
Rex says
Money math without the spreadsheet headache. Plug in your numbers and I'll show you exactly where the dollars land.
Try a scenario
Click to load — tweak from there.Inputs
Result
Nodes needed
13
Pods per node
16
Estimated monthly node cost
$3,644.16
Bottleneck resource
CPU
Unused CPU per node
0.0%
Unused memory per node
50.0%

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How to use this
- 1Enter node allocatable cpu (vCPU).
- 2Enter node allocatable memory (GB).
- 3Enter pod cpu request (vCPU).
- 4Enter pod memory request (GB).
- 5Enter total pods to schedule.
- 6Enter node hourly cost ($).
- 7Read your nodes needed on the right — it updates as you type.
- 8Hit Share to keep the scenario or send it to someone.
About this calculator
Kubernetes scheduling is a bin-packing problem: each node has a fixed amount of allocatable CPU and memory (slightly less than total, after reserving capacity for the kubelet and system daemons), and each pod requests a slice of both. This calculator computes how many pods fit per node based on whichever resource — CPU or memory — runs out first, then divides your total pod count by that packing density to estimate node count, and multiplies by node hourly cost for a monthly estimate. It also reports the 'wasted' capacity on the bottleneck resource, which is almost always non-zero because pod requests rarely divide evenly into node capacity. This is the same math cluster autoscalers use internally, and knowing it helps you size instance types deliberately — sometimes a slightly larger node type packs more efficiently and lowers total node count and cost even though its hourly price is higher.
Worked example
Using the values the calculator loads with:
Inputs
- Node allocatable CPU: 8 vCPU
- Node allocatable memory: 32 GB
- Pod CPU request: 0.5 vCPU
- Pod memory request: 1 GB
- Total pods to schedule: 200
- Node hourly cost: 0.384 $
Results
- Nodes needed: 13
- Pods per node: 16
- Estimated monthly node cost: $3,644.16
- Bottleneck resource: CPU
- Unused CPU per node: 0.0%
- Unused memory per node: 50.0%
What each field means
Inputs
- Node allocatable CPU (vCPU)
- The node allocatable cpu used in the calculation, measured in vCPU. Starts at 8 vCPU so you have a working example on load.
- Node allocatable memory (GB)
- The node allocatable memory used in the calculation, measured in GB. Starts at 32 GB so you have a working example on load.
- Pod CPU request (vCPU)
- The pod cpu request used in the calculation, measured in vCPU. Starts at 0.5 vCPU so you have a working example on load.
- Pod memory request (GB)
- The pod memory request used in the calculation, measured in GB. Starts at 1 GB so you have a working example on load.
- Total pods to schedule
- The total pods to schedule used in the calculation. Starts at 200 so you have a working example on load.
- Node hourly cost ($)
- The node hourly cost used in the calculation, measured in $. Starts at 0.384 $ so you have a working example on load.
Results
- Nodes needed
- Returned as a whole number and shown as the headline result. It recalculates instantly whenever you change an input, so you can compare scenarios without reloading.
- Pods per node
- Returned as a whole number. It recalculates instantly whenever you change an input, so you can compare scenarios without reloading.
- Estimated monthly node cost
- Returned as a money amount in US dollars. It recalculates instantly whenever you change an input, so you can compare scenarios without reloading.
- Bottleneck resource
- Returned as a plain value. It recalculates instantly whenever you change an input, so you can compare scenarios without reloading.
- Unused CPU per node
- Returned as a percentage. It recalculates instantly whenever you change an input, so you can compare scenarios without reloading.
- Unused memory per node
- Returned as a percentage. It recalculates instantly whenever you change an input, so you can compare scenarios without reloading.
FAQ
Why does 'allocatable' matter instead of total node capacity?
Every node reserves a slice of CPU and memory for the kubelet, container runtime, and OS itself before any pods can be scheduled — typically 5-10% of memory and a few hundred millicores of CPU. Cloud providers publish allocatable capacity per instance type separately from raw specs; use that number, not the raw vCPU/RAM spec sheet, or you'll overestimate how many pods actually fit.
Why would a bigger, more expensive node type lower total cost?
Bin-packing waste is per-node, so more nodes means more total wasted capacity. A node type that packs pod requests evenly (little remainder on both CPU and memory) can need fewer total nodes for the same pod count than a cheaper node type that leaves each node with 20-30% stranded capacity, and the fewer-larger-nodes total often costs less overall.
Should I size nodes around requests or actual usage?
The scheduler only sees requests, so bin-packing math always runs on requests, not real usage. But if your requests are set far above real usage (a common anti-pattern), you're paying for stranded capacity that never gets used — audit with a tool like Kubecost or the metrics-server to right-size requests before doing node capacity planning.
Accuracy and limitations
- Results are estimates before tax, fees, and inflation unless an input explicitly covers them.
- Rates are treated as fixed for the whole period — variable-rate products will drift from this projection.
- This is educational maths, not financial advice. Check anything contractual with the lender or your accountant.
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Cite this calculator
Writing about this topic? Grab a citation — every link helps keep these tools free.
RevenueLab. (2026). Kubernetes Node Bin-Packing Calculator. Retrieved from https://www.revenuelab.fyi/toolbox/kubernetes-node-bin-packing
<p>Source: <a href="https://www.revenuelab.fyi/toolbox/kubernetes-node-bin-packing" target="_blank" rel="noopener">Kubernetes Node Bin-Packing Calculator — RevenueLab</a> (2026).</p>
Source: [Kubernetes Node Bin-Packing Calculator — RevenueLab](https://www.revenuelab.fyi/toolbox/kubernetes-node-bin-packing) (2026).
