Reserved Instances vs. Savings Plans: Which One Actually Saves You Money?

Published: 2026-05-20
Author: Saascutters
Read time: 6 minutes
Keywords: AWS reserved instances, AWS savings plans, cloud reservation strategy, compute savings, FinOps reserved capacity

Every cloud provider offers a discount for committing to future usage. AWS calls them Reserved Instances and Savings Plans. Azure calls them Reservations. GCP calls them Committed Use Discounts. The names differ, but the math is the same: commit to one or three years, get 30–72% off on-demand pricing.

The problem: most teams buy the wrong one. Here is how to choose correctly.

Reserved Instances: the old way

AWS Reserved Instances (RIs) are tied to a specific instance family, region, and operating system. A m6i.2xlarge RI in us-east-1 running Linux will not apply to a m6i.2xlarge in us-west-2, nor to a c6i.2xlarge anywhere.

RIs make sense when:

• Your workload is stable and predictable
• You know the exact instance family you need
• You do not plan to change regions

The risk: if your architecture changes — and it always does — your RIs become stranded capacity you are still paying for.

Savings Plans: the flexible way

Savings Plans are AWS's newer, more flexible alternative. They apply to any instance family, any region, any size — as long as the compute usage matches your committed hourly rate. There are two types:

• Compute Savings Plans: Apply to EC2, Fargate, and Lambda. Most flexible.
• EC2 Instance Savings Plans: Tied to a specific family and region. Slightly cheaper but less flexible.

For 90% of teams, Compute Savings Plans are the right choice. The flexibility premium is small — usually 2–5% — and the protection against architectural change is worth it.

Azure and GCP equivalents

Azure Reservations work like AWS RIs: tied to a specific VM family and region. Azure also offers a Hybrid Benefit that stacks on top of Reservations for additional savings on Windows and SQL Server workloads.

GCP Committed Use Discounts (CUDs) are the most flexible of the three. You commit to a certain level of vCPU and memory usage, and the discount applies to any machine type that consumes those resources. You can even apply CUDs to Custom Machine Types.

The commitment trap

The biggest mistake we see: teams commit to three years because the discount is larger, then re-architect within twelve months. The new architecture uses different instance types, different regions, or serverless compute. The old commitment still bills every month.

Our rule: if your workload has been stable for twelve months, commit for one year. If your workload has been stable for thirty-six months, commit for three years. If you are not sure, commit for one year and re-evaluate at renewal.

How to audit your existing commitments

Log into Cost Explorer (AWS), Cost Management (Azure), or Billing (GCP). Check:

• What commitments are active?
• What is the utilization rate?
• Are there unused or underutilized commitments?
• When do they expire?

Set a calendar reminder 60 days before every expiration. That is your window to re-evaluate needs, get competitive quotes, and decide whether to renew, modify, or let expire.

Performance-based help

If your compute bill is over $30,000 per month and you have never audited your reservation strategy, there is almost certainly money on the table. Saascutters analyzes your usage patterns, recommends the optimal commitment structure, and verifies the savings against your on-demand baseline. Thirty percent of verified first-year savings. No retainer. Request a compute audit →