver.
- C. Publish various metrics from the application directly to the Slackdriver Monitoring API, and then observe these custom metrics in Stackdriver.
- D. Install the Cloud Pub/Sub client libraries, push various metrics from the application to various topics, and then observe the aggregated metrics in Stackdriver.
Answer: C
Explanation:
Explanation
https://cloud.google.com/kubernetes-engine/docs/concepts/custom-and-external-metrics#custom_metrics
https://github.com/GoogleCloudPlatform/k8s-stackdriver/blob/master/custom-metrics-stackdriver-adapter/READ Your application can report a custom metric to Cloud Monitoring. You can configure Kubernetes to respond to these metrics and scale your workload automatically. For example, you can scale your application based on metrics such as queries per second, writes per second, network performance, latency when communicating with a different application, or other metrics that make sense for your workload.
https://cloud.google.com/kubernetes-engine/docs/concepts/custom-and-external-metrics
NEW QUESTION # 108
You use Terraform to manage an application deployed to a Google Cloud environment The application runs on instances deployed by a managed instance group The Terraform code is deployed by using a CI/CD pipeline When you change the machine type on the instance template used by the managed instance group, the pipeline fails at the terraform apply stage with the following error message
You need to update the instance template and minimize disruption to the application and the number of pipeline runs What should you do?
- A. Remove the managed instance group from the Terraform state file update the instance template and reimport the managed instance group.
- B. Set the create_bef ore_destroy meta-argument to true in the lifecycle block on the instance template
- C. Delete the managed instance group and recreate it after updating the instance template
- D. Add a new instance template update the managed instance group to use the new instance template and delete the old instance template
Answer: B
Explanation:
Explanation
The best option for updating the instance template and minimizing disruption to the application and the number of pipeline runs is to set the create_before_destroy meta-argument to true in the lifecycle block on the instance template. The create_before_destroy meta-argument is a Terraform feature that specifies that a new resource should be created before destroying an existing one during an update. This way, you can avoid downtime and errors when updating a resource that is in use by another resource, such as an instance template that is used by a managed instance group. By setting the create_before_destroy meta-argument to true in the lifecycle block on the instance template, you can ensure that Terraform creates a new instance template with the updated machine type, updates the managed instance group to use the new instance template, and then deletes the old instance template.
NEW QUESTION # 109
You support a production service that runs on a single Compute Engine instance. You regularly need to spend time on recreating the service by deleting the crashing instance and creating a new instance based on the relevant image. You want to reduce the time spent performing manual operations while following Site Reliability Engineering principles. What should you do?
- A. File a bug with the development team so they can find the root cause of the crashing instance.
- B. Add a Load Balancer in front of the Compute Engine instance and use health checks to determine the system status.
- C. Create a Stackdriver Monitoring dashboard with SMS alerts to be able to start recreating the crashed instance promptly after it has crashed.
- D. Create a Managed Instance Group with a single instance and use health checks to determine the system status.
Answer: B
NEW QUESTION # 110
You recently deployed your application in Google Kubernetes Engine (GKE) and now need to release a new version of the application You need the ability to instantly roll back to the previous version of the application in case there are issues with the new version Which deployment model should you use?
- A. Perform A. B testing, and test your application periodically after the deployment is complete
- B. Perform a canary deployment, and test your new application periodically after the new version is deployed
- C. Perform a rolling deployment and test your new application after the deployment is complete
- D. Perform a blue/green deployment and test your new application after the deployment is complete
Answer: D
Explanation:
Explanation
The best deployment model for releasing a new version of your application in GKE with the ability to instantly roll back to the previous version is to perform a blue/green deployment and test your new application after the deployment is complete. A blue/green deployment is a deployment strategy that involves creating two identical environments, one running the current version of the application (blue) and one running the new version of the application (green). The traffic is switched from blue to green after testing the new version, and if any issues are discovered, the traffic can be switched back to blue instantly. This way, you can minimize downtime and risk during deployment.
NEW QUESTION # 111
You have a pool of application servers running on Compute Engine. You need to provide a secure solution that requires the least amount of configuration and allows developers to easily access application logs for troubleshooting. How would you implement the solution on GCP?
- A. * Deploy the Stackdriver monitoring agent to the application servers.
* Give the developers the IAM Monitoring Viewer role to access Stackdriver and view metrics. - B. * Deploy the Stackdriver logging agent to the application servers.
* Give the developers the IAM Logs Viewer role to access Stackdriver and view logs. - C. * Install the gsutil command line tool on your application servers.
* Write a script using gsutil to upload your application log to a Cloud Storage bucket, and then schedule it to run via cron every 5 minutes.
* Give the developers the IAM Object Viewer access to view the logs in the specified bucket. - D. * Deploy the Stackdriver logging agent to the application servers.
* Give the developers the IAM Logs Private Logs Viewer role to access Stackdriver and view logs.
Answer: D
NEW QUESTION # 112
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