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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

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

Building and implementing CI/CD pipelines for a service

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

Implementing service monitoring strategies

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

Optimizing service performance

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

Managing service incidents

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

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How to book Google Professional Cloud DevOps Engineer Exams

The registration for the Google Professional Cloud DevOps Engineer exam follows the steps given below.

  • Step 1: Visit the Google Cloud Webassessor Website
  • Step 2: Sign-in or sign up to your Google Cloud Webassessor account
  • Step 3: Search for the exam name Google Professional Cloud DevOps Engineer
  • Step 4: Take the date of the exam, choose the exam center, and make further payment using payment methods like credit/debit, etc.

After registering for the exam, prepare from the Professional Cloud DevOps Engineer exam dumps and make sure to take Professional Cloud DevOps Engineer practice exam so you know the exam format in advance. This will give you an advantage over other candidates.

The Google Professional Cloud DevOps Engineer exam is taken by the specialists who want to obtain international certification and get validated as professional engineers who can manage Cloud DevOps features.

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

SectionObjectives
Implement security and compliance- Secure CI/CD pipelines
  • 1. Secret and credential management
    • 2. IAM and least privilege access
      - Compliance and governance
      • 1. Audit logging and policy enforcement
        Develop and implement CI/CD pipelines- Build and manage CI/CD pipelines using Google Cloud tools
        • 1. Cloud Build pipeline design
          • 2. Artifact repository management
            - Automate build, test, and deployment processes
            • 1. Deployment automation strategies
              • 2. Release management practices
                Implement site reliability engineering (SRE) practices- Incident management and postmortems
                • 1. Alerting and on-call practices
                  - Define and manage SLI, SLO, and SLA
                  • 1. Error budgets and monitoring strategies
                    Optimize performance and continuous delivery- Monitoring and observability
                    • 1. Performance tuning and feedback loops
                      • 2. Cloud Monitoring and Logging
                        - System performance optimization
                        • 1. Scaling strategies and load handling

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