System Capacity Planner

Plan overall CPU, memory and storage capacity needed to support projected system growth.

About System Capacity Planner

A server's overall capacity headroom is only as good as its most constrained resource — even if CPU, disk and network all have plenty of room, a server pinned at 95% memory utilization is effectively out of capacity. This calculator therefore scores overall capacity as 100 minus the highest of the four utilization percentages, and explicitly names that highest-utilization resource as the bottleneck, since that is the one that needs attention (or additional capacity) before any of the others.

Formula

Capacity score

score = 100 − max(cpu%, memory%, disk%, network%)

c: CPU utilization %
m: memory utilization %
d: disk utilization %
n: network utilization %

Worked example

With the default values below, System Capacity Planner returns Overall Capacity Score of 22.0. Change any input above and every figure here is recalculated in your browser.

Inputs used

CPU Utilizationaccepts 0–100 %: 65 %
Memory Utilizationaccepts 0–100 %: 78 %
Disk Utilizationaccepts 0–100 %: 55 %
Network Utilizationaccepts 0–100 %: 40 %

Results

Overall Capacity Score: 22.0
Bottleneck Resource: Memory
Bottleneck Utilization: 78.0%
Status: Healthy — ample headroom across all resources

Step by step

1Values used
2Capacity score
3Overall Capacity Score= 22.0
4Bottleneck Resource= Memory
5Bottleneck Utilization= 78.0
6Status= Healthy — ample headroom across all resources

Assumptions and limits

The result is derived only from the 4 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 1 decimal place, 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

Why use the maximum instead of an average of the four metrics?

Averaging would hide a critical single-resource bottleneck behind three healthy metrics — a server can be functionally out of capacity even with low average utilization if just one resource (commonly memory or disk) is pinned near 100%, so the true constraint is always the highest individual figure.

What should I do once I identify the bottleneck resource?

Address that specific resource first — add RAM or tune memory-hungry services if memory is the bottleneck, expand or clean up storage if disk is the constraint, and so on — since improving non-bottleneck resources provides no additional real-world capacity until the bottleneck itself is resolved.

How often should these utilization percentages be measured?

Use sustained averages over a representative window (an hour or a business day) rather than instantaneous snapshots, since brief spikes are normal and don't necessarily indicate a capacity problem — most monitoring systems track p95 or similar percentiles over rolling windows for exactly this reason.