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Pass Leader Professional-Cloud-DevOps-Engineer Dumps, Professional-Cloud-DevOps-Engineer Test Sample Questions

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q30-Q35):

NEW QUESTION # 30
You support an application running on GCP and want to configure SMS notifications to your team for the most critical alerts in Stackdriver Monitoring. You have already identified the alerting policies you want to configure this for. What should you do?

A. Configure a Slack notification for each alerting policy. Set up a Slack-to-SMS integration to send SMS messages when Slack messages are received. Ensure that your team members add their SMS/phone numbers to the external integration.
B. Download and configure a third-party integration between Stackdriver Monitoring and an SMS gateway. Ensure that your team members add their SMS/phone numbers to the external tool.
C. Select the Webhook notifications option for each alerting policy, and configure it to use a third-party integration tool. Ensure that your team members add their SMS/phone numbers to the external tool.
D. Ensure that your team members set their SMS/phone numbers in their Stackdriver Profile. Select the SMS notification option for each alerting policy and then select the appropriate SMS/phone numbers from the list.

Answer: A

NEW QUESTION # 31
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. Increase the CPU limit in the application deployment.
B. Add Cloud Trace to the application, and redeploy.
C. Increase the memory limit in the application deployment.
D. Add high memory compute nodes to the cluster.

Answer: C

Explanation:
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.

NEW QUESTION # 32
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. Add a Load Balancer in front of the Compute Engine instance and use health checks to determine the system status.
B. Create a Managed Instance Group with a single 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. File a bug with the development team so they can find the root cause of the crashing instance.

Answer: B

NEW QUESTION # 33
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 logging agent to the application servers.
* Give the developers the IAM Logs Private Logs Viewer role to access Stackdriver and view logs.
B. * Deploy the Stackdriver monitoring agent to the application servers.
* Give the developers the IAM Monitoring Viewer role to access Stackdriver and view metrics.
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 Viewer role to access Stackdriver and view logs.

Answer: A

NEW QUESTION # 34
Your team is building a service that performs compute-heavy processing on batches of data The data is processed faster based on the speed and number of CPUs on the machine These batches of data vary in size and may arrive at any time from multiple third-party sources You need to ensure that third parties are able to upload their data securely. You want to minimize costs while ensuring that the data is processed as quickly as possible What should you do?

A. * Provide a secure file transfer protocol (SFTP) server on a Compute Engine instance so that third parties can upload batches of data and provide appropriate credentials to the server
* Create a Cloud Function with a google.storage, object, finalize Cloud Storage trigger Write code so that the function can scale up a Compute Engine autoscaling managed instance group
* Use an image pre-loaded with the data processing software that terminates the instances when processing completes
B. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate identity and Access Management (1AM) access to the bucket
* Create a Cloud Function with a google, storage, object .finalise Cloud Storage trigger Write code so that the function can scale up a Compute Engine autoscaling managed instance group
* Use an image pre-loaded with the data processing software that terminates the instances when processing completes
C. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate Identity and Access Management (1AM) access to the bucket
* Use a standard Google Kubernetes Engine (GKE) cluster and maintain two services one that processes the batches of data and one that monitors Cloud Storage for new batches of data
* Stop the processing service when there are no batches of data to process
D. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate Identity and Access Management (1AM) access to the bucket
* Use Cloud Monitoring to detect new batches of data in the bucket and trigger a Cloud Function that processes the data
* Set a Cloud Function to use the largest CPU possible to minimize the runtime of the processing

Answer: B

Explanation:
Explanation
The best option for ensuring that third parties are able to upload their data securely and minimizing costs while ensuring that the data is processed as quickly as possible is to provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate Identity and Access Management (IAM) access to the bucket; create a Cloud Function with a google.storage.object.finalize Cloud Storage trigger; write code so that the function can scale up a Compute Engine autoscaling managed instance group; use an image pre-loaded with the data processing software that terminates the instances when processing completes. A Cloud Storage bucket is a resource that allows you to store and access data in Google Cloud. You can provide a Cloud Storage bucket so that third parties can upload batches of data securely and conveniently. You can also provide appropriate IAM access to the bucket by using roles and policies to control who can read or write data to the bucket. A Cloud Function is a serverless function that executes code in response to an event, such as a change in a Cloud Storage bucket. A google.storage.object.finalize trigger is a type of trigger that fires when a new object is created or an existing object is overwritten in a Cloud Storage bucket. You can create a Cloud Function with a google.storage.object.finalize trigger so that the function runs whenever a new batch of data is uploaded to the bucket. You can write code so that the function can scale up a Compute Engine autoscaling managed instance group, which is a group of VM instances that automatically adjusts its size based on load or custom metrics. You can use an image pre-loaded with the data processing software that terminates the instances when processing completes, which means that the instances only run when there is data to process and stop when they are done. This way, you can minimize costs while ensuring that the data is processed as quickly as possible.

NEW QUESTION # 35
......

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