What is a key economic consideration when autoscaling is enabled?

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Multiple Choice

What is a key economic consideration when autoscaling is enabled?

Explanation:
Autoscaling affects cost by aligning resource supply with actual demand and reducing idle capacity. When you enable autoscaling, you should size resources appropriately—set realistic CPU/mMemory requests and limits, and configure sensible minimum and maximum replicas for your workloads—so you’re not paying for more than you need. It’s also important to scale down or shut off unused resources when demand drops, which directly lowers spend. This is why managing costs through proper sizing and decommissioning or scaling down idle resources is the strongest takeaway. It’s not accurate to say costs are unchanged by autoscaling, since scaling decisions change how many pods or nodes run. It’s also not accurate to claim zeros waste or that only memory matters; autoscaling typically responds to metrics like CPU and memory usage and relies on proper sizing to truly optimize cost.

Autoscaling affects cost by aligning resource supply with actual demand and reducing idle capacity. When you enable autoscaling, you should size resources appropriately—set realistic CPU/mMemory requests and limits, and configure sensible minimum and maximum replicas for your workloads—so you’re not paying for more than you need. It’s also important to scale down or shut off unused resources when demand drops, which directly lowers spend.

This is why managing costs through proper sizing and decommissioning or scaling down idle resources is the strongest takeaway. It’s not accurate to say costs are unchanged by autoscaling, since scaling decisions change how many pods or nodes run. It’s also not accurate to claim zeros waste or that only memory matters; autoscaling typically responds to metrics like CPU and memory usage and relies on proper sizing to truly optimize cost.

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