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| Certification Vendor: | Google Cloud |
|---|---|
| Exam Name: | Google Cloud Certified - Professional Cloud DevOps Engineer |
| Exam Number: | Professional-Cloud-DevOps-Engineer |
| Exam Duration: | 120 minutes |
| Real Exam Qty: | Approximately 50–60 |
| Available Languages: | English, Portuguese (Brazil), Spanish, Japanese |
| Exam Price: | $200 USD |
| Certificate Validity Period: | 2 years |
| Exam Format: | Multiple select, Multiple choice |
| Passing Score: | Not officially disclosed |
| Related Certifications: | Google Cloud Certified - Professional Cloud Security Engineer Google Cloud Certified - Professional Cloud Network Engineer Google Cloud Certified - Professional Cloud Architect Google Cloud Certified - Associate Cloud Engineer |
| Recommended Training: | Google Cloud Skills Boost - DevOps Engineer Path Coursera Google Cloud DevOps Engineering Courses |
| Exam Registration: | Google Cloud Certification Portal Kryterion Webassessor Registration |
| Sample Questions: | Google Professional-Cloud-DevOps-Engineer Sample Questions |
| Exam Way: | Online proctored or test center (Kryterion/Webassessor) |
| Pre Condition: | No formal prerequisites. Recommended: 3+ years of industry experience including 1+ years designing and managing solutions using Google Cloud. |
| Official Syllabus URL: | https://cloud.google.com/certification/cloud-devops-engineer |
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The Professional-Cloud-DevOps-Engineer Certification Exam measures the candidate's ability to manage and monitor the entire software delivery pipeline, from continuous integration and deployment to delivery and monitoring. Professional-Cloud-DevOps-Engineer exam also tests the candidate's knowledge of automation tools and techniques, as well as their ability to analyze and optimize the cloud infrastructure for better performance and cost-effectiveness.
NEW QUESTION # 58
Your company is developing applications that are deployed on Google Kubernetes Engine (GKE) Each team manages a different application You need to create the development and production environments for each team while you minimize costs Different teams should not be able to access other teams environments You want to follow Google-recommended practices What should you do?
Answer: D
Explanation:
The best option for creating the development and production environments for each team while minimizing costs and ensuring isolation is to create a development and a production GKE cluster in separate projects, in each cluster create a Kubernetes namespace per team, and then configure Kubernetes role-based access control (RBAC) so that each team can only access its own namespace. This option allows you to use fewer clusters and projects than creating one project or cluster per team, which reduces costs and complexity. It also allows you to isolate each team's environment by using namespaces and RBAC, which prevents teams from accessing other teams' environments.
NEW QUESTION # 59
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?
Answer: B
NEW QUESTION # 60
You support a multi-region web service running on Google Kubernetes Engine (GKE) behind a Global HTTP'S Cloud Load Balancer (CLB). For legacy reasons, user requests first go through a third-party Content Delivery Network (CDN). which then routes traffic to the CLB. You have already implemented an availability Service Level Indicator (SLI) at the CLB level. However, you want to increase coverage in case of a potential load balancer misconfiguration. CDN failure, or other global networking catastrophe. Where should you measure this new SLI?
Choose 2 answers
Answer: A,B
NEW QUESTION # 61
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?
Answer: C
Explanation:
The correct answer is D. Option D.
According to the DevOps best practices, a joint-ownership model for a service between the DevOps team and the Software Development team should follow these principles12:
The DevOps team and the Software Development team should share the responsibility and collaboration for managing the service infrastructure, performing code reviews, and adopting and sharing SLOs for the service.
The DevOps team and the Software Development team should have end-to-end ownership of the service, from design to development to deployment to operation to maintenance.
The DevOps team and the Software Development team should use common tools and processes to facilitate communication, coordination, and feedback.
The DevOps team and the Software Development team should align their goals and incentives with the business outcomes and customer satisfaction.
Option D is the only option that reflects these principles. Option D assigns both teams the responsibilities of managing the service infrastructure, performing code reviews, and adopting and sharing SLOs for the service.
Option D also implies that both teams have end-to-end ownership of the service, as they are involved in every stage of the service lifecycle.Option D also encourages both teams to use common tools and processes, such as GitLab3, to collaborate and communicate effectively. Option D also aligns both teams with the business outcomes and customer satisfaction, as they use SLOs to measure and improve the service quality.
The other options are incorrect because they do not follow the DevOps best practices. Option A is incorrect because it assigns only the DevOps team the responsibility of managing the service infrastructure, which creates a silo between the two teams and reduces their collaboration. Option A also does not assign any responsibility for adopting and sharing SLOs for the service, which means that both teams lack a common metric for measuring and improving the service quality. Option B is incorrect because it assigns only the Software Development team the responsibility of performing code reviews, which creates a gap between the two teams and reduces their feedback. Option B also does not assign any responsibility for adopting and sharing SLOs for the service, which means that both teams lack a common metric for measuring and improving the service quality. Option C is incorrect because it assigns both teams the same responsibilities as option A and option B, which combines their drawbacks.
Reference:
5 key organizational models for DevOps teams | GitLab, 5 key organizational models for DevOps teams | GitLab.Building a Culture of Full-Service Ownership - DevOps.com, Building a Culture of Full-Service Ownership - DevOps.com.GitLab, GitLab.
NEW QUESTION # 62
Your company runs services by using multiple globally distributed Google Kubernetes Engine (GKE) clusters Your operations team has set up workload monitoring that uses Prometheus-based tooling for metrics alerts:
and generating dashboards This setup does not provide a method to view metrics globally across all clusters You need to implement a scalable solution to support global Prometheus querying and minimize management overhead What should you do?
Answer: A
Explanation:
Explanation
The best option for implementing a scalable solution to support global Prometheus querying and minimize management overhead is to use Google Cloud Managed Service for Prometheus. Google Cloud Managed Service for Prometheus is a fully managed service that allows you to collect, query, and visualize metrics from your GKE clusters using Prometheus-based tooling. You can use Google Cloud Managed Service for Prometheus to query metrics across multiple clusters and regions using a global view. You can also use Google Cloud Managed Service for Prometheus to integrate with other Google Cloud services, such as Cloud Monitoring, Cloud Logging, and BigQuery. By using Google Cloud Managed Service for Prometheus, you can avoid managing and scaling your own Prometheus servers and focus on your application performance.
NEW QUESTION # 63
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