A logistics company needs to run a weekly 12-hour batch processing job to re-calculate global shipping routes. The workload is containerized, fully fault-tolerant, and designed to automatically save state to Cloud Storage and resume from checkpoints if interrupted. The operations team wants to minimize compute costs while ensuring that any terminated compute capacity is automatically replaced until the job finishes. Which compute configuration should the cloud engineer recommend to meet these requirements at the lowest cost?
- Deploy a Compute Engine Managed Instance Group (MIG) configured with Spot VMs.Cevap
- BDeploy the job to a Cloud Functions function triggered by Cloud Scheduler to run continuously for 12 hours.
- CProvision standalone Compute Engine instances backed by a 3-year Committed Use Discount (CUD).
- DProvision On-Demand instances in a GKE cluster with static node sizing to prevent instance termination.
Cevap
Deploying a Compute Engine Managed Instance Group (MIG) configured with Spot VMs is the optimal solution because Spot VMs offer up to 60-91% discounts for fault-tolerant batch workloads, and the Managed Instance Group automatically maintains capacity by replacing preempted instances.
The option recommending a Compute Engine Managed Instance Group (MIG) configured with Spot VMs is correct because Spot VMs offer extreme cost savings for workloads that tolerate preemption. Since the batch application saves state to Cloud Storage and can resume from checkpoints, instance preemption will not cause data loss. The MIG ensures high availability by automatically recreating instances when GCP reclaims Spot capacity.
Adım Adım Çözüm
Anahtar Kavram
Selecting cost-effective compute solutions using Spot VMs and Managed Instance Groups for fault-tolerant batch workloads.