EC2 Auto Scaling Calculator
Compute the desired Auto Scaling capacity from a target-tracking policy and see how long a full scale-out takes.
Inputs
Launch plus bootstrap plus the time before the instance serves at full capacity.
Desired Capacity
18
Usable Capacity per Instance
280requests/s
Spare Capacity at Desired Size
2,400requests/s
Utilisation at Desired Size
66.7%
Time to Reach Desired Size
1,920seconds
Maximum Size Check
The maximum size has room above the desired capacity
Step by step
Values used
Offered load = 4,800 requests/s; Capacity of one instance at 100% = 400 requests/s; Target tracking utilisation = 70 %; Minimum group size = 2 instances; Maximum group size = 20 instances; Instance warm-up = 180 seconds; Instances added per scaling activity = 2 instances
EC2 Auto Scaling
desired = ceil(load ÷ (capacity per instance × target utilisation)), clamped to the group's minimum and maximum.
Desired Capacity
= 18
Usable Capacity per Instance
= 280 requests/s
Spare Capacity at Desired Size
= 2,400 requests/s
Utilisation at Desired Size
= 66.7
Time to Reach Desired Size
= 1,920 seconds
Maximum Size Check
= The maximum size has room above the desired capacity
How it works
Target tracking behaves like a thermostat: it solves for the instance count that puts the chosen metric back on its set point, which is load divided by the usable capacity per instance. The scale-out time matters just as much — each activity adds a step of instances and then waits out the warm-up before the next evaluation, so a large gap between minimum and desired is crossed in several slow rounds rather than one jump. Setting a target too high leaves no absorption for the warm-up window, so traffic that arrives faster than instances boot causes errors even though the policy is technically correct.
Formula
EC2 Auto Scaling
desired = ceil(load ÷ (capacity per instance × target utilisation)), clamped to the group's minimum and maximum.
- target
- Target-tracking set point, e.g. 70% of instance capacity
- capacity per instance
- Throughput one instance sustains at 100%
- warmup
- Seconds before a new instance counts toward capacity
Frequently Asked Questions
How is EC2 Auto Scaling calculated?
desired = ceil(load ÷ (capacity per instance × target utilisation)), clamped to the group's minimum and maximum. Target tracking behaves like a thermostat: it solves for the instance count that puts the chosen metric back on its set point, which is load divided by the usable capacity per instance. The scale-out time matters just as much — each activity adds a step of instances and then waits out the warm-up before the next evaluation, so a large gap between minimum and desired is crossed in several slow rounds rather than one jump.
Why does EC2 Auto Scaling matter?
Setting a target too high leaves no absorption for the warm-up window, so traffic that arrives faster than instances boot causes errors even though the policy is technically correct.
What values do I need to enter?
This calculator takes 7 inputs: Offered load, Capacity of one instance at 100%, Target tracking utilisation, Minimum group size, Maximum group size, Instance warm-up, Instances added per scaling activity. The pre-filled defaults are a realistic starting point — replace them with figures from your own environment for a result you can act on.
Why add 60 seconds per scaling round?
CloudWatch alarms for target tracking evaluate on one-minute metrics, so even after the warm-up expires the group waits for the next evaluation period before it acts again. The extra minute approximates that detection lag.
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