Google Professional-Cloud-DevOps-Engineer日本語 : Google Cloud Certified - Professional Cloud DevOps Engineer Exam (Professional-Cloud-DevOps-Engineer日本語版)

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.

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

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

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

Implementing service monitoring strategies

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

Optimizing service performance

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

Managing service incidents

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

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

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