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Tested Material Used To Google Get Ahead Professional-Cloud-DevOps-Engineer Exam Certification

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q166-Q171):

NEW QUESTION # 166
Your team deploys applications to three Google Kubernetes Engine (GKE) environments development staging and production You use GitHub reposrtones as your source of truth You need to ensure that the three environments are consistent You want to follow Google-recommended practices to enforce and install network policies and a logging DaemonSet on all the GKE clusters in those environments What should you do?

A. Use Google Cloud Deploy to deploy the network policies and the DaemonSet Use Cloud Monitoring to trigger an alert if the network policies and DaemonSet drift from your source in the repository.
B. Use Google Cloud Deploy to deploy the DaemonSet and use Policy Controller to configure the network policies Use Cloud Monitoring to detect drifts from the source in the repository and Cloud Functions tocorrect the drifts
C. Use Cloud Build to render and deploy the network policies and the DaemonSet Set up Config Sync to sync the configurations for the three environments
D. Use Cloud Build to render and deploy the network policies and the DaemonSet Set up a Policy Controller to enforce the configurations for the three environments

Answer: C

NEW QUESTION # 167
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 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
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
* 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
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
* 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
D. * 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

Answer: C

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 # 168
Your team is running microservices in Google Kubernetes Engine (GKE) You want to detect consumption of an error budget to protect customers and define release policies What should you do?

A. Use the metrics from Anthos Service Mesh to measure the health of the microservices
B. Create SLIs from metrics Enable Alert Policies if the services do not pass
C. Create a SLO and configure uptime checks for your services Enable Alert Policies if the services do not pass
D. Create a SLO Create an Alert Policy on select_slo_bum_rate

Answer: D

Explanation:
The best option for detecting consumption of an error budget to protect customers and define release policies is to create a service level objective (SLO) and create an alert policy on select_slo_burn_rate. A SLO is a target value or range of values for a service level indicator (SLI) that measures some aspect of the service quality, such as availability or latency. An error budget is the amount of time or number of errors that a service can tolerate while still meeting its SLO. A select_slo_burn_rate is a metric that indicates how fast the error budget is being consumed by the service. By creating an alert policy on select_slo_burn_rate, you can trigger notifications or actions when the error budget consumption exceeds a certain threshold. This way, you can balance change, velocity, and reliability of the service by adjusting the release policies based on the error budget status.

NEW QUESTION # 169
You are leading a DevOps project for your organization. The DevOps team is responsible for managing the service infrastructure and being on-call for incidents. The Software Development team is responsible for writing, submitting, and reviewing code. Neither team has any published SLOs. You want to design a new joint-ownership model for a service between the DevOps team and the Software Development team. Which responsibilities should be assigned to each team in the new joint-ownership model?

A. DevOps team responsibilitiesManage the service infrastructureBe on-call for incidentsPerform code reviewsSoftware Development team responsibilitiesSubmit code to be reviewed by the DevOps teamPublish the SLOs that the DevOps team must meet
B. DevOps team responsibilitiesManage the service infrastructurePerform code reviewsSoftware Development team responsibilitiesSubmit code to be reviewed by the DevOps teamBe on-call for incidentsPublish the SLOs that the DevOps team must meet
C. DevOps team responsibilitiesManage the service infrastructureBe on-call for incidentsSoftware Development team responsibilitiesAdopt and publish SLOs for the serviceSubmit code to be reviewedShared responsibilities for code reviews
D. DevOps team responsibilitiesShared responsibilities for code reviewsSoftware Development team responsibilitiesManage the service infrastructureBe on-call for incidents on a rotation basisAdopt and publish SLOs for the serviceSubmit code to be reviewed

Answer: C

Explanation:
Comprehensive and Detailed Explanation:
The best approach to a joint-ownership DevOps model follows SRE and DevOps best practices, where:
The DevOps team manages infrastructure and is on-call for incidents.
The Software Development team owns SLOs and submits code.
Code reviews should be a shared responsibility to ensure both teams maintain quality.
#Why not other options?
A (DevOps team reviewing all code)## Breaks DevOps best practices by making developers dependent on the DevOps team for code review.
B (DevOps does code reviews, developers handle incidents)## Developers should not handle on-call duties unless part of a shared rotation.
C (Developers manage infrastructure)## Developers should not be fully responsible for infrastructure.
#Official Reference:
SRE & DevOps Ownership Model
Shared Responsibility Model in Google Cloud

NEW QUESTION # 170
You are running an experiment to see whether your users like a new feature of a web application. Shortly after deploying the feature as a canary release, you receive a spike in the number of 500 errors sent to users, and your monitoring reports show increased latency. You want to quickly minimize the negative impact on users. What should you do first?

A. Start monitoring latency, traffic, errors, and saturation.
B. Roll back the experimental canary release.
C. Record data for the postmortem document of the incident.
D. Trace the origin of 500 errors and the root cause of increased latency.

Answer: D

NEW QUESTION # 171
......

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