Google Exam Professional-Cloud-DevOps-Engineer Questions Answers Test Simulator

Professional-Cloud-DevOps-Engineer Exam Topics

Section 1. Applying site reliability engineering principles to a service

1.1 Balance change, velocity, and reliability of the service:

• Discover SLIs (e.g., availability, latency)
• Define SLOs and understand SLAs
• Agree to consequences of not meeting the error budget
• Construct feedback loops to decide what to build next
• Eliminate toil via automation

1.2 Manage service life cycle:

• Manage a service (e.g., introduce a new service, deploy, maintain, and retire it)
• Plan for capacity (e.g., quotas and limits management)
• 3 Ensure healthy communication and collaboration for operations:
• Prevent burnout (e.g., set up automation processes to prevent burnout)
• Foster a learning culture
• Foster a culture of blamelessness

Section 2. Building and implementing CI/CD pipelines for a service

2.1 Design CI/CD pipelines:

• Creating and storing immutable artifacts with Artifact Registry
• Deployment strategies with Cloud Build and Spinnaker
• Deployment to hybrid and multicloud environments with Anthos, Spinnaker, and Kubernetes
• Artifact versioning strategy with Cloud Build and Artifact Registry
• CI/CD pipeline triggers with Cloud Source Repositories, external SCM, and Pub/Sub
• Testing a new version with Spinnaker
• Configuring deployment processes (e.g., approval flows)

2.2 Implement CI/CD pipelines:

• CI with Cloud Build
• CD with Cloud Build
• Open source tooling (e.g., Jenkins, Spinnaker, GitLab, Concourse)
• Auditing and tracing of deployments (e.g., CSR, Artifact Registry, Cloud Build, Cloud Audit Logs)

2.3 Manage configuration and secrets:

• Secure storage methods
• Secret rotation and config changes

2.4 Manage infrastructure as code:

• Terraform
• Infrastructure code versioning
• Make infrastructure changes safer
• Immutable architecture

2.5 Deploy CI/CD tooling:

• Centralized tools vs. multiple tools (single vs. multi-tenant)
• Security of CI/CD tooling

2.6 Manage different development environments (e.g., staging, production):

• Decide on the number of environments and their purpose
• Create environments dynamically per feature branch with GKE
• Local development environments with Docker, Cloud Code, Skaffold

2.7 Secure the deployment pipeline:

• Vulnerability analysis with Artifact Registry
• Binary Authorization
• IAM policies per environment

Section 3. Implementing service monitoring strategies

3.1 Manage application logs:

• Collecting logs from Compute Engine, GKE with Cloud Logging, Fluentd
• Collecting third-party and structured logs with Cloud Logging, Fluentd
• Sending application logs directly to the Cloud Logging API

3.2 Manage application metrics with Cloud Monitoring:

• Collecting metrics from Compute Engine
• Collecting GKE/Kubernetes metrics
• Use Metrics Explorer for ad hoc metric analysis

3.3 Manage Cloud Monitoring platform:

• Creating a monitoring dashboard
• Filtering and sharing dashboards
• Configure third-party alerting in Cloud Monitoring (e.g., PagerDuty, Slack)
• Define alerting policies based on SLIs with Cloud Monitoring
• Automate alerting policy definition with Terraform
• Implementing SLO monitoring and alerting with Cloud Monitoring
• Understand Cloud Monitoring integrations (e.g., Grafana, BigQuery)
• Using SIEM tools to analyze audit/flow logs (e.g., Splunk, Datadog)
• Design Cloud Monitoring metrics scopes

3.4 Manage Cloud Logging platform:

• Enabling data access logs (e.g., Cloud Audit Logs)
• Enabling VPC flow logs
• Viewing logs in the Google Cloud Console
• Using basic vs. advanced logging filters
• Implementing logs-based metrics
• Understanding the logging exclusion vs. logging export
• Selecting the options for logging export
• Implementing a project-level / org-level export
• Viewing export logs in Cloud Storage and BigQuery
• Sending logs to an external logging platform

3.5 Implement logging and monitoring access controls:

• Set ACL to restrict access to audit logs with IAM, Cloud Logging
• Set ACL to restrict export configuration with IAM, Cloud Logging
• Set ACL to allow metric writing for custom metrics with IAM, Cloud Monitoring

Section 4. Optimizing service performance

4.1 Identify service performance issues:

• Evaluate and understand user impact
• Utilize Google Cloud’s operations suite to identify cloud resource utilization
• Utilize Cloud Trace and Cloud Profiler to profile performance characteristics
• Interpret service mesh telemetry
• Troubleshoot issues with the image/OS
• Troubleshoot network issues (e.g., VPC flow logs, firewall logs, latency, view network details)

4.2 Debug application code:

• Application instrumentation
• Cloud Debugger
• Cloud Logging
• Cloud Trace
• Debugging distributed applications
• App Engine local development server
• Error Reporting
• Cloud Profiler

4.3 Optimize resource utilization:

• Identify resource costs
• Identify resource utilization levels
• Develop plan to optimize areas of greatest cost or lowest utilization
• Manage preemptible VMs
• Utilize committed use discounts where appropriate
• TCO considerations (e.g., security, logging, networking)
• Consider network pricing

Section 5. Managing service incidents

5.1 Coordinate roles and implement communication channels during a service incident:

• Define roles (incident commander, communication lead, operations lead)
• Handle requests for impact assessment
• Provide regular status updates, internal and external
• Record major changes in incident state (e.g., When mitigated? When is all clear?)
• Establish communications channels (e.g., email, IRC, Hangouts, Slack, phone)
• Scaling response team and delegation
• Avoid exhaustion / burnout
• Rotate / hand over roles
• Manage stakeholder relationships

5.2 Investigate incident symptoms impacting users:

• Identify probable causes of service failure
• Evaluate symptoms against probable causes; rank probability of cause based on observed behavior
• Perform investigation to isolate most likely actual cause
• Identify alternatives to mitigate issue

5.3 Mitigate incident impact on users:

• Roll back release
• Drain / redirect traffic
• Turn off experiment
• Add capacity

5.4 Resolve issues with deployments (e.g., Cloud Build, Jenkins):

• Code change / fix bug
• Verify fix
• Declare all-clear

5.5 Document issue in a postmortem:

• Document root causes
• Create and prioritize action items
• Communicate postmortem to stakeholders

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