Reserved Instances vs. Savings Plans: What's the Difference?

If you manage a cloud budget, you've seen these terms on invoices and in optimization recommendations: reserved instances, savings plans, committed use discounts. They all promise lower rates in exchange for commitment. But they work differently, apply to different services, and carry different risks.

This guide explains what each instrument is, how pricing works, and where the flexibility tradeoffs are — written for finance and procurement buyers who need to understand the economics, not the API calls.

Reserved instances

A reserved instance (RI) is a commitment to use a specific type of cloud resource — a particular instance family, size, region, and operating system — for a one-year or three-year term. In exchange, you pay a discounted rate, typically 30–60% below on-demand pricing depending on the term and payment option.

How pricing works

RIs are priced in three payment models:

• All upfront:You pay the entire term cost at purchase. This gives the deepest discount (often 40–60% off on-demand).
• Partial upfront: You pay a portion at purchase and a reduced hourly rate for the term. Discount is slightly less than all upfront.
• No upfront:No upfront payment, but a committed hourly rate for the term. Discount is the smallest of the three options (typically 30–40% off).

Flexibility

Standard RIs are locked to a specific instance type in a specific region. Convertible RIs (available on AWS) allow you to change the instance family, operating system, or tenancy during the term — but the process is manual, and conversions can only move to equal or greater value commitments.

Azure Reservations work similarly, covering specific VM sizes in specific regions, with the option to exchange or refund under certain conditions.

Which clouds offer them

• AWS: EC2 Reserved Instances, RDS Reserved Instances, ElastiCache Reserved Nodes, Redshift Reserved Nodes, and others.
• Azure: Azure Reservations for VMs, SQL Database, Cosmos DB, Azure Synapse, and more.
• GCP:Committed Use Discounts (CUDs) for Compute Engine and Cloud SQL. GCP's model is spend-based rather than instance-based.

Savings plans

Savings plans are a newer instrument (AWS introduced them in 2019) that offers more flexibility than reserved instances. Instead of committing to a specific instance type, you commit to a dollar amount of usage per hour. Any usage that falls under the committed amount gets the discounted rate.

How pricing works

You commit to a consistent amount of usage measured in dollars per hour (e.g., $10/hour). All eligible usage up to that amount is billed at the savings plan rate. Usage above that amount is billed at on-demand rates. Terms are one year or three years, with the same payment options as RIs (all upfront, partial, or no upfront).

Flexibility

This is the key differentiator. AWS offers two types:

• Compute Savings Plans: Apply across any EC2 instance family, size, region, operating system, or tenancy. Also cover Fargate and Lambda usage. This is the most flexible option.
• EC2 Instance Savings Plans: Apply to a specific instance family in a specific region, but are flexible on size, OS, and tenancy. Slightly deeper discounts than Compute Savings Plans in exchange for less flexibility.

Azure's equivalent is the Azure Savings Plan for Compute, which works similarly to AWS Compute Savings Plans — committing a dollar-per-hour amount that applies across VM families and regions.

GCP does not have a direct savings plan equivalent. Their Committed Use Discounts serve a similar purpose but are structured differently (resource-based or spend-based commitments).

The tradeoffs

Discount depth vs. flexibility

Reserved instances typically offer deeper discounts than savings plans for the same term and payment option. The tradeoff is rigidity: if your workload changes, an RI may not cover the new usage. Savings plans sacrifice a small amount of discount depth for the ability to follow your usage wherever it goes.

Simplicity vs. precision

Savings plans are simpler to purchase and manage because you're not specifying instance types. But that simplicity means less control over exactly which workloads get covered and at what rate. For companies with stable, predictable workloads, RIs can be more cost-effective. For companies with dynamic environments, savings plans reduce the risk of mismatch.

Term length as the real risk

Both instruments share the same fundamental risk: you're committing for one or three years. If your usage drops, shifts to a different service, or moves to a different cloud, you're still paying for the commitment. This is why most companies undercommit — the downside of getting it wrong feels worse than the cost of paying on-demand rates for uncovered usage.

Why most companies undercommit

The structural problem with both RIs and savings plans as self-service instruments is that the risk of over-commitment paralyzes decision-making. Common patterns we see:

• Teams buy RIs for only the most stable workloads and leave everything else on-demand — resulting in 40–50% coverage.
• Finance requests a “conservative” savings plan commitment that covers 60% of current usage, leaving 40% at full price.
• Existing RIs expire and nobody notices for weeks or months because there's no automated alerting.
• Multi-cloud environments mean managing two or three separate instrument portfolios, each with different mechanics and different review cadences.

The result is that the average self-managed coverage rate across mid-market companies is 40–60%. That means 40–60% of eligible spend is paying on-demand rates — a premium of 30–60% above what it could be.

Where managed services change the equation

Cloudsaver's Managed Discountsservice addresses the structural problems with self-managing these instruments. Instead of choosing between RIs and savings plans and hoping you picked the right one, the service selects the optimal instrument for each workload — including non-standard instruments with 30-day terms that aren't available through self-service.

Thirty-day terms eliminate the commitment risk that causes undercommitment. Continuous rebalancing means coverage adjusts with your usage, not three months after it changes. And multi-cloud management means one service handles AWS, Azure, and GCP instead of three separate optimization efforts.

Understanding the instruments is the first step. Seeing how they apply to your specific environment is the next one. A free savings assessmentshows your current coverage, identifies the gaps, and models what optimal coverage would look like — no commitment required.