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Audience for This Certification Exam

The target audience for the Google Professional Cloud DevOps Engineer test is formed of those individuals who want to learn how they can develop efficient operations and find a balance between the speed in delivering services and its reliability. Also, the candidates who are interested in taking this evaluation want to validate their skills in using the Google Cloud Platform at a professional level. Therefore, thanks to such an exam, applicants will learn how to develop pipelines related to software delivery, as well as become experts at monitoring and deploying services, together with managing and learning from them.

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

• Agree to consequences of not meeting the error budget
• Manage a service (e.g., introduce a new service, deploy it, maintain and retire it)
• Toil automation
• 1.2 Manage service life cycle:
• Discover SLIs (availability, latency, etc.)
• Balance change, velocity, and reliability of the service:
• Construct feedback loops to decide what to build next
• Define SLOs and understand SLAs

Building and implementing CI/CD pipelines for a service

• Deployment strategies with Cloud Build, Spinnaker
• Deployment to hybrid and multi-cloud environments with Anthos, Spinnaker, Kubernetes
• CI/CD pipeline triggers with Cloud Source Repositories, Cloud Build GitHub App, Cloud Pub/Sub
• Testing a new version with Spinnaker
• Configure deployment processes (e.g., approval flows)
• Artifact repositories with Container Registry
• Immutable artifacts with Container Registry
• Design CI/CD pipelines:
• Artifact versioning strategy with Cloud Build, Container Registry

Implementing service monitoring strategies

• Sending logs to an external logging platform
• Viewing export logs in Cloud Storage and BigQuery
• Enabling VPC flow logs
• Using basic vs. advanced logging filters
• Collecting third-party and structured logs with Stackdriver Logging, Fluentd
• Collecting logs from Compute Engine, GKE with Stackdriver Logging, Fluentd
• Implementing logs-based metrics
• Set ACL to allow metric writing for custom metrics with IAM, Stackdriver Monitoring
• Viewing logs in the GCP Console
• Selecting the options for logging export
• Collecting metrics from Compute Engine
• Enabling data access logs (e.g., Cloud Audit Logs)
• Understanding the logging exclusion vs. logging export
• Sending application logs directly to Stackdriver API with Stackdriver Logging
• Manage application logs:
• Use metric explorer for ad hoc metric analysis
• Implementing a project-level / org-level export
• Collecting GKE/Kubernetes metrics
• Set ACL to restrict access to audit logs with IAM, Stackdriver Logging
• Set ACL to restrict export configuration with IAM, Stackdriver Logging

Optimizing service performance

• TCO considerations
• Identify resource utilization levels
• Troubleshoot issues with the image/OS
• Evaluate and understand user impact (Stackdriver Service Monitoring for App Engine, Istio)
• Interpret service mesh telemetry
• Utilize Stackdriver to identify cloud resource utilization
• Identify service performance issues:
• identify resource costs
• Manage preemptible VMs
• Utilize Stackdriver Trace/Profiler to profile performance characteristics
• Develop a plan to optimize areas of greatest cost or lowest utilization
• Consider network pricing
• Troubleshoot network issues (e.g., VPC flow logs, firewall logs, latency, view network details)
• Work with committed-use discounts

Managing service incidents

• Provide regular status updates, internal and external
• Scaling response team and delegation
• Coordinate roles and implement communication channels during a service incident:
• Identify alternatives to mitigate the issue
• Manage stakeholder relationships
• Avoid exhaustion/burnout
• Perform an investigation to isolate the most likely actual cause
• Evaluate symptoms against probable causes; the rank probability of cause based on observed behavior
• Identify probable causes of service failure
• Define roles (incident commander, communication lead, operations lead)
• Establish communications channels (email, IRC, Hangouts, Slack, phone, etc.)
• Rotate/hand over roles
• Handle requests for impact assessment
• Record major changes in incident state (When mitigated? When all clear? etc.)

Conclusion

Passing the Google Professional Cloud DevOps Engineer evaluation is not impossible as long as you combine different learning solutions. While the vendor offers different preparation resources for the exam-takers who want to get the passing score without stress, you shouldn’t stop here. You can also go as far as to explore the guides available on Amazon and enhance your skills for becoming a certified Cloud DevOps Engineer.

Career Prospects

The Google Professional Cloud DevOps Engineer certification demonstrates your ability to efficiently perform the development operations that can balance service reliability and delivery speed. After completing the qualifying exam, you will be proficient in using Google Cloud Platform to build software delivery pipelines, deploy & monitor services, and manage incidents. This expertise will give you access to endless opportunities for career development. Immediately after getting certified, you can start a career as a Cloud DevOps Engineer. Additionally, you can apply for the related job roles, such as a DevOps Infrastructure Engineer, a Cloud Solutions Architect, a GCP Cloud Native Architect, a Google Cloud Platform Data Architect, a GCP Cloud Data Engineer, and more. The average salary that the certificate holders can earn ranges between $137,000 and $180,000 per year.