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Difficulty: HardProvisioning Compute Engine and Kubernetes Engine Clusters

A global gaming enterprise is preparing to launch a real-time multiplayer backend hosted on Google Cloud using automated Infrastructure as Code (IaC) pipelines with Terraform. The design requires deploying regional Compute Engine Managed Instance Groups (MIGs) across multiple zones to process high-throughput UDP traffic. To support the upcoming launch of 50,000 concurrent game instances, the deployment automation must prevent state concurrency conflicts, ensure successful automated resource creation without runtime quota rejections, and strictly observe least-privilege security principles. Which TWO architectural and administrative actions should the team perform as part of the initial provisioning strategy?

  1. Configure the Terraform deployment pipeline to use a Cloud Storage backend configured with bucket versioning and object state locking enabled.Answer
  2. Submit a request to increase the regional Compute Engine N2 vCPU quota in the target deployment regions prior to triggering the automated provisioning pipeline.Answer
  3. C
    Grant the deployment pipeline service account the Service Account Admin role (roles/iam.serviceAccountAdmin) on the custom compute service account attached to the MIG instances.
  4. D
    Assign the primitive Owner role (roles/owner) to the Compute Engine service account to ensure uninterrupted communication with backend Cloud Storage and Logging APIs.
  5. E
    Migrate the game server instances to a Google Kubernetes Engine (GKE) Autopilot cluster to host non-containerized legacy monolithic C++ game binary executables directly.

Answer

The correct provisioning strategy requires storing the Terraform state file in a Cloud Storage backend configured with versioning and object locking, and requesting regional Compute Engine vCPU quota increases before initiating the deployment.
Establishing a remote Cloud Storage backend with object versioning and state locking protects the IaC environment from concurrent modification and state file corruption. Concurrently, requesting regional Compute Engine vCPU quota increases prior to triggering large automated deployments ensures that compute provisioning requests succeed without hitting default quota caps.

Step-by-Step Solution

1
Evaluate IaC state management requirements for automated pipelines
Configuring a Cloud Storage remote backend with state locking prevents race conditions and state corruption during concurrent pipeline executions.
Enterprise IaC automation requires centralized, lockable, and version-controlled remote state.
2
Analyze capacity requirements for large-scale compute resource provisioning
Requesting regional vCPU quota increases prior to deployment guarantees that Compute Engine MIG scaling operations will not be blocked by default quota limits.
Default project quotas in GCP often fall below the requirements of large-scale enterprise deployments, leading to runtime resource creation errors if not increased in advance.
3
Audit security and service choices against GCP architectural best practices
Reject primitive IAM roles and excessive administrative grants in favor of targeted roles like Service Account User, and avoid running non-containerized monoliths on GKE.
Adhering to least-privilege security and matching compute platforms to workload types prevents operational and compliance issues.

Key Concept

Provisioning Compute Engine Resources and IaC State Management
Estimated Time:2m 0s
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Topics

Provisioning Compute Engine and Kubernetes Engine Clusters

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