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Pricing Models & Commitments

Choosing how you pay for compute. You compare On-Demand, Spot, Savings Plans, and Reserved Instances, weigh flexibility against discount, and decide when rightsizing or an architecture change beats a commitment.

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questions

6

AWS bills EC2 compute at On-Demand rates by default. What are the main ways to pay less for the same compute, and what does each one ask of you in return?

level: juniorimportance: must knowfreq 76%

answer

  1. Three axes, not one ladder
  2. Each discount buys a transferred risk
  3. Demand risk versus interruption risk
  4. Commitment is a floor on the bill
  5. Layer over the usage trough

basics

~20 s

Three purchase axes exist. On-Demand pays the list rate for total flexibility. Commitments — Savings Plans or Reserved Instances — trade a one- or three-year pledge for a large discount. Spot buys spare capacity cheaply, but AWS can reclaim it.

solid answer

~50 s

There are three ways to pay for AWS compute, and they trade discount against a different kind of freedom. **On-Demand** is the list rate: no commitment, start and stop whenever, and you pay the most per hour. **Commitments** — Savings Plans and Reserved Instances — ask you to promise one or three years of usage in exchange for a discount that can approach two-thirds off On-Demand; the bill arrives whether or not you actually run the workload, so the risk you take on is demand risk. **Spot** sells AWS's spare capacity at a deep discount, but the capacity can be taken back, so the risk you take on is interruption risk. In practice a mature account layers them: commitments cover the always-on baseline, Spot absorbs interruptible batch and scale-out capacity, and On-Demand handles the unpredictable remainder.

go deeper

for a junior

Be able to name On-Demand, commitment-based pricing (Savings Plans and Reserved Instances) and Spot, and say in one sentence what each costs you in flexibility. Do not claim a commitment can be cancelled.

for a middle

Explain that the discount pays you for taking a risk off AWS — demand risk for commitments, interruption risk for Spot — and that a commitment is a floor on your bill regardless of what you run.

for a senior

Show how you would layer the three over a real usage graph: commit to the trough, Spot the interruptible tier, leave the spiky remainder On-Demand, and rightsize before you lock anything in.

for a principal

Own the position that a multi-year commitment is a financial instrument against a technical roadmap. Be ready to say how you keep a commitment portfolio from constraining architectural change, and who signs off on it.

## The three axes AWS compute pricing is not a ladder of tiers; it is three independent ways of buying the *same* underlying capacity. Each buys a discount by taking a specific risk off Amazon's hands and putting it on yours. ## On-Demand: the list rate On-Demand is what you pay if you do nothing. You launch an instance, you are billed for the time it runs (per second, with a one-minute minimum, for most Linux instances), and you stop being billed when you terminate it. Nothing is promised in either direction: you can walk away at any moment, and AWS charges the published rate for the region, instance type and operating system. On-Demand is the correct answer more often than cost-conscious engineers admit. Workloads that run for a few hours a week, environments that may be deleted next quarter, and anything whose shape you cannot yet predict all belong here. Buying a discount on capacity you later stop using is a loss, not a saving. ## Commitments: you take the demand risk A commitment is a promise about the future. Two products implement it: - A **Savings Plan** commits you to a fixed dollar amount of compute usage per hour — say $12/hour — for one or three years. Any eligible usage up to that amount is billed at discounted rates; usage above it falls back to On-Demand. - A **Reserved Instance** commits you to a specific instance configuration (family, region, platform) for one or three years, and discounts matching usage. Both come with payment options — All Upfront, Partial Upfront, No Upfront — where paying more of it in advance buys a slightly deeper discount. The essential property is that the commitment is a *floor on your bill*: if your usage falls below the committed amount, you still pay it. That is exactly why the discount exists. You have taken the demand risk away from AWS, and AWS pays you for it. Commitments also do not, by themselves, guarantee that capacity will be available when you ask for it. A Savings Plan is purely a billing instrument. ## Spot: you take the interruption risk Spot sells capacity AWS is not currently selling at On-Demand rates, at a discount that is typically the deepest of the three. The price of that discount is that AWS can reclaim the instance when it needs the capacity back. Spot therefore belongs to workloads that can be interrupted and retried — batch processing, CI runners, stateless scale-out fleets behind a queue — and never to a single stateful instance you cannot afford to lose. (The mechanics of interruption handling belong with EC2 purchase options; here Spot matters as the third pricing axis.) ## How they layer The experienced answer is that these are not alternatives to choose between once, but layers stacked over a usage graph: 1. Plot hourly compute usage over a representative period. 2. The flat *trough* — the amount you are certain to consume every hour of every day — is the commitment target. 3. Interruptible work above the trough goes to Spot. 4. What is left, the spiky and unpredictable part, stays On-Demand. That ordering also explains a common mistake in reverse: commitments are a discount on the architecture you have, so if a workload is oversized, idle overnight, or about to be rewritten, fixing that first lowers the baseline you are about to commit to for three years. ## Order of application A useful detail: discounts are applied automatically at billing time, not selected at launch. You do not launch a "Savings Plan instance" — you launch an instance, and AWS matches your commitments and reservations against the usage on the bill. That is why a commitment purchased in one account can benefit usage elsewhere in the same billing family, and why a badly targeted commitment silently attaches to whatever usage it matches rather than failing loudly. ## What interviewers are listening for They want to hear that the discount is compensation for a transferred risk, and that you can name which risk each option transfers. A candidate who says "Reserved Instances are cheaper, so use those" has skipped the entire question. A candidate who says "commit to the baseline, Spot the interruptible tier, On-Demand the rest, and rightsize before committing" has answered it.

