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| Certification Vendor: | Google Cloud |
|---|---|
| Exam Name: | Google Cloud Certified - Professional Cloud DevOps Engineer Exam |
| Exam Number: | Professional-Cloud-DevOps-Engineer |
| Passing Score: | Not publicly disclosed |
| Exam Format: | Multiple select, Multiple choice |
| Available Languages: | English, Japanese |
| Real Exam Qty: | 50-60 |
| Certificate Validity Period: | 2 years |
| Exam Price: | $200 (plus tax where applicable) |
| Exam Duration: | 120 minutes |
| Related Certifications: | Professional Cloud Architect Professional Cloud Developer Professional Cloud Network Engineer Professional Cloud Security Engineer |
| Recommended Training: | Professional Cloud DevOps Engineer Learning Path Exam Guide |
| Exam Registration: | Google Cloud Certification Registration |
| Sample Questions: | Google Professional-Cloud-DevOps-Engineer Sample Questions |
| Exam Way: | Online proctored (remote) or onsite proctored (testing center) |
| Pre Condition: | No mandatory prerequisites; recommended: 3+ years industry experience, 1+ year managing production systems on Google Cloud |
| Official Syllabus URL: | https://cloud.google.com/learn/certification/cloud-devops-engineer |
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Google Cloud Certified Professional Cloud DevOps Engineer exam is designed to test the skills and knowledge of professionals who can help organizations improve their software delivery pipelines and build reliable, scalable, and secure applications on Google Cloud Platform (GCP). Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification verifies that the candidate possesses the necessary skills to design, implement, and manage DevOps processes using GCP tools and services.
NEW QUESTION # 79
You use Spinnaker to deploy your application and have created a canary deployment stage in the pipeline. Your application has an in-memory cache that loads objects at start time. You want to automate the comparison of the canary version against the production version. How should you configure the canary analysis?
Answer: C
NEW QUESTION # 80
You recently noticed that one of your services has exceeded the error budget for the current rolling window period. Your company's product team is about to launch a new feature. You want to follow Site Reliability Engineering (SRE) practices. What should you do?
Answer: A
Explanation:
Comprehensive and Detailed Explanation:
In Google's Site Reliability Engineering (SRE) practices, an error budget defines the acceptable level of failure before new feature deployments should pause. If a service exceeds its error budget, the correct approach is to:
Notify the product team that the error budget is depleted.
Negotiate a launch freeze or decide if the team can tolerate slightly degraded performance.
#Why not other options?
A (Ensure all tests pass and proceed)## Testing cannot guarantee stability when the error budget is already depleted.
C (Request additional error budget)## Error budgets are not arbitrary; increasing them would defeat their purpose.
D (Reallocate SLOs from other areas)## Error budgets should not be mixed across different SLOs, as this breaks reliability guarantees.
#Official Reference:
Google SRE: Error Budget Policy
Google Cloud SRE Principles
NEW QUESTION # 81
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?
Answer: B
Explanation:
Explanation
https://cloud.google.com/error-reporting/docs/formatting-error-messages
https://cloud.google.com/error-reporting/docs/reference/libraries#client-libraries-install-python no need to install error reporting library on App Engine Flex.
NEW QUESTION # 82
You support a high-traffic web application with a microservice architecture. The home page of the application displays multiple widgets containing content such as the current weather, stock prices, and news headlines. The main serving thread makes a call to a dedicated microservice for each widget and then lays out the homepage for the user. The microservices occasionally fail; when that happens, the serving thread serves the homepage with some missing content. Users of the application are unhappy if this degraded mode occurs too frequently, but they would rather have some content served instead of no content at all. You want to set a Service Level Objective (SLO) to ensure that the user experience does not degrade too much. What Service Level Indicator {SLI) should you use to measure this?
Answer: B
NEW QUESTION # 83
You are implementing a CI'CD pipeline for your application in your company s multi-cloud environment Your application is deployed by using custom Compute Engine images and the equivalent in other cloud providers You need to implement a solution that will enable you to build and deploy the images to your current environment and is adaptable to future changes Which solution stack should you use'?
Answer: C
Explanation:
Explanation
Cloud Build is a fully managed continuous integration and continuous delivery (CI/CD) service that helps you automate your builds, tests, and deployments. Google Cloud Deploy is a service that automates the deployment of your applications to Google Kubernetes Engine (GKE).
Together, Cloud Build and Google Cloud Deploy can be used to build and deploy your application's custom Compute Engine images to your current environment and to other cloud providers in the future.
Here are the steps involved in using Cloud Build and Google Cloud Deploy to implement a CI/CD pipeline for your application:
Create a Cloud Build trigger that fires whenever a change is made to your application's code.
In the Cloud Build trigger, configure Cloud Build to build your application's Docker image.
Create a Google Cloud Deploy configuration file that specifies how to deploy your application's Docker image to GKE.
In Google Cloud Deploy, create a deployment that uses your configuration file.
Once you have created the Cloud Build trigger and Google Cloud Deploy configuration file, any changes made to your application's code will trigger Cloud Build to build a new Docker image. Google Cloud Deploy will then deploy the new Docker image to GKE.
This solution stack is adaptable to future changes because it uses a cloud-agnostic approach. Cloud Build can be used to build Docker images for any cloud provider, and Google Cloud Deploy can be used to deploy Docker images to any Kubernetes cluster.
The other solution stacks are not as adaptable to future changes. For example, solution stack A (Cloud Build with Packer) is limited to building Docker images for Compute Engine. Solution stack C (Google Kubernetes Engine with Google Cloud Deploy) is limited to deploying Docker images to GKE. Solution stack D (Cloud Build with kpt) is a newer solution that is not yet as mature as Cloud Build and Google Cloud Deploy.
Overall, the best solution stack for implementing a CI/CD pipeline for your application in a multi-cloud environment is Cloud Build with Google Cloud Deploy. This solution stack is fully managed, cloud-agnostic, and adaptable to future changes.
NEW QUESTION # 84
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