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

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

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q49-Q54):

NEW QUESTION # 49
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.editor and monitoring.metricwriter roles to the Compute Engine service accounts.
D. Grant the Logging. admin and monitoring . editor 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 # 50
Your organization recently adopted a container-based workflow for application development. Your team develops numerous applications that are deployed continuously through an automated build pipeline to a Kubernetes cluster in the production environment. The security auditor is concerned that developers or operators could circumvent automated testing and push code changes to production without approval. What should you do to enforce approvals?

A. Enable binary authorization inside the Kubernetes cluster and configure the build pipeline as an attestor.
B. Leverage Kubernetes Role-Based Access Control (RBAC) to restrict access to only approved users.
C. Configure the build system with protected branches that require pull request approval.
D. Use an Admission Controller to verify that incoming requests originate from approved sources.

Answer: A

NEW QUESTION # 51
Your team deploys applications to three Google Kubernetes Engine (GKE) environments development staging and production You use GitHub reposrtones as your source of truth You need to ensure that the three environments are consistent You want to follow Google-recommended practices to enforce and install network policies and a logging DaemonSet on all the GKE clusters in those environments What should you do?

A. Use Cloud Build to render and deploy the network policies and the DaemonSet Set up Config Sync to sync the configurations for the three environments
B. Use Cloud Build to render and deploy the network policies and the DaemonSet Set up a Policy Controller to enforce the configurations for the three environments
C. Use Google Cloud Deploy to deploy the DaemonSet and use Policy Controller to configure the network policies Use Cloud Monitoring to detect drifts from the source in the repository and Cloud Functions to correct the drifts
D. Use Google Cloud Deploy to deploy the network policies and the DaemonSet Use Cloud Monitoring to trigger an alert if the network policies and DaemonSet drift from your source in the repository.

Answer: A

Explanation:
The best option for ensuring that the three environments are consistent and following Google-recommended practices is to use Cloud Build to render and deploy the network policies and the DaemonSet, and set up Config Sync to sync the configurations for the three environments. Cloud Build is a service that executes your builds on Google Cloud infrastructure. You can use Cloud Build to render and deploy your network policies and DaemonSet as code using tools like Kustomize, Helm, or kpt. Config Sync is a feature that enables you to manage the configurations of your GKE clusters from a single source of truth, such as a Git repository. You can use Config Sync to sync the configurations for your development, staging, and production environments and ensure that they are consistent.

NEW QUESTION # 52
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. Develop an App Engine application that pulls the logs from Stackdriver and saves them in BigQuery.
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. Create a Cloud Storage bucket and develop your application to send logs directly to the bucket.

Answer: C

Explanation:
https://cloud.google.com/logging/docs/routing/overview

NEW QUESTION # 53
You are creating and assigning action items in a postmodern for an outage. The outage is over, but you need to address the root causes. You want to ensure that your team handles the action items quickly and efficiently.
How should you assign owners and collaborators to action items?

A. Assign one owner for each action item and any necessary collaborators.
B. Assign the team lead as the owner for all action items because they are in charge of the SRE team.
C. Assign multiple owners for each item to guarantee that the team addresses items quickly
D. Assign collaborators but no individual owners to the items to keep the postmortem blameless.

Answer: A

Explanation:
Explanation
https://devops.com/when-it-disaster-strikes-part-3-conducting-a-blameless-post-mortem/

NEW QUESTION # 54
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