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

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

Introduction to Google Professional Cloud DevOps Engineer Exam

Google Professional Cloud DevOps Engineer Exam is a certification exam that is conducted by Google to validates candidate knowledge and skills of working as a Professional Cloud DevOps engineer in the IT industry.

After passing this Professional Cloud DevOps Engineer Exam test, candidates get a certificate from Google that helps them to demonstrate their proficiency in Google Professional Cloud DevOps Engineer to their clients and employers.

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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.

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

• Define SLOs and understand SLAs
• Discover SLIs (availability, latency, etc.)
• Toil automation
• Construct feedback loops to decide what to build next
• Agree to consequences of not meeting the error budget
• Balance change, velocity, and reliability of the service:
• 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

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

Implementing service monitoring strategies

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

Optimizing service performance

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

Managing service incidents

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