A healthcare telemetry platform is deploying a bursty event-processing workload on Google Cloud using Compute Engine Managed Instance Groups (MIGs). The autoscaling policy scales compute nodes based on custom Cloud Monitoring queue depth metrics, rapidly expanding from 10 instances to over 400 N2 high-memory instances during peak ingestion windows. The deployment pipeline uses Terraform to automate infrastructure provisioning, and the worker instances must securely assume a custom identity to interact with Bigtable. During initial stress testing of a new region, scaling events stalled halfway through expansion, and Terraform updates failed. Which combination of administrative and provisioning actions must the architecture team implement to prevent these failures?
- Submit regional vCPU quota increase requests in advance for the target compute instance family, and grant the deployment pipeline service account the Service Account User role (roles/iam.serviceAccountUser) on the worker service account.Cevap
- BMigrate the processing workload to a Google Kubernetes Engine (GKE) Autopilot cluster, as GKE managed clusters automatically override and bypass project-level regional compute quotas.
- CStore the Terraform state file in a local ephemeral container volume during deployment to reduce network latency and state locking timeouts during large autoscaling events.
- DAssign the Owner primitive IAM role (roles/owner) to the deployment pipeline service account to ensure it bypasses service account identity configuration checks.