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An organization runs an image processing pipeline on Google Cloud Compute Engine. The system requires a guaranteed baseline capacity of 10 virtual machines running 24/7 to handle critical operational SLAs, while demand frequently spikes up to 40 additional virtual machines for fault-tolerant, stateless batch jobs that can tolerate interruptions and restarts.
Which provisioning strategy offers the most cost-effective architecture while guaranteeing baseline performance SLAs?
Purchase a 3-year Committed Use Discount for all 50 instances to maximize commitment discounts across total peak capacity.
Provision all 50 virtual machines on standard On-Demand pricing within a single regional Managed Instance Group with aggressive CPU rightsizing enabled.
Purchase 3-year Committed Use Discounts (CUDs) for the baseline 10 instances, and configure an autoscaling Managed Instance Group (MIG) utilizing Spot VMs for the surge batch processing capacity.
Provision all 50 virtual machines as Spot VMs in a Managed Instance Group to achieve maximum upfront cost savings across the entire fleet.
Purchase a 3-year Committed Use Discount for all 50 instances to maximize commitment discounts across total peak capacity.
Provision all 50 virtual machines on standard On-Demand pricing within a single regional Managed Instance Group with aggressive CPU rightsizing enabled.
Purchase 3-year Committed Use Discounts (CUDs) for the baseline 10 instances, and configure an autoscaling Managed Instance Group (MIG) utilizing Spot VMs for the surge batch processing capacity.
This hybrid provisioning strategy combines Committed Use Discounts (CUDs) for predictable, continuous baseline workloads with Spot VMs (compute volatility instances) for dynamic, fault-tolerant surge capacity within Google Cloud Compute Engine.
Alternative approaches either incur excessive costs by running all 50 nodes on standard on-demand/committed rates or risk violating core SLAs by deploying baseline capacity on preemptible/spot infrastructure.
Provision all 50 virtual machines as Spot VMs in a Managed Instance Group to achieve maximum upfront cost savings across the entire fleet.
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