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Zorluk: OrtaDeveloping Procedures to Test and Validate Technical Solutions

A healthcare enterprise is establishing a pre-flight deployment validation procedure on Google Cloud for a patient telemetry microservices application running on private Google Kubernetes Engine (GKE) clusters with sensitive datasets protected by VPC Service Controls. The validation procedure must ensure infrastructure readiness, pipeline safety, and service quality prior to directing live production traffic to new software releases. Which TWO validation practices should be included in the automated pre-deployment testing procedure? (Select TWO.)

  1. Verify regional compute and quota availability in the target GCP project using Service Usage APIs or Cloud Monitoring prior to triggering automated infrastructure deployment.Cevap
  2. B
    Store the Terraform state files created during ephemeral test environment provisioning in an unversioned local directory to accelerate CI/CD runner execution speeds.
  3. Execute automated canary deployments using Cloud Deploy with traffic shifting to validate key Service Level Indicators (SLIs) against Service Level Objectives (SLOs) before completing the rollout.Cevap
  4. D
    Grant the CI/CD pipeline service account the Service Account Admin role (`roles/iam.serviceAccountAdmin`) to allow it to attach service accounts to GKE node pools during pre-flight checks.
  5. E
    Disable control plane authorized networks on private GKE clusters during pre-flight testing so public CI/CD runners can perform integration checks via the Kubernetes API.

Cevap

The validation procedure should include verifying regional resource quota availability prior to deployment and executing automated canary deployments with Cloud Deploy to evaluate SLIs against defined SLO thresholds before completing full production releases.
A robust pre-flight validation strategy requires checking regional quota availability prior to resource creation to prevent provisioning failures, along with executing progressive canary deployments using Cloud Deploy to measure live telemetry against SLOs before full promotion.

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1
Assess pre-flight quota readiness
Ensure sufficient CPU, memory, and regional API quotas exist before creating resources, avoiding mid-deployment failures.
Large automated deployments fail if project quotas are exceeded, creating inconsistent environment states.
2
Implement progressive traffic validation with canary releases
Route a small percentage of production traffic to the new software release while Cloud Deploy monitors application health metrics.
Validating SLIs against SLOs in production with small traffic percentages confirms technical performance while limiting blast radius.

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Technical Solution Testing and Validation Procedures
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Developing Procedures to Test and Validate Technical Solutions