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100% Pass Google - Professional-Cloud-DevOps-Engineer - High Pass-Rate Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions

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Domains Tested in Final Evaluation

The candidates who succeed in passing the Google Professional Cloud DevOps Engineer validation will add an international designation under their belt that helps them consolidate their position in the company and receive generous offers from their employers. So, if applicants want to differentiate themselves from other colleagues, they should demonstrate the following skills:

Identifying issues related to service performance and implementing solutions to optimize it;
Coordinating teams to identify and manage incidents related to service development.
Identifying the most effective principles related to site reliability engineering and applying them to a definite service;
Checking and implementing strategies related to service monitoring;
Implementing and building CI/CD service pipelines;

To be eligible to take the Professional-Cloud-DevOps-Engineer Certification Exam, candidates must have at least three years of experience in software development, DevOps, or system administration. They must also have experience using Google Cloud Platform services and be proficient in at least one programming language.

Google Professional-Cloud-DevOps-Engineer (Google Cloud Certified - Professional Cloud DevOps Engineer) Certification Exam is designed to test the technical skills and knowledge of professionals who work with Google Cloud Platform (GCP) and are responsible for designing, building, and managing highly scalable, highly available, and highly reliable cloud-native applications using DevOps principles and practices. Professional-Cloud-DevOps-Engineer exam measures the candidate's ability to manage and automate workflows, deploy applications, monitor and optimize application performance, and implement security measures using GCP tools and services.

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q114-Q119):

NEW QUESTION # 114
You have a set of applications running on a Google Kubernetes Engine (GKE) cluster, and you are using Stackdriver Kubernetes Engine Monitoring. You are bringing a new containerized application required by your company into production. This application is written by a third party and cannot be modified or reconfigured. The application writes its log information to /var/log/app_messages.log, and you want to send these log entries to Stackdriver Logging. What should you do?

A. Deploy a Fluentd daemonset to GKE. Then create a customized input and output configuration to tail the log file in the application's pods and write to Slackdriver Logging.
B. Install Kubernetes on Google Compute Engine (GCE> and redeploy your applications. Then customize the built-in Stackdriver Logging configuration to tail the log file in the application's pods and write to Stackdriver Logging.
C. Use the default Stackdriver Kubernetes Engine Monitoring agent configuration.
D. Write a script to tail the log file within the pod and write entries to standard output. Run the script as a sidecar container with the application's pod. Configure a shared volume between the containers to allow the script to have read access to /var/log in the application container.

Answer: A

NEW QUESTION # 115
A third-party application needs to have a service account key to work properly When you try to export the key from your cloud project you receive an error "The organization policy constraint larn.disableServiceAccountKeyCreation is enforcedM You need to make the third-party application work while following Google-recommended security practices What should you do?

A. Add a rule to set the iam.disableServiceAccountKeyCreation policy to off in your project and create a key.
B. Enable the default service account key. and download the key
C. Disable the service account key creation policy at the project's folder, and download the default key
D. Remove the iam.disableServiceAccountKeyCreation policy at the organization level, and create a key.

Answer: A

Explanation:
The best option for making the third-party application work while following Google-recommended security practices is to add a rule to set the iam.disableServiceAccountKeyCreation policy to off in your project and create a key. The iam.disableServiceAccountKeyCreation policy is an organization policy that controls whether service account keys can be created in a project or organization. By default, this policy is set to on, which means that service account keys cannot be created. However, you can override this policy at a lower level, such as a project, by adding a rule to set it to off. This way, you can create a service account key for your project without affecting other projects or organizations. You should also follow the best practices for managing service account keys, such as rotating them regularly, storing them securely, and deleting them when they are no longer needed.

NEW QUESTION # 116
You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (Pll) is leaking into certain log entry fields. All Pll entries begin with the text userinfo. You want to capture these log entries in a secure location for later review and prevent them from leaking to Stackdriver Logging. What should you do?

A. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, create an advanced log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
B. Create an advanced log filter matching userinfo, configure a log export in the Stackdriver console with Cloud Storage as a sink, and then configure a tog exclusion with userinfo as a filter.
C. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, and then copy the entries to a Cloud Storage bucket.
D. Create a basic log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.

Answer: D

NEW QUESTION # 117
Your product is currently deployed in three Google Cloud Platform (GCP) zones with your users divided between the zones. You can fail over from one zone to another, but it causes a 10-minute service disruption for the affected users. You typically experience a database failure once per quarter and can detect it within five minutes. You are cataloging the reliability risks of a new real-time chat feature for your product. You catalog the following information for each risk:
* Mean Time to Detect (MUD} in minutes
* Mean Time to Repair (MTTR) in minutes
* Mean Time Between Failure (MTBF) in days
* User Impact Percentage
The chat feature requires a new database system that takes twice as long to successfully fail over between zones. You want to account for the risk of the new database failing in one zone. What would be the values for the risk of database failover with the new system?

A. MTTD:5
MTTR: 20
MTBF: 90
Impact: 33%
B. MTTD: 5
MTTR: 10
MTBF: 90
Impact: 33%
C. MTTD:5
MTTR: 10
MTBF: 90
Impact 50%
D. MTTD:5
MTTR: 20
MTBF: 90
Impact: 50%

Answer: B

NEW QUESTION # 118
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 trigger a Spinnaker pipeline.
C. Use a custom builder in Cloud Build to trigger a Jenkins pipeline.
D. Use Cloud Build to trigger a Spinnaker pipeline.

Answer: A

NEW QUESTION # 119
......

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Max Ford Max Ford

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