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Exam Topics
To achieve good results in the Google Professional Cloud DevOps Engineer certification exam, the candidates need to develop a comprehensive understanding of its domains. The detailed outline of the topics and subtopics covered in the test is available on the official platform. Their brief overview is provided below:
- Optimization of Service Performance
Within this module, the learners need to show that they are capable of optimizing resource utilization, including determining resource costs, defining resource utilization levels, developing a plan to optimize areas of the lowest utilization/greatest cost, managing preemptible Virtual Machines, considering network pricing, and so on. They must also possess the skills in debugging application code as well as determining service performance issues.
- Management of Service Incidents
To answer the questions related to this part of the certification test, the students need to have the skills in coordinating roles and implementing the channels of communication in the course of the service incident. In addition, they need to have an understanding of how to perform the analysis of incident symptoms affecting the users. The test takers should also know how to mitigate the impact of an incident on the users. Finally, they need to have the sufficient competency in resolving issues (for example, Cloud Build, Jenkins, etc.) and documenting an issue in the postmortem.
- Building & Implementation of CI/CD Pipelines for Services
The second topic focuses on the ability of the examinees to manage various development environments (for instance, staging, production, etc.), manage infrastructure as code, as well as manage configuration & secrets. Moreover, the test takers are required to demonstrate their proficiency in designing & implementing CI/CD pipelines, deploying CI/CD tooling, and securing the deployment pipeline.
- Application of Site Reliability Engineering Principles to Services
This subject area measures the skills of the professionals in ensuring healthy collaboration for operations, including preventing burnout (for example, setting up automation procedures to prevent burnout) as well as fostering a learning culture & culture of blamelessness. Besides that, the candidates need to possess the expertise in managing the service life cycle as well as balancing the service change, velocity, and reliability.
- Implementation of Strategies for Service Monitoring
Here the applicants will be asked to show that they have the capacity to manage the Stackdriver Logging and Stackdriver Monitoring platforms. They should also know how to manage application logs as well as application metrics using Stackdriver Monitoring. Additionally, the individuals will require the competency in implementing logging & monitoring access control.
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The Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam tests the candidate's knowledge of DevOps principles, practices, and tools, as well as their ability to apply these concepts on the Google Cloud Platform. Professional-Cloud-DevOps-Engineer Exam covers a wide range of topics, including continuous integration and delivery, infrastructure automation, monitoring and logging, security and compliance, and collaboration and communication.
Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q26-Q31):
NEW QUESTION # 26
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. logwriter and monitoring. editor roles to the Compute Engine service accounts.
- B. Grant the logging. logWriter and monitoring. metricWriter roles to the Compute Engine service accounts.
- C. Grant the Logging. admin and monitoring . editor roles to the Compute Engine service accounts.
- D. Grant the logging.editor and monitoring.metricwriter roles to the Compute Engine service accounts.
Answer: B
Explanation:
Explanation
The correct answer is D. Grant the logging.logWriter and monitoring.metricWriter roles to the Compute Engine service accounts.
According to the Google Cloud documentation, the Compute Engine service account is a Google-managed service account that is automatically created when you enable the Compute Engine API1. This service account is used by default to run your Compute Engine instances and access other Google Cloud services on your behalf1. To ensure that monitoring metrics and logs for the instances are visible in Cloud Logging and Cloud Monitoring, you need to grant the following IAM roles to the Compute Engine service account23:
The logging.logWriter role allows the service account to write log entries to Cloud Logging4.
The monitoring.metricWriter role allows the service account to write custom metrics to Cloud Monitoring5.
These roles grant the minimum permissions that are needed for logging and monitoring, following the principle of least privilege. The other roles are either unnecessary or too broad for this purpose. For example, the logging.editor role grants permissions to create and update logs, log sinks, and log exclusions, which are not required for writing log entries6. The logging.admin role grants permissions to delete logs, log sinks, and log exclusions, which are not required for writing log entries and may pose a security risk if misused. The monitoring.editor role grants permissions to create and update alerting policies, uptime checks, notification channels, dashboards, and groups, which are not required for writing custom metrics.
NEW QUESTION # 27
Your team uses Cloud Build for all CI/CO pipelines. You want to use the kubectl builder for Cloud Build to deploy new images to Google Kubernetes Engine (GKE). You need to authenticate to GKE while minimizing development effort. What should you do?