  • If a Savings Plan is a billing construct, what actually guarantees you can launch the instances you committed to?
    Nothing in the Savings Plan does. It only discounts usage that occurs. If you need assurance that capacity exists in a specific Availability Zone, you buy an On-Demand Capacity Reservation, which reserves capacity and is itself billed — and that billed capacity can then be discounted by a matching Savings Plan or Reserved Instance. Zonal Reserved Instances also carry a capacity reservation; regional ones do not.
  • Why is On-Demand sometimes the right answer even for a workload that runs continuously?
    Because the commitment is one or three years, not the workload's expected life. If the service is likely to be re-architected, moved to a different compute model, or retired inside that window, a three-year commitment converts a future saving into a locked-in loss. Short-lived certainty argues for a one-year term or no commitment at all.
  • How would you decide the dollar amount to commit to?
    Take hourly compute spend over a representative window, find the level that is exceeded essentially all the time — the trough, not the average and never the peak — subtract usage you plan to move to Spot or delete, and commit at or slightly under that. Committing to the average guarantees hours where you pay for capacity you are not consuming.

saying these in an interview costs you the question

  • Says a Savings Plan reserves capacity as well as discounting it
  • Assumes a commitment can be cancelled if usage drops
  • Treats Spot as simply a cheaper On-Demand
  • Commits to peak or average usage instead of the baseline
  • Buys a three-year commitment before rightsizing the fleet

context

open as a page

Compare an AWS Compute Savings Plan with an EC2 Instance Savings Plan: what does each one commit you to, and what flexibility do you give up for the deeper discount?

level: middleimportance: must knowfreq 64%

basics

~20 s

Both commit a fixed dollar-per-hour spend for one or three years. A Compute Savings Plan applies to EC2 in any family or region and also to Fargate and Lambda. An EC2 Instance Savings Plan is locked to one instance family in one region and discounts more deeply.

open as a page

Savings Plans have largely replaced Reserved Instances for new AWS EC2 commitments. What can a Reserved Instance still do that a Savings Plan cannot, and when would you buy a standard rather than a convertible RI?

level: middleimportance: should knowfreq 52%

basics

~20 s

Reserved Instances can reserve capacity when scoped to an Availability Zone, can be exchanged if convertible, and can be sold on the Reserved Instance Marketplace if standard. Savings Plans do none of these — and services such as RDS and ElastiCache still only offer reserved instances.

open as a page

Finance reports that your AWS Savings Plans utilization is 100% but coverage is around 40%. What do those two numbers measure, and what does that combination tell you to do next?

level: seniorimportance: should knowfreq 45%

basics

~20 s

Utilization is the share of your committed hourly spend that eligible usage actually consumed; coverage is the share of eligible compute usage that a commitment discounted. Full utilization with low coverage means the commitment is sound but too small — most compute is still billing at On-Demand rates.

open as a page

Your company wants a multi-year AWS compute commitment, but the fleet is mid-migration to containers and part of it is moving to a different instance architecture. How do you decide what to commit to, and for how long?

level: principalimportance: should knowfreq 34%

basics

~20 s

Commit only to the part of the baseline that survives every plausible roadmap outcome, prefer Compute Savings Plans because they follow workloads across families and into Fargate and Lambda, ladder shorter terms over the uncertain portion, and buy in tranches rather than one irreversible purchase.

open as a page

A manager wants to buy a three-year AWS Savings Plan immediately to cut the EC2 bill. Why should rightsizing and a Graviton evaluation happen first, and what does AWS Compute Optimizer contribute?

level: seniorimportance: nice to knowfreq 38%

basics

~20 s

A commitment discounts the fleet you have, so buying first locks in three years of existing waste. Rightsizing and moving eligible workloads to cheaper Graviton instance types lower the baseline first; AWS Compute Optimizer supplies the per-resource evidence for those changes.

open as a page