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To become a Google Cloud Certified Professional Cloud DevOps Engineer, candidates must pass the certification exam, which consists of multiple-choice and multiple-select questions. Professional-Cloud-DevOps-Engineer Exam covers a wide range of topics, including GCP services such as Kubernetes Engine, Cloud Functions, and Cloud Run, as well as DevOps practices such as continuous integration and delivery, monitoring and logging, and infrastructure as code. Candidates must also demonstrate their ability to troubleshoot issues and optimize performance in a GCP environment. Overall, the certification exam is a rigorous test of a candidate's skills and knowledge in deploying and managing applications on GCP, and passing it is a significant achievement for any DevOps professional.
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To qualify for the Google Professional-Cloud-DevOps-Engineer Certification Exam, candidates must have at least three years of experience working in a DevOps engineering role and a minimum of one year of experience working with Google Cloud. Candidates are also expected to have a solid understanding of software development principles and practices, as well as experience with scripting languages such as Python and Bash.
NEW QUESTION # 69
You manage an application that is writing logs to Stackdriver Logging. You need to give some team members the ability to export logs. What should you do?
Answer: B
Explanation:
https://cloud.google.com/logging/docs/access-control
NEW QUESTION # 70
You manage applications deployed on Google Kubernetes Engine (GKE) clusters across multiple Google Cloud projects. You require a centralized and scalable solution to collect and query Prometheus metrics from these clusters by using a flexible query language. You want to follow Google-recommended practices. What should you do?
Answer: B
Explanation:
Comprehensive and Detailed 150 to 200 words of Explanation From Google Cloud DevOps guides documents:
Google Cloud's recommended practice for scalable, multi-cluster monitoring is Google Cloud Managed Service for Prometheus (GMP). This service is a fully managed, multi-cloud-capable solution built on top of Monarch (the same globally scalable time-series database Google uses internally). By using managed collection, GKE clusters automatically deploy collectors that scrape metrics without the operational overhead of managing a manual Prometheus server, scaling, or long-term storage (sharding).
This solution satisfies the "centralized and scalable" requirement because GMP allows you to query data across multiple projects and clusters using PromQL, which provides the flexible query language requested.
While the Ops Agent (Option C) is useful for VM-based workloads, GMP is the purpose-built solution for Kubernetes environments. Standard sidecar deployments (Option A) or self-managed admin clusters (Option D) introduce significant administrative toil and fail to leverage the global scale and high availability of the Cloud Monitoring backend. By centralizing metrics in Metrics Explorer, SRE teams gain a unified view of system health, making it easier to define SLOs and manage incidents across a complex microservices landscape.
NEW QUESTION # 71
You manage an application that runs in Google Kubernetes Engine (GKE) and uses the blue/green deployment methodology Extracts of the Kubernetes manifests are shown below
The Deployment app-green was updated to use the new version of the application During post-deployment monitoring you notice that the majority of user requests are failing You did not observe this behavior in the testing environment You need to mitigate the incident impact on users and enable the developers to troubleshoot the issue What should you do?
Answer: B
Explanation:
The best option for mitigating the incident impact on users and enabling the developers to troubleshoot the issue is to change the selector on the Service app-svc to app: my-app, version: blue. A Service is a resource that defines how to access a set of Pods. A selector is a field that specifies which Pods are selected by the Service. By changing the selector on the Service app-svc to app: my-app, version: blue, you can ensure that the Service only routes traffic to the Pods that have both labels app: my-app and version: blue. These Pods belong to the Deployment app-blue, which uses the previous version of the application. This way, you can mitigate the incident impact on users by switching back to the working version of the application. You can also enable the developers to troubleshoot the issue with the new version of the application in the Deployment app-green without affecting users.
NEW QUESTION # 72
Your application runs on Google Cloud Platform (GCP). You need to implement Jenkins for deploying application releases to GCP. You want to streamline the release process, lower operational toil, and keep user data secure. What should you do?
Answer: C
NEW QUESTION # 73
You are reviewing your deployment pipeline in Google Cloud Deploy You must reduce toil in the pipeline and you want to minimize the amount of time it takes to complete an end-to-end deployment What should you do?
Choose 2 answers
Answer: C,D
Explanation:
The best options for reducing toil in the pipeline and minimizing the amount of time it takes to complete an end-to-end deployment are to create a trigger to notify the required team to complete the next step when manual intervention is required and to automate promotion approvals from the development environment to the test environment. A trigger is a resource that initiates a deployment when an event occurs, such as a code change, a schedule, or a manual request. You can create a trigger to notify the required team to complete the next step when manual intervention is required by using Cloud Build or Cloud Functions. This way, you can reduce the waiting time and human errors in the pipeline. A promotion approval is a process that allows you to approve or reject a deployment from one environment to another, such as from development to test. You can automate promotion approvals from the development environment to the test environment by using Google Cloud Deploy or Cloud Build. This way, you can speed up the deployment process and avoid manual steps.
NEW QUESTION # 74
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