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.

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Introduction to Google Professional Cloud DevOps Engineer Exam

Google Professional Cloud DevOps Engineer Exam is a certification exam that is conducted by Google to validates candidate knowledge and skills of working as a Professional Cloud DevOps engineer in the IT industry.

After passing this Professional Cloud DevOps Engineer Exam test, candidates get a certificate from Google that helps them to demonstrate their proficiency in Google Professional Cloud DevOps Engineer to their clients and employers.

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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

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

Building and implementing CI/CD pipelines for a service

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

Implementing service monitoring strategies

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

Optimizing service performance

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

Managing service incidents

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

Reference: https://cloud.google.com/certification/cloud-devops-engineer

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