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Google Professional Cloud DevOps Engineer Certification Path

The Google Professional Cloud DevOps Engineer Certification is the highest level of certification mainly focusing on the Solution Architect Professional. There is no prerequisite for this exam but still, it would be best to follow some sequence to prove immense knowledge as a Google Professional Cloud DevOps Engineer.

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

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

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

Building and implementing CI/CD pipelines for a service

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

Implementing service monitoring strategies

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

Optimizing service performance

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

Managing service incidents

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

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