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[General] Google Professional-Cloud-DevOps-Engineer Testfagen, Professional-Cloud-DevOps-E

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【General】 Google Professional-Cloud-DevOps-Engineer Testfagen, Professional-Cloud-DevOps-E

Posted at yesterday 23:20      View：5 | Replies：0        Print      Only Author   [Copy Link] 1#
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Wir sind der Schnellste, der daa Google Professional-Cloud-DevOps-Engineer Zertifikat erhält; wir sind noch der höchste, der Ihre Interessen schützt. Wir sind EchteFrage. EchteFrage kann Ihnen versprechen, dass die Testaufgaben von Google Professional-Cloud-DevOps-Engineer Zertifizierungsprüfung 100% richtig und ganz umfassend sind. Nachdem Sie die Testfragen zur Google Professional-Cloud-DevOps-Engineer Zertifizierung gekauft haben, werden Sie kostenlos die einjährige Aktualisierung genießen.
Um sich auf die Prüfung vorzubereiten, können Kandidaten verschiedene Ressourcen nutzen, die von Google Cloud bereitgestellt werden, wie Online-Kurse, Übungsprüfungen und Lernmaterialien. Darüber hinaus können Kandidaten durch die Arbeit an Google Cloud-Projekten und die Teilnahme an Online-Foren und Communities praktische Erfahrungen sammeln.
Die Google Professional Professional-Cloud-Devops-Engineer-Zertifizierungsprüfung ist eine herausfordernde Prüfung, die ein tiefes Verständnis der DevOps-Prinzipien und -Praktiken sowie die Fähigkeit erfordert, sie in einer Cloud-Umgebung anzuwenden. Es ist eine umfassende Prüfung, die eine breite Palette von Themen abdeckt und die Kandidaten erfordert, um ihre praktischen Fähigkeiten durch praktische Übungen zu demonstrieren.
Professional-Cloud-DevOps-Engineer Fragen&Antworten - Professional-Cloud-DevOps-Engineer ZertifizierungsfragenHeutztage hat ein Fachqualifizieter große Vorteile in der heute konkurrenzfähigen Gesellschaft, besonders im IT-Bereich. Einige IT-Zertifikate zu bekommen ist sehr nützlich. Die Google Professional-Cloud-DevOps-Engineer Zertifizierungsprüfung ist eine Prüfung, die das Niveau der fachlichen Kenntnissen überprüft und stellt ein großes Gewicht in der IT-Branche dar. Wegen der Schwierigkeit der Google Professional-Cloud-DevOps-Engineer (Google Cloud Certified - Professional Cloud DevOps Engineer Exam) Zertifizierungsprüfung hat man viel Zeit und Energie für die Prüfung benutzt. Jedoch sind sie am Ende doch in der Prüfung durchgefallen. Die Gründe dafür liegt darin, dass Sie nicht an der speziellen Kursen teilnehmen. Nun haben Experten die zielgerichteten Prüfungen entwickelt, die Ihnen helden, viel Zeit und Energie zu ersparen und trotzdem die Prüfung 100% zu bestehen.
Google Cloud Certified - Professional Cloud DevOps Engineer Exam Professional-Cloud-DevOps-Engineer Prüfungsfragen mit Lösungen (Q165-Q170):165. Frage
You support a trading application written in Python and hosted on App Engine flexible environment. You want to customize the error information being sent to Stackdriver Error Reporting. What should you do?
  • A. Install the Stackdriver Error Reporting library for Python, and then run your code on a Compute Engine VM.
  • B. Install the Stackdriver Error Reporting library for Python, and then run your code on Google Kubernetes Engine.
  • C. Use the Stackdriver Error Reporting API to write errors from your application to ReportedErrorEvent, and then generate log entries with properly formatted error messages in Stackdriver Logging.
  • D. Install the Stackdriver Error Reporting library for Python, and then run your code on App Engine flexible environment.
Antwort: C

166. Frage
You support a high-traffic web application that runs on Google Cloud Platform (GCP). You need to measure application reliability from a user perspective without making any engineering changes to it. What should you do?
Choose 2 answers
  • A. Create new synthetic clients to simulate a user journey using the application.
  • B. Modify the code to capture additional information for user interaction.
  • C. Use current and historic Request Logs to trace customer interaction with the application.
  • D. Analyze the web proxy logs only and capture response time of each request.
  • E. Review current application metrics and add new ones as needed.
Antwort: A,C

