CompTIA Cloud+ (CV0-004)OperationsMedium
A cloud operations team is reviewing their cloud expenditure and identifies that a significant portion of their compute costs comes from idle virtual machines (VMs) during off-peak hours. The applications running on these VMs can tolerate some downtime for startup. Which optimization strategy would provide the most immediate and significant cost savings?
- AScheduling VMs to power off during off-peak hours.
- BImplementing auto-scaling for the VMs.
- CMigrating VMs to smaller instance types.
- DSwitching to reserved instances for all VMs.
Show answer & explanationAnswer & explanation
Correct answer: A. Scheduling VMs to power off during off-peak hours.
Scheduling VMs to power off during off-peak hours directly eliminates compute costs for the periods when they are idle, providing immediate and significant savings, especially for applications that can tolerate startup time.
Why the other options are wrong
- B. Auto-scaling would dynamically adjust capacity, but if the VMs are truly idle and the application can tolerate downtime, powering them off completely is more cost-effective than just scaling down.
- C. Migrating to smaller instance types optimizes costs if the VMs are over-provisioned, but doesn't address the cost of *idle* time.
- D. Reserved instances offer discounts for continuous, long-term use, but they still incur costs even if the instance is idle and not running, which doesn't solve the idle cost issue completely.
Cost Optimization: Scheduling Off-Peak Shutdown
A cloud cost optimization technique that involves automatically powering off non-production or non-critical resources during periods of low or no demand.
- Directly reduces compute costs by stopping billing for idle resources.
- Ideal for development, test, or non-critical environments.
- Requires applications to tolerate startup time after power-on.
Memory trick: Turn off the lights, save the bytes!