- A. Specify the Container Developer role for Cloud Build in the cloudbuild.yaml file.
- B. Create a new service account with the Container Developer role and use it to run Cloud Build.
- C. Assign the Container Developer role to the Cloud Build service account.
- D. Create a separate step in Cloud Build to retrieve service account credentials and pass these to kubectl.
Answer: C
NEW QUESTION # 28
Your team is designing a new application for deployment into Google Kubernetes Engine (GKE). You need to set up monitoring to collect and aggregate various application-level metrics in a centralized location. You want to use Google Cloud Platform services while minimizing the amount of work required to set up monitoring. What should you do?
- A. Install the OpenTelemetry client libraries in the application, configure Stackdriver as the export destination for the metrics, and then observe the application's metrics in Stackdriver.
- B. Emit all metrics in the form of application-specific log messages, pass these messages from the containers to the Stackdriver logging collector, and then observe metrics in Stackdriver.
- C. Install the Cloud Pub/Sub client libraries, push various metrics from the application to various topics, and then observe the aggregated metrics in Stackdriver.
- D. Publish various metrics from the application directly to the Slackdriver Monitoring API, and then observe these custom metrics in Stackdriver.
Answer: D
Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/custom-and-external-metrics#custom_metrics
https://github.com/GoogleCloudPlatform/k8s-stackdriver/blob/master/custom-metrics-stackdriver-adapter/README.md Your application can report a custom metric to Cloud Monitoring. You can configure Kubernetes to respond to these metrics and scale your workload automatically. For example, you can scale your application based on metrics such as queries per second, writes per second, network performance, latency when communicating with a different application, or other metrics that make sense for your workload. https://cloud.google.com/kubernetes-engine/docs/concepts/custom-and-external-metrics
NEW QUESTION # 29
You are configuring a Cl pipeline. The build step for your Cl pipeline integration testing requires access to APIs inside your private VPC network. Your security team requires that you do not expose API traffic publicly. You need to implement a solution that minimizes management overhead. What should you do?
- A. Use Spinnaker for Google Cloud to connect to the private VPC.
- B. Use Cloud Build as a pipeline runner. Configure External HTTP(S) Load Balancing with a Google Cloud Armor policy for API access.
- C. Use Cloud Build private pools to connect to the private VPC.
- D. Use Cloud Build as a pipeline runner. Configure Internal HTTP(S) Load Balancing for API access.
Answer: C
Explanation:
Explanation
Cloud Build is a service that executes your builds on Google Cloud Platform infrastructure1. Cloud Build can be used as a pipeline runner for your CI pipeline, which is a process that automates the integration and testing of your code2. Cloud Build private pools are private, dedicated pools of workers that offer greater customization over the build environment, including the ability to access resources in a private VPC network3.
A VPC network is a virtual network that provides connectivity for your Google Cloud resources and services. By using Cloud Build private pools, you can implement a solution that minimizes management overhead, as Cloud Build private pools are hosted and fully-managed by Cloud Build and scale up and down to zero, with no infrastructure to set up, upgrade, or scale3. You can also implement a solution that meets your security requirement, as Cloud Build private pools use network peering to connect into your private VPC network and do not expose API traffic publicly.
NEW QUESTION # 30
You use Cloud Build to build and deploy your application. You want to securely incorporate database credentials and other application secrets into the build pipeline. You also want to minimize the development effort. What should you do?
- A. Create a Cloud Storage bucket and use the built-in encryption at rest. Store the secrets in the bucket and grant Cloud Build access to the bucket.
- B. Use client-side encryption to encrypt the secrets and store them in a Cloud Storage bucket. Store a decryption key in the bucket and grant Cloud Build access to the bucket.
- C. Encrypt the secrets and store them in the application repository. Store a decryption key in a separate repository and grant Cloud Build access to the repository.
- D. Use Cloud Key Management Service (Cloud KMS) to encrypt the secrets and include them in your Cloud Build deployment configuration. Grant Cloud Build access to the KeyRing.
Answer: D
Explanation:
https://cloud.google.com/build/docs/securing-builds/use-encrypted-credentials
NEW QUESTION # 31
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