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  • Determine vCPU consumption
  • In-app
  • Observability tools
  1. PerfectScale trial

How to find your allocated vCPU?

Learn how to retrieve the number of CPU Units per Kubernetes node to find your perfect license

PreviousPerfectScale trialNextPerfectScale Prometheus Exporter

Last updated 1 month ago

To provide a more accurate cost metric and improve pricing transparency, the PerfectScale solution is licensed by the amount of vCPU/h your clusters consume monthly.

If your usage remains under 10K vCPU/h per month during your trial, you will be automatically converted to the free community package. Learn more about the Pricing model .

Determine vCPU consumption

There are a few ways to determine your vCPU consumption:

In-app

Navigate to your Subscription Details and check the that PerfectScale has already calculated for you. To get more details and review vCPU consumption over-time run a following two easy steps:

  • Go to the Trends tab

  • Select 'Allocated vCPU' in the Scope drop-down list.

Observability tools

With your observability tool, like Grafana and DataDog you can either use some existing dashboard or create a new graph summarizing cluster capacity. For example, Prometheus can be used to create a visualization of cluster capacity, as shown below:

    SUM(kube_node_status_capacity{resource="cpu", unit="core"})

In the above example, the allocated vCPU is around 90 cores. We can estimate monthly core hours as 90*24*30 = 64800

Use the terminal following the guide below:

  • Open a new terminal on the machine that has kubectl been installed. Make sure you are running in the correct context (=cluster)

  • Type the following command on the prompt:

kubectl get nodes -o custom-columns=NAME:'{.metadata.name}',CORES:'{.status.capacity.cpu}'

This will show you the currently running instances and their core capacity at a single point in time:

NAME                                             CORES
ip-10-107-0-11.eu-central-1.compute.internal     2
ip-10-107-12-213.eu-central-1.compute.internal   2
ip-10-107-24-124.eu-central-1.compute.internal   8
ip-10-107-24-142.eu-central-1.compute.internal   2
ip-10-107-26-193.eu-central-1.compute.internal   2
ip-10-107-31-30.eu-central-1.compute.internal    8
ip-10-107-32-253.eu-central-1.compute.internal   4
ip-10-107-32-47.eu-central-1.compute.internal    4
ip-10-107-37-121.eu-central-1.compute.internal   2
ip-10-107-4-114.eu-central-1.compute.internal    2
ip-10-107-40-28.eu-central-1.compute.internal    4
ip-10-107-45-210.eu-central-1.compute.internal   2
ip-10-107-47-136.eu-central-1.compute.internal   2
ip-10-107-47-184.eu-central-1.compute.internal   4
ip-10-107-7-175.eu-central-1.compute.internal    4
ip-10-107-7-204.eu-central-1.compute.internal    2
  • Now you can summarize the cores to have cluster cores right now. You can multiply this number by 24*30 to have a monthly estimate.

If your cluster has a dynamic nature, this approach may be less accurate than Observability tools or PerfectScale.

here
trends report
In the PerfectScale platform
In your observability tool
Current Month vCPU Consumption
vCPU/hours in the trends report
vCPU/hours in the observability tool