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Updated Google Professional-Cloud-DevOps-Engineer Testkings & Latest Profess
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You may want to own a Professional-Cloud-DevOps-Engineer certificate to prove that you are competent and boost excellent practical abilities in some certain area. Thus you will be regarded as the capable people and be respected. Passing the test Professional-Cloud-DevOps-Engineer certification can help you realize your goals and if you buy our Professional-Cloud-DevOps-Engineer Guide Torrent you will pass the Professional-Cloud-DevOps-Engineer exam easily. Our Professional-Cloud-DevOps-Engineer exam questions are written by the most professional experts, so the quality of our Professional-Cloud-DevOps-Engineer learning material is wonderful. And we always keep our Professional-Cloud-DevOps-Engineer study guide the most updated for you to pass the exam.
Google Professional-Cloud-DevOps-Engineer Certification Exam is a highly sought-after certification that is designed for IT professionals who want to demonstrate their skills in managing and deploying applications on Google Cloud Platform (GCP). Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification validates the skills and knowledge of individuals in various areas of cloud computing, including DevOps practices, infrastructure automation, continuous delivery, and monitoring and logging.
Latest Google Professional-Cloud-DevOps-Engineer Exam Tips | Professional-Cloud-DevOps-Engineer Pass RateThe Google Professional-Cloud-DevOps-Engineer certification exam offers a great opportunity for Google professionals to demonstrate their expertise and knowledge level. In return, they can become competitive and updated with the latest technologies and trends. To do this they just need to enroll in Google Cloud Certified - Professional Cloud DevOps Engineer Exam (Professional-Cloud-DevOps-Engineer) certification exam and have to put all efforts and resources to pass this challenging Professional-Cloud-DevOps-Engineer exam. You should also keep in mind that to get success in the Google Professional-Cloud-DevOps-Engineer exam is not an easy task.
Google Professional-Cloud-DevOps-Engineer certification is ideal for professionals who work in DevOps roles and are proficient in using GCP to build and deploy applications. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is also suitable for professionals who want to enhance their skills and advance their careers in the DevOps field. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is recognized globally and is highly valued by employers, making it an excellent investment for IT professionals who want to stay ahead of the competition.
Google Professional-Cloud-DevOps-Engineer Exam is a performance-based exam that evaluates the candidate's practical skills in the real-world scenario. Professional-Cloud-DevOps-Engineer exam is conducted online, and the candidates are required to complete a set of tasks within a given time frame. Professional-Cloud-DevOps-Engineer exam is divided into two parts - a scenario-based section and a hands-on section. The scenario-based section tests the candidate's ability to analyze and solve complex problems, while the hands-on section evaluates the candidate's skills in implementing and managing GCP solutions.
Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q173-Q178):NEW QUESTION # 173
You support an e-commerce application that runs on a large Google Kubernetes Engine (GKE) cluster deployed on-premises and on Google Cloud Platform. The application consists of microservices that run in containers. You want to identify containers that are using the most CPU and memory. What should you do?
- A. Use the Stackdriver Monitoring API to create custom metrics, and then organize your containers using groups.
- B. Use Stackdriver Kubernetes Engine Monitoring.
- C. Use Prometheus to collect and aggregate logs per container, and then analyze the results in Grafana.
- D. Use Stackdriver Logging to export application logs to BigOuery. aggregate logs per container, and then analyze CPU and memory consumption.
Answer: B
Explanation:
https://cloud.google.com/anthos/ ... ging-and-monitoring
NEW QUESTION # 174
You are working with a government agency that requires you to archive application logs for seven years. You need to configure Stackdriver to export and store the logs while minimizing costs of storage. What should you do?
- A. Create an export in Stackdriver and configure Cloud Pub/Sub to store logs in permanent storage for seven years.
- B. Create a Cloud Storage bucket and develop your application to send logs directly to the bucket.
- C. Create a sink in Stackdriver, name it, create a bucket on Cloud Storage for storing archived logs, and then select the bucket as the log export destination.
- D. Develop an App Engine application that pulls the logs from Stackdriver and saves them in BigQuery.
Answer: C
Explanation:
https://cloud.google.com/logging/docs/routing/overview
NEW QUESTION # 175
You are performing a semiannual capacity planning exercise for your flagship service. You expect a service user growth rate of 10% month-over-month over the next six months. Your service is fully containerized and runs on Google Cloud Platform (GCP). using a Google Kubernetes Engine (GKE) Standard regional cluster on three zones with cluster autoscaler enabled. You currently consume about 30% of your total deployed CPU capacity, and you require resilience against the failure of a zone. You want to ensure that your users experience minimal negative impact as a result of this growth or as a result of zone failure, while avoiding unnecessary costs. How should you prepare to handle the predicted growth?
- A. Because you are at only 30% utilization, you have significant headroom and you won't need to add any additional capacity for this rate of growth.
- B. Proactively add 60% more node capacity to account for six months of 10% growth rate, and then perform a load test to make sure you have enough capacity.
- C. Because you are deployed on GKE and are using a cluster autoscaler. your GKE cluster will scale automatically, regardless of growth rate.
- D. Verity the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verity your expected resource needs.
Answer: D
Explanation:
Explanation
https://cloud.google.com/kuberne ... zontalpodautoscaler The Horizontal Pod Autoscaler changes the shape of your Kubernetes workload by automatically increasing or decreasing the number of Pods in response to the workload's CPU or memory consumption
NEW QUESTION # 176
You are designing a system with three different environments: development, quality assurance (QA), and production.
Each environment will be deployed with Terraform and has a Google Kubemetes Engine (GKE) cluster created so that application teams can deploy their applications. Anthos Config Management will be used and templated to deploy infrastructure level resources in each GKE cluster. All users (for example, infrastructure operators and application owners) will use GitOps. How should you structure your source control repositories for both Infrastructure as Code (laC) and application code?
- A. Cloud Infrastructure (Terraform) repositories are separated: different branches are different environmentsGKE Infrastructure (Anthos Config Management Kustomize manifests) repositories are separated:different overlay directories are different environmentsApplication (app source code) repositories are separated: different branches are different features
- B. Cloud Infrastructure (Terraform) repository is shared: different directories are different environmentsGKE Infrastructure (Anthos Config Management Kustomize manifests) repository is shared: differentoverlay directories are different environmentsApplication (app source code) repositories are separated: different branches are different features
- C. Cloud Infrastructure (Terraform) repository is shared: different branches are different environmentsGKE Infrastructure (Anthos Config Management Kustomize manifests) repository is shared: differentoverlay directories are different environmentsApplication (app source code) repository is shared: different directories are different features
- D. Cloud Infrastructure (Terraform) repository is shared: different directories are different environmentsGKE Infrastructure (Anthos Config Management Kustomize manifests) repositories are separated:different branches are different environmentsApplication (app source code) repositories are separated: different branches are different features
Answer: D
NEW QUESTION # 177
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. Enable the default service account key. and download the key
- B. Disable the service account key creation policy at the project's folder, and download the default key
- C. Add a rule to set the iam.disableServiceAccountKeyCreation policy to off in your project and create a key.
- D. Remove the iam.disableServiceAccountKeyCreation policy at the organization level, and create a key.
Answer: C
NEW QUESTION # 178
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