Google Professional-Cloud-DevOps-Engineer日本語版と英語版 & Professional-Cloud-DevOps-Engineerトレーリング学習

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Google Professional-Cloud-DevOps-Engineer Exam Overview:

Certification Vendor:	Google Cloud
Exam Name:	Google Cloud Certified - Professional Cloud DevOps Engineer Exam
Exam Number:	Professional-Cloud-DevOps-Engineer
Available Languages:	English, Portuguese, Spanish, Japanese
Passing Score:	70%
Real Exam Qty:	50
Exam Duration:	120 minutes
Exam Format:	Multiple Select, Multiple Choice
Exam Price:	$200 USD
Related Certifications:	Google Cloud Associate Cloud Engineer Google Cloud Professional Cloud Developer Google Cloud Professional Cloud Architect
Certificate Validity Period:	2 years
Sample Questions:	Google Professional-Cloud-DevOps-Engineer Sample Questions
Exam Way:	Online proctored exam available through Pearson VUE or online proctoring. In-person testing at Kryterion test centers also available.
Pre Condition:	Recommended: Associate Cloud Engineer certification and 3+ years industry experience including 1+ years Google Cloud experience. No mandatory prerequisites required.
Official Syllabus URL:	https://cloud.google.com/certification/cloud-devops-engineer

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Professional-Cloud-DevOps-Engineerトレーリング学習 & Professional-Cloud-DevOps-Engineer資格試験

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GoogleのProfessional-Cloud-DevOps-Engineer認定試験は、クラウドDevOpsエンジニアリングの候補者のスキルと知識を厳密かつ包括的に評価する試験です。クラウドインフラストラクチャの自動化、コンテナ化、CI/CDパイプライン、モニタリングとログ、セキュリティとコンプライアンスなど、幅広いトピックをカバーしています。この試験は、現代の組織のニーズに適合するクラウドベースのDevOpsソリューションを設計、実装、管理する能力をテストするために設計されています。

Google Professional-Cloud-DevOps-Engineer 認定試験の出題範囲：

トピック	出題範囲
トピック 1	Implementing service monitoring strategies: This topic covers structured and unstructured logs from Compute Engine, GKE, and serverless platforms using Cloud Logging. Its sub-topics include coverage of metrics with Cloud Monitoring, dashboards and alerts in Cloud Monitoring, Cloud Logging platform, and logging and monitoring access controls.
トピック 2	Building and implementing CI CD pipelines for a service: Management and designing of CI CD pipelines, implementation of CI CD pipelines, management of CI CD configuration, and secrets are discussed in this paper. Moreover, it focuses on storage methods and key rotation services, and finally securing the CI CD deployment pipeline.
トピック 3	Applying site reliability engineering practices to a service: It deals with velocity, and reliability of the service, service lifecycle, healthy communication, and collaboration for operations. The topic also discusses mitigation of incident impact on users and conducting a postmortem.
トピック 4	Bootstrapping a Google Cloud organization for DevOps: It discusses the overall resource hierarchy for an organization, infrastructure as code, CI CD architecture stack in Google Cloud, hybrid, and multi-cloud environments. Moreover, the topic focuses on multiple environments including staging and production.
トピック 5	Optimizing the service performance: It delves into the identification of service performance issues, implementation of debugging tools in Google Cloud, and optimization of resource utilization and costs.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam 認定 Professional-Cloud-DevOps-Engineer 試験問題 (Q116-Q121):

質問 # 116
Your team is building a service that performs compute-heavy processing on batches of data The data is processed faster based on the speed and number of CPUs on the machine These batches of data vary in size and may arrive at any time from multiple third-party sources You need to ensure that third partiesare able to upload their data securely. You want to minimize costs while ensuring that the data is processed as quickly as possible What should you do?

A. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provideappropriate Identity and Access Management (1AM) access to the bucket* Use a standard Google Kubernetes Engine (GKE) cluster and maintain two services one that processes the batches of data and one that monitors Cloud Storage for new batches of data* Stop the processing service when there are no batches of data to process
B. * Provide a secure file transfer protocol (SFTP) server on a Compute Engine instance so that thirdparties can upload batches of data and provide appropriate credentials to the server* Create a Cloud Function with a google.storage, object, finalize Cloud Storage trigger Write code so that the function can scale up a Compute Engine autoscaling managed instance group* Use an image pre-loaded with the data processing software that terminates the instances when processing completes
C. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provide appropriate identity and Access Management (1AM) access to the bucket* Create a Cloud Function with a google, storage, object .finalise Cloud Storage trigger Write code so that the function can scale up a Compute Engine autoscaling managed instance group* Use an image pre-loaded with the data processing software that terminates the instances when processing completes
D. * Provide a Cloud Storage bucket so that third parties can upload batches of data, and provideappropriate Identity and Access Management (1AM) access to the bucket* Use Cloud Monitoring to detect new batches of data in the bucket and trigger a Cloud Function that processes the data* Set a Cloud Function to use the largest CPU possible to minimize the runtime of the processing

正解：C

質問 # 117
You support a high-traffic web application and want to ensure that the home page loads in a timely manner. As a first step, you decide to implement a Service Level Indicator (SLI) to represent home page request latency with an acceptable page load time set to 100 ms. What is the Google-recommended way of calculating this SLI?

A. Count the number of home page requests that load in under 100 ms. and then divide by the total number of all web application requests.
B. Bucketize the request latencies into ranges, and then compute the median and 90th percentiles.
C. Buckelize Ihe request latencies into ranges, and then compute the percentile at 100 ms.
D. Count the number of home page requests that load in under 100 ms, and then divide by the total number of home page requests.

正解：D

解説：
Explanation
https://sre.google/workbook/implementing-slos/
In the SRE principles book, it's recommended treating the SLI as the ratio of two numbers: the number of good events divided by the total number of events. For example: Number of successful HTTP requests / total HTTP requests (success rate)

質問 # 118
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?

A. Option A
B. Option B
C. Option C
D. Option D

正解：D

解説：
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.

質問 # 119
You have deployed a fleet Of Compute Engine instances in Google Cloud. You need to ensure that monitoring metrics and logs for the instances are visible in Cloud Logging and Cloud Monitoring by your company's operations and cyber security teams. You need to grant the required roles for the Compute Engine service account by using Identity and Access Management (IAM) while following the principle of least privilege. What should you do?

A. Grant the logging.editor and monitoring.metricwriter roles to the Compute Engine service accounts.
B. Grant the Logging. admin and monitoring . editor roles to the Compute Engine service accounts.
C. Grant the logging. logwriter and monitoring. editor roles to the Compute Engine service accounts.
D. Grant the logging. logWriter and monitoring. metricWriter roles to the Compute Engine service accounts.

正解：A

質問 # 120
Your company runs applications in Google Kubernetes Engine (GKE). Several applications rely on ephemeral volumes. You noticed some applications were unstable due to the DiskPressure node condition on the worker nodes. You need to identify which Pods are causing the issue, but you do not have execute access to workloads and nodes.
What should you do?

A. Check the node/ephemeral_storage/used_bytes metric by using Metrics Explorer.
B. Check the metric by using Metrics Explorer.
C. Locate all the Pods with emptyDir volumes. Use the du -sh * command to measure volume disk usage.
D. Locate all the Pods with emptyDir volumes. use the df-h command to measure volume disk usage.

正解：A

解説：
The correct answer is A. Check the node/ephemeral_storage/used_bytes metric by using Metrics Explorer.
The node/ephemeral_storage/used_bytes metric reports the total amount of ephemeral storage used by Pods on each node1.You can use Metrics Explorer to query and visualize this metric and filter it by node name, namespace, or Pod name2. This way, you can identify which Pods are consuming the most ephemeral storage and causing disk pressure on the nodes. You do not need to have execute access to the workloads or nodes to use Metrics Explorer.
The other options are incorrect because they require execute access to the workloads or nodes, which you do not have.The df -h and du -sh * commands are Linux commands that can measure disk usage, but you need to run them inside the Pods or on the nodes, which is not possible in your scenario34.

質問 # 121
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