167. Frage
You are creating Cloud Logging sinks to export log entries from Cloud Logging to BigQuery for future analysis Your organization has a Google Cloud folder named Dev that contains development projects and a folder named Prod that contains production projects Log entries for development projects must be exported to dev_dataset. and log entries for production projects must be exported to prod_dataset You need to minimize the number of log sinks created and you want to ensure that the log sinks apply to future projects What should you do?
  • A. Create a single aggregated log sink at the organization level.
  • B. Create a log sink in each project
  • C. Create two aggregated log sinks at the organization level, and filter by project ID
  • D. Create an aggregated Iog sink in the Dev and Prod folders
Antwort: D
Begründung:
The best option for minimizing the number of log sinks created and ensuring that the log sinks apply to future projects is to create an aggregated log sink in the Dev and Prod folders. An aggregated log sink is a log sink that collects logs from multiple sources, such as projects, folders, or organizations. By creating an aggregated log sink in each folder, you can export log entries for development projects to dev_dataset and log entries for production projects to prod_dataset. You can also use filters to specify which logs you want to export. Additionally, by creating an aggregated log sink at the folder level, you can ensure that the log sink applies to future projects that are created under that folder.

168. Frage
You need to build a CI/CD pipeline for a containerized application in Google Cloud Your development team uses a central Git repository for trunk-based development You want to run all your tests in the pipeline for any new versions of the application to improve the quality What should you do?
  • A. 1. Install a Git hook to require developers to run unit tests before pushing the code to a central repository
    2. Trigger Cloud Build to build the application container Deploy the application container to a testing environment, and run integration tests
    3. If the integration tests are successful deploy the application container to your production environment.
    and run acceptance tests
  • B. 1. Install a Git hook to require developers to run unit tests before pushing the code to a central repository If all tests are successful build a container
    2. Trigger Cloud Build to deploy the application container to a testing environment, and run integration tests and acceptance tests
    3. If all tests are successful tag the code as production ready Trigger Cloud Build to build and deploy the application container to the production environment
  • C. 1. Trigger Cloud Build to build the application container and run unit tests with the container
    2. If unit tests are successful, deploy the application container to a testing environment, and run integration tests
    3. If the integration tests are successful the pipeline deploys the application container to the production environment After that, run acceptance tests
  • D. 1. Trigger Cloud Build to run unit tests when the code is pushed If all unit tests are successful, build and push the application container to a central registry.
    2. Trigger Cloud Build to deploy the container to a testing environment, and run integration tests and acceptance tests
    3. If all tests are successful the pipeline deploys the application to the production environment and runs smoke tests
Antwort: D
Begründung:
Explanation
The best option for building a CI/CD pipeline for a containerized application in Google Cloud is to trigger Cloud Build to run unit tests when the code is pushed, if all unit tests are successful, build and push the application container to a central registry, trigger Cloud Build to deploy the container to a testing environment, and run integration tests and acceptance tests, and if all tests are successful, the pipeline deploys the application to the production environment and runs smoke tests. This option follows the best practices for CI/CD pipelines, such as running tests at different stages of the pipeline, using a central registry for storing and managing containers, deploying to different environments, and using Cloud Build as a unified tool for building, testing, and deploying.

169. Frage
Your team is designing a new application for deployment both inside and outside Google Cloud Platform (GCP). You need to collect detailed metrics such as system resource utilization. You want to use centralized GCP services while minimizing the amount of work required to set up this collection system. What should you do?
  • A. Install an Application Performance Monitoring (APM) tool in both locations, and configure an export to a central data storage location for analysis.
  • B. Instrument the code using a timing library, and publish the metrics via a health check endpoint that is scraped by Stackdriver.
  • C. Import the Stackdriver Profiler package, and configure it to relay function timing data to Stackdriver for further analysis.
  • D. Import the Stackdriver Debugger package, and configure the application to emit debug messages with timing information.
Antwort: C
Begründung:
The easiest way to collect detailed metrics such as system resource utilization is to import the Stackdriver Profiler package, and configure it to relay function timing data to Stackdriver for further analysis. This way, you can use centralized GCP services without modifying your code or setting up additional tools.

170. Frage
......
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