What is the duration, language, and format of Google Professional Cloud DevOps Engineer Exam

• Language: English
• Format: Multiple choices, multiple select
• Passing score: 80%
• Number of Questions: 50-60
• Length of Examination: 120 minutes

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

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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.

Domains Tested in Final Evaluation

The candidates who succeed in passing the Google Professional Cloud DevOps Engineer validation will add an international designation under their belt that helps them consolidate their position in the company and receive generous offers from their employers. So, if applicants want to differentiate themselves from other colleagues, they should demonstrate the following skills:

• Implementing and building CI/CD service pipelines;
• Coordinating teams to identify and manage incidents related to service development.
• Identifying issues related to service performance and implementing solutions to optimize it;
• Identifying the most effective principles related to site reliability engineering and applying them to a definite service;
• Checking and implementing strategies related to service monitoring;

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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

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

Building and implementing CI/CD pipelines for a service

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

Implementing service monitoring strategies

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

Optimizing service performance

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

Managing service incidents

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

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