EC2 Fleet Capacity Calculator
Split an EC2 Fleet target capacity into on-demand base and Spot instances, then price the blended result.
About EC2 Fleet Capacity Calculator
A mixed instances policy fills capacity in a fixed order: the on-demand base first, then the on-demand percentage of whatever remains, then Spot for the rest. Expressing the target in vCPUs rather than instances is what lets a fleet substitute a 2xlarge for two xlarges when capacity is scarce, which is exactly the flexibility that keeps Spot interruption rates low. The base is your insurance policy: it is the capacity that survives a complete Spot reclamation event, so it should cover the minimum traffic you must serve rather than being left at zero.
Formula
EC2 Fleet Capacity
instances = ceil(target capacity ÷ capacity per instance); on-demand = base + round((instances − base) × on-demand share); the remainder is Spot.
- base
- Instances always fulfilled on-demand, regardless of the split
- share
- Percentage of capacity above the base bought on-demand
- blended
- Weighted hourly price of the mixed fleet
Worked example
With the default values below, EC2 Fleet Capacity Calculator returns Monthly Fleet Cost of $8,964.40. Change any input above and every figure here is recalculated in your browser.
Inputs used
- Target capacityaccepts 1–1,000,000 vCPU
- 480 vCPU
- vCPUs per instanceaccepts 1–448 vCPU
- 16 vCPU
- On-demand base capacityaccepts 0–10,000 instances
- 2 instances
- On-demand share above the baseaccepts 0–100 %
- 30 %
- On-demand rate per instance-hourminimum 0 USD/hour
- 0.768 USD/hour
- Spot rate per instance-hourminimum 0 USD/hour
- 0.23 USD/hour
- Hours running per monthaccepts 0–744 hours
- 730 hours
Results
- Monthly Fleet Cost
- $8,964.40
- Instances in the Fleet
- 30
- On-Demand Instances
- 10
- Spot Instances
- 20
- Blended Hourly Cost
- $12.28
- Saving vs an All On-Demand Fleet
- 46.7%
Step by step
- 1Values used
- 2EC2 Fleet Capacity
- 3Monthly Fleet Cost= 8,964.40
- 4Instances in the Fleet= 30
- 5On-Demand Instances= 10
- 6Spot Instances= 20
- 7Blended Hourly Cost= 12.28
- 8Saving vs an All On-Demand Fleet= 46.7
Assumptions and limits
- The result is derived only from the 7 inputs listed above. Anything not among them is not part of the calculation.
- In particular, this calculator does not take inflation, tax, fees or charges or compounding frequency into account.
- Figures are rounded for display to 2 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.
How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.
Frequently Asked Questions
How is EC2 Fleet Capacity calculated?
instances = ceil(target capacity ÷ capacity per instance); on-demand = base + round((instances − base) × on-demand share); the remainder is Spot. A mixed instances policy fills capacity in a fixed order: the on-demand base first, then the on-demand percentage of whatever remains, then Spot for the rest. Expressing the target in vCPUs rather than instances is what lets a fleet substitute a 2xlarge for two xlarges when capacity is scarce, which is exactly the flexibility that keeps Spot interruption rates low.
Why does EC2 Fleet Capacity matter?
The base is your insurance policy: it is the capacity that survives a complete Spot reclamation event, so it should cover the minimum traffic you must serve rather than being left at zero.
What values do I need to enter?
This calculator takes 7 inputs: Target capacity, vCPUs per instance, On-demand base capacity, On-demand share above the base, On-demand rate per instance-hour, Spot rate per instance-hour, Hours running per month. The pre-filled defaults are a realistic starting point — replace them with figures from your own environment for a result you can act on.
How many instance types should a fleet allow?
As many as your workload tolerates — practical fleets list 10 or more types across several families and sizes in every AZ. Spot capacity pools are independent, so diversification is the single most effective way to cut interruptions, and the capacity-optimized allocation strategy then picks the deepest pools.
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