Reserved Instances and Savings Plans
Last updated 2026-06-04
Reserved Instances (RIs) and Savings Plans are commitment-based pricing models that grant a significant discount in exchange for committing to a level of usage over a one or three year term. Reserved Instances apply to specific instance families or configurations, so the discount only lands when running resources match the reservation's attributes (instance type, region, and sometimes operating system or tenancy). Savings Plans (on AWS) and Committed Use Discounts (on Google Cloud) instead commit to a steady dollar-per-hour or resource amount, which the discount applies to automatically across matching usage, giving more flexibility as workloads change. Both can be paid all upfront, partial upfront, or no upfront, with deeper discounts for larger commitments. They suit steady-state, predictable workloads but require careful coverage analysis to avoid over-committing (paying for capacity you do not use) or under-committing (paying on-demand rates). LevelFour analyzes commitment coverage and surfaces RI, Savings Plan, and Committed Use Discount gaps as part of its optimization recommendations.
Frequently asked questions
- What is the difference between Reserved Instances and Savings Plans?
- Reserved Instances discount specific instance configurations, so the discount only applies when running resources match the reservation's family, region, and similar attributes. Savings Plans commit to a steady dollar-per-hour spend and apply that discount automatically across matching compute usage, making them more flexible when workloads shift between instance types or sizes.
- When should you buy a commitment instead of paying on-demand?
- Commitments suit steady-state, predictable workloads that run continuously enough to recover the one or three year obligation. Run coverage analysis first: commit to your reliable baseline usage and leave variable or short-lived workloads on on-demand. Over-committing wastes money on unused capacity; under-committing leaves steady workloads paying full on-demand rates.
LevelFour automates this across AWS, GCP, Azure, and Kubernetes with automated infrastructure-as-code pull requests.