Professional-Cloud-DevOps-Engineer Übungsfragen: Google Cloud Certified - Professional Cloud DevOps Engineer Exam & Professional-Cloud-DevOps-Engineer Dateien Prüfungsunterlagen

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Google Professional-Cloud-DevOps-Engineer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|
| Building and implementing CI/CD pipelines | 25% | - 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. Enforce security scanning and compliance checks
- 2. Automate build, test, and deployment stages
- 3. Manage pipeline secrets and credentials
- Optimize and maintain pipelines
- 1. Improve speed and reliability
- 2. Monitor pipeline performance
- 3. Handle rollbacks and versioning
|
| Implementing observability and troubleshooting | 20% | - Troubleshoot complex issues
- 1. Trace requests end-to-end
- 2. Isolate problems across layers
- 3. Analyze performance and latency
- Optimize observability strategy
- 1. Reduce noise and prioritize signals
- 2. Integrate observability into development
- 3. Scale monitoring for large environments
- Build monitoring and logging systems
- 1. Create dashboards and alerts
- 2. Collect and analyze metrics, logs, traces
- 3. Use Cloud Monitoring, Cloud Logging, Cloud Trace
|
| Optimizing performance and cost | 17% | - Apply FinOps practices
- 1. Monitor and analyze cloud costs
- 2. Right-size resources and eliminate waste
- 3. Use spot instances and committed use discounts
- Balance cost, performance, and reliability
- 1. Make tradeoff decisions based on data
- 2. Optimize over time
- 3. Plan capacity and scaling
- Improve system performance
- 1. Tune applications and infrastructure
- 2. Optimize resource allocation
- 3. Use caching and content delivery
|
| Bootstrapping and maintaining a Google Cloud organization | 20% | - Design resource hierarchy
- 1. Plan shared networking and connectivity
- 2. Organize resources by project/folder/application
- 3. Define IAM policies and access control
- Manage configuration and deployment
- 1. Enforce consistency across environments
- 2. Use Infrastructure as Code tools
- 3. Automate resource provisioning
- Set up governance and compliance
- 1. Configure audit logging and monitoring
- 2. Implement organization policies
- 3. Manage resource quotas and limits
|
| Applying site reliability engineering practices | 18% | - Define reliability goals
- 1. Use error budgets to balance change and stability
- 2. Align reliability with business needs
- 3. Establish SLIs, SLOs, SLAs
- Manage incidents and outages
- 1. Implement improvements to prevent recurrence
- 2. Detect and respond to issues quickly
- 3. Perform postmortems and root cause analysis
- Design for resilience
- 1. Test failure scenarios and recovery
- 2. Plan redundancy and fault tolerance
- 3. Automate remediation and self-healing
|
>> Professional-Cloud-DevOps-Engineer Fragen Beantworten <<
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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Professional-Cloud-DevOps-Engineer Prüfungsfragen mit Lösungen (Q21-Q26):
21. Frage
Your organization wants to increase the availability target of an application from 99 9% to 99 99% for an investment of $2 000 The application's current revenue is S1,000,000 You need to determine whether the increase in availability is worth the investment for a single year of usage What should you do?
- A. Calculate the value of improved availability to be $1 000 and determine that the increase in availability is not worth the investment
- B. Calculate the value of improved availability to be $9,000. and determine that the increase in availability is worth the investment
- C. Calculate the value of improved availability to be $900, and determine that the increase in availability is not worth the investment
- D. Calculate the value of improved availability to be $1 000 and determine that the increase in availability is worth the investment
Antwort: C
Begründung:
Explanation
The best option for determining whether the increase in availability is worth the investment for a single year of usage is to calculate the value of improved availability to be $900, and determine that the increase in availability is not worth the investment. To calculate the value of improved availability, we can use the following formula:
Value of improved availability = Revenue * (New availability - Current availability) Plugging in the given numbers, we get:
Value of improved availability = $1,000,000 * (0.9999 - 0.999) = $900
Since the value of improved availability is less than the investment of $2,000, we can conclude that the increase in availability is not worth the investment.
22. Frage
You are on-call for an infrastructure service that has a large number of dependent systems. You receive an alert indicating that the service is failing to serve most of its requests and all of its dependent systems with hundreds of thousands of users are affected. As part of your Site Reliability Engineering (SRE) incident management protocol, you declare yourself Incident Commander (IC) and pull in two experienced people from your team as Operations Lead (OLJ and Communications Lead (CL). What should you do next?
- A. Contact the affected service owners and update them on the status of the incident.
- B. Look for ways to mitigate user impact and deploy the mitigations to production.
- C. Establish a communication channel where incident responders and leads can communicate with each other.
- D. Start a postmortem, add incident information, circulate the draft internally, and ask internal stakeholders for input.
Antwort: C
23. Frage
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. logwriter and monitoring. editor roles to the Compute Engine service accounts.
- C. Grant the logging. logWriter 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.
Antwort: C
Begründung:
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.
24. Frage
You have a CI/CD pipeline that uses Cloud Build to build new Docker images and push them to Docker Hub. You use Git for code versioning. After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline. You need to resolve the issue following Site Reliability Engineering practices. What should you do?
- A. Upload the configuration YAML file to Cloud Storage and use Error Reporting to identify and fix the issue.
- B. Run a Git compare between the previous and current Cloud Build Configuration files to find and fix the bug.
- C. Disable the CI pipeline and revert to manually building and pushing the artifacts.
- D. Change the CI pipeline to push the artifacts to Container Registry instead of Docker Hub.
Antwort: B
Begründung:
"After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline"- means something wrong on the recent change not with the image registry.
25. Frage
Your team is running microservices in Google Kubernetes Engine (GKE) You want to detect consumption of an error budget to protect customers and define release policies What should you do?
- A. Use the metrics from Anthos Service Mesh to measure the health of the microservices
- B. Create SLIs from metrics Enable Alert Policies if the services do not pass
- C. Create a SLO and configure uptime checks for your services Enable Alert Policies if the services do not pass
- D. Create a SLO Create an Alert Policy on select_slo_bum_rate
Antwort: D
Begründung:
Explanation
The best option for detecting consumption of an error budget to protect customers and define release policies is to create a service level objective (SLO) and create an alert policy on select_slo_burn_rate. A SLO is a target value or range of values for a service level indicator (SLI) that measures some aspect of the service quality, such as availability or latency. An error budget is the amount of time or number of errors that a service can tolerate while still meeting its SLO. A select_slo_burn_rate is a metric that indicates how fast the error budget is being consumed by the service. By creating an alert policy on select_slo_burn_rate, you can trigger notifications or actions when the error budget consumption exceeds a certain threshold. This way, you can balance change, velocity, and reliability of the service by adjusting the release policies based on the error budget status.
26. Frage
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