Professional Cloud DevOps Engineer
Prepare and test your skills
Prepare and test your skills
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An enterprise runs three distinct workloads on Google Cloud Compute Engine:
Which combination of instance configurations and purchasing models should the DevOps engineer implement to minimize total infrastructure costs while maintaining reliability?
This strategy combines custom machine types, resource-based Committed Use Discounts (CUDs), stateless Managed Instance Groups (MIGs) with autoscaling, and Spot VMs to align infrastructure purchase models precisely with workload profiles and utilization metrics.
StudyCerts
StudyCertsn1-standard or n2-standard) enforce standard resource ratios of 1 vCPU to 4 GB RAM. For a workload requiring 24 vCPUs and 48 GB RAM (1:2 ratio), predefined sizing would force provisioning a standard 24 vCPU / 96 GB RAM instance or an oversized machine, creating 48 GB of unutilized, paid RAM. Provisioning a custom machine type aligns allocation directly to the 1:2 ratio. Backing this steady-state baseline with a 1-year or 3-year resource-based Committed Use Discount cuts baseline compute costs by up to 55% without incurring waste.This architecture adheres to core FinOps principles by pairing predictable, non-standard footprints with custom sizing and commitments, while utilizing elasticity and deeply discounted preemptible capacity where architectural fault tolerance permits.
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