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How much Google Professional Cloud DevOps Engineer Exam cost
Google Professional Cloud DevOps Engineer exam cost is USD 200, for more information related to the Google Professional Cloud DevOps Engineer exam, please visit Google Website. Additional costs of Professional Cloud DevOps Engineer exam dumps pdf and Professional Cloud DevOps Engineer practice test are not included in this price.
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 |
| Real Exam Qty: | 50 |
| Available Languages: | English, Japanese, Spanish, Portuguese |
| Exam Duration: | 120 minutes |
| Passing Score: | 70% |
| Exam Price: | $200 USD |
| Certificate Validity Period: | 2 years |
| Related Certifications: | Google Cloud Associate Cloud Engineer Google Cloud Professional Cloud Architect Google Cloud Professional Cloud Developer |
| Exam Format: | Multiple Choice, Multiple Select |
| 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 |
Google Professional-Cloud-DevOps-Engineer Exam Syllabus Topics:
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Reference: https://cloud.google.com/certification/cloud-devops-engineer
Topics of Google Professional Cloud DevOps Engineer Exam
Candidates must know the exam topics before they start preparation because it will help them in hitting the core. Our Professional Cloud DevOps Engineer Dumps will include the following topics:
Applying site reliability engineering principles to a service
- Balance change, velocity, and reliability of the service:
- Define SLOs and understand SLAs
- Toil automation
- Agree to consequences of not meeting the error budget
- Discover SLIs (availability, latency, etc.)
- Construct feedback loops to decide what to build next
- 1.2 Manage service life cycle:
- Manage a service (e.g., introduce a new service, deploy it, maintain and retire it)
Building and implementing CI/CD pipelines for a service
- Artifact versioning strategy with Cloud Build, Container Registry
- Deployment to hybrid and multi-cloud environments with Anthos, Spinnaker, Kubernetes
- Artifact repositories with Container Registry
- Design CI/CD pipelines:
- CI/CD pipeline triggers with Cloud Source Repositories, Cloud Build GitHub App, Cloud Pub/Sub
- Testing a new version with Spinnaker
- Immutable artifacts with Container Registry
- Configure deployment processes (e.g., approval flows)
- Deployment strategies with Cloud Build, Spinnaker
Implementing service monitoring strategies
- Implementing a project-level / org-level export
- Sending application logs directly to Stackdriver API with Stackdriver Logging
- Implementing logs-based metrics
- Manage application logs:
- Set ACL to allow metric writing for custom metrics with IAM, Stackdriver Monitoring
- Viewing logs in the GCP Console
- Collecting metrics from Compute Engine
- Collecting GKE/Kubernetes metrics
- Understanding the logging exclusion vs. logging export
- Set ACL to restrict access to audit logs with IAM, Stackdriver Logging
- Viewing export logs in Cloud Storage and BigQuery
- Sending logs to an external logging platform
- Selecting the options for logging export
- Enabling VPC flow logs
- Enabling data access logs (e.g., Cloud Audit Logs)
- Using basic vs. advanced logging filters
- Collecting third-party and structured logs with Stackdriver Logging, Fluentd
- Set ACL to restrict export configuration with IAM, Stackdriver Logging
- Use metric explorer for ad hoc metric analysis
- Collecting logs from Compute Engine, GKE with Stackdriver Logging, Fluentd
Optimizing service performance
- Manage preemptible VMs
- Work with committed-use discounts
- identify resource costs
- Develop a plan to optimize areas of greatest cost or lowest utilization
- Evaluate and understand user impact (Stackdriver Service Monitoring for App Engine, Istio)
- Consider network pricing
- Troubleshoot issues with the image/OS
- Troubleshoot network issues (e.g., VPC flow logs, firewall logs, latency, view network details)
- Utilize Stackdriver to identify cloud resource utilization
- Utilize Stackdriver Trace/Profiler to profile performance characteristics
- TCO considerations
- Identify resource utilization levels
- Interpret service mesh telemetry
- Identify service performance issues:
Managing service incidents
- Perform an investigation to isolate the most likely actual cause
- Manage stakeholder relationships
- Record major changes in incident state (When mitigated? When all clear? etc.)
- Provide regular status updates, internal and external
- Identify alternatives to mitigate the issue
- Avoid exhaustion/burnout
- Rotate/hand over roles
- Evaluate symptoms against probable causes; the rank probability of cause based on observed behavior
- Define roles (incident commander, communication lead, operations lead)
- Coordinate roles and implement communication channels during a service incident:
- Scaling response team and delegation
- Establish communications channels (email, IRC, Hangouts, Slack, phone, etc.)
- Handle requests for impact assessment
- Identify probable causes of service failure
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