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

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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

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

Building and implementing CI/CD pipelines for a service

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

Implementing service monitoring strategies

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

Optimizing service performance

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

Managing service incidents

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

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