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Preparation Process

The best way to prepare for the Google Professional Cloud DevOps Engineer certification exam is to explore the training tools offered on its official website. The candidates can start their preparation process by reviewing the topics in the study guide. This will give them an idea of what they need to cover studying for the test and plan their learning time properly.

The official platform recommends that the potential individuals complete the Professional DevOps Engineer learning path, which includes in-person classes, online training, and hands-on labs for a better understating of the exam content. The courses within this path cover each aspect of the certification test in depth improving the candidates’ chances of passing the exam at the first attempt. Apart from the learning path, the applicants can take advantage of additional resources such as Google Cloud documentation and Google Cloud solutions. There is also the option of signing up for a dedicated webinar to learn valuable prep tips from the Google experts. At the end of your preparation, use the official sample questions to familiarize yourself with the format of exam questions and check the level of readiness.

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

Building and implementing CI/CD pipelines for a service

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

Implementing service monitoring strategies

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

Optimizing service performance

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

Managing service incidents

• Identify probable causes of service failure
• Manage stakeholder relationships
• 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
• Provide regular status updates, internal and external
• Avoid exhaustion/burnout
• Handle requests for impact assessment
• Identify alternatives to mitigate the issue
• Perform an investigation to isolate the most likely actual cause
• Rotate/hand over roles
• Scaling response team and delegation
• Coordinate roles and implement communication channels during a service incident:
• Define roles (incident commander, communication lead, operations lead)
• Establish communications channels (email, IRC, Hangouts, Slack, phone, etc.)

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

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