Professional-Cloud-DevOps-Engineer Practice Guide Materials: Google Cloud Certified - Professional Cloud DevOps Engineer Exam and Professional-Cloud-DevOps-Engineer Study Torrent - VCEEngine

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Google Professional-Cloud-DevOps-Engineer Exam Syllabus Topics:

Section	Weight	Objectives
Optimizing performance and cost	17%	- Balance cost, performance, and reliability 1. Optimize over time 2. Make tradeoff decisions based on data 3. Plan capacity and scaling - Improve system performance 1. Use caching and content delivery 2. Tune applications and infrastructure 3. Optimize resource allocation - Apply FinOps practices 1. Use spot instances and committed use discounts 2. Monitor and analyze cloud costs 3. Right-size resources and eliminate waste
Bootstrapping and maintaining a Google Cloud organization	20%	- Set up governance and compliance 1. Manage resource quotas and limits 2. Implement organization policies 3. Configure audit logging and monitoring - Design resource hierarchy 1. Define IAM policies and access control 2. Plan shared networking and connectivity 3. Organize resources by project/folder/application - Manage configuration and deployment 1. Use Infrastructure as Code tools 2. Automate resource provisioning 3. Enforce consistency across environments
Building and implementing CI/CD pipelines	25%	- Optimize and maintain pipelines 1. Improve speed and reliability 2. Monitor pipeline performance 3. Handle rollbacks and versioning - Design CI/CD pipelines 1. Integrate artifact management 2. Support hybrid/multi-cloud deployment 3. Plan pipelines for apps, infrastructure, ML workloads - Implement and secure pipelines 1. Manage pipeline secrets and credentials 2. Enforce security scanning and compliance checks 3. Automate build, test, and deployment stages
Applying site reliability engineering practices	18%	- Design for resilience 1. Plan redundancy and fault tolerance 2. Automate remediation and self-healing 3. Test failure scenarios and recovery - Define reliability goals 1. Align reliability with business needs 2. Establish SLIs, SLOs, SLAs 3. Use error budgets to balance change and stability - Manage incidents and outages 1. Detect and respond to issues quickly 2. Implement improvements to prevent recurrence 3. Perform postmortems and root cause analysis
Implementing observability and troubleshooting	20%	- Optimize observability strategy 1. Reduce noise and prioritize signals 2. Integrate observability into development 3. Scale monitoring for large environments - Troubleshoot complex issues 1. Analyze performance and latency 2. Trace requests end-to-end 3. Isolate problems across layers - Build monitoring and logging systems 1. Use Cloud Monitoring, Cloud Logging, Cloud Trace 2. Collect and analyze metrics, logs, traces 3. Create dashboards and alerts

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q27-Q32):

NEW QUESTION # 27
You are deploying a Cloud Build job that deploys Terraform code when a Git branch is updated. While testing, you noticed that the job fails. You see the following error in the build logs:
Initializing the backend. ..
Error: Failed to get existing workspaces : querying Cloud Storage failed: googleapi : Error
403
You need to resolve the issue by following Google-recommended practices. What should you do?

A. Create a storage bucket with the name specified in the Terraform configuration.
B. Grant the roles/ storage. objectAdmin Identity and Access Management (IAM) role to the Cloud Build service account on the state file bucket.
C. Change the Terraform code to use local state.
D. Grant the roles/ owner Identity and Access Management (IAM) role to the Cloud Build service account on the project.

Answer: B

NEW QUESTION # 28
You are currently planning how to display Cloud Monitoring metrics for your organization's Google Cloud projects. Your organization has three folders and six projects:

You want to configure Cloud Monitoring dashboards lo only display metrics from the projects within one folder You need to ensure that the dashboards do not display metrics from projects in the other folders You want to follow Google-recommended practices What should you do?

A. Use the current app-one-prod project as the scoping project
B. Create new scoping projects for each folder
C. Use the current app-one-dev, app-one-staging and app-one-prod projects as the scoping project for each folder
D. Create a single new scoping project

Answer: D

Explanation:
The best option for configuring Cloud Monitoring dashboards to only display metrics from the projects within one folder is to create new scoping projects for each folder. A scoping project is a project that defines which resources are monitored by Cloud Monitoring. You can create new scoping projects for each folder by using the gcloud monitoring register-project command. This way, you can associate each scoping project with a folder and only monitor the resources within that folder. You can then configure Cloud Monitoring dashboards to use the scoping projects as data sources and only display metrics from the projects within one folder.

NEW QUESTION # 29
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. 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.
B. 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.
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 # 30
You are running an application in a virtual machine (VM) using a custom Debian image. The image has the Stackdriver Logging agent installed. The VM has the cloud-platform scope. The application is logging information via syslog. You want to use Stackdriver Logging in the Google Cloud Platform Console to visualize the logs. You notice that syslog is not showing up in the "All logs" dropdown list of the Logs Viewer. What is the first thing you should do?

A. SSH to the VM and execute the following commands on your VM: ps ax I grep fluentd
B. Look for the agent's test log entry in the Logs Viewer.
C. Verify the VM service account access scope includes the monitoring.write scope.
D. Install the most recent version of the Stackdriver agent.

Answer: A

Explanation:
https://cloud.google.com/compute/docs/access/service-accounts#associating_a_service_account_to_an_instance

NEW QUESTION # 31
Your company recently migrated to Google Cloud. You need to design a fast, reliable, and repeatable solution for your company to provision new projects and basic resources in Google Cloud. What should you do?

A. Write a Terraform module and save it in your source control repository. Copy and run the apply command to create the new project.
B. Use the Google Cloud console to create projects.
C. Use the Terraform repositories from the Cloud Foundation Toolkit. Apply the code with appropriate parameters to create the Google Cloud project and related resources.
D. Write a script by using the gcloud CLI that passes the appropriate parameters from the request. Save the script in a Git repository.

Answer: C

Explanation:
Terraform is an open-source tool that allows you to define and provision infrastructure as code1. Terraform can be used to create and manage Google Cloud resources, such as projects, networks, and services2. The Cloud Foundation Toolkit is a set of open-source Terraform modules and tools that provide best practices and guidance for deploying Google Cloud infrastructure3. The Cloud Foundation Toolkit includes Terraform repositories for creating Google Cloud projects and related resources, such as IAM policies, APIs, service accounts, and billing4. By using the Terraform repositories from the Cloud Foundation Toolkit, you can design a fast, reliable, and repeatable solution for your company to provision new projects and basic resources in Google Cloud. You can also customize the Terraform code to suit your specific needs and preferences.

NEW QUESTION # 32
......

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