Professional Cloud DevOps Engineer
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Prepare and test your skills
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A DevOps team manages a large-scale, fault-tolerant data processing workload on Google Cloud. The team uses Spot Virtual Machines (VMs) to maximize FinOps cost efficiency over standard on-demand compute rates. However, regional capacity shifts in spare compute resources occasionally lead to high preemption spikes when the workload is pinned to a single machine type (n2-standard-16). The team needs to configure a regional Managed Instance Group (MIG) that leverages multiple machine families (c3-standard-16, n2-standard-16, and c2-standard-16) while minimizing workload disruption from preemptions.
How should the DevOps team configure the regional Managed Instance Group to achieve the lowest preemption rate across these machine types?
Configure a regional MIG with an ANY_SINGLE_ZONE distribution shape and apply a single-year Committed Use Discount (CUD) reservation to prevent Compute Engine from preempting Spot instances.
Deploy separate zonal MIGs for each machine family and use Cloud Scheduler with Cloud Functions to migrate instances based on hourly on-demand price differences.
Create a Dataproc cluster with secondary workers and modify the spot-to-non-preemptible secondary worker mix ratio dynamically during peak preemption hours.
Configure an instance flexibility policy containing the desired machine types within an instance selection, allowing the regional MIG to automatically select the machine type with the lowest observed preemption rate.
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