Run your Kubernetes workloads on auto-pilot

The ScaleOps platform simplifies Kubernetes resource management by automatically adjusting nodes and pods to match real-time demand.

Designed and developed with DevOps in mind

Continuous & Automatic Pod Rightsizing

Automatically adjusts CPU and Mem requests of Kubernetes pods during runtime.
Significantly reduce compute costs and eliminate OOM and CPU throttling by dynamically scaling resources according to workloads needs.

Optimal Node Utilization

Automatically optimize Kubernetes nodes and boost cluster efficiency by consolidating pods onto more suitable nodes and removing unnecessary ones.

Workload-Based Scaling Policies

Select from multiple pre-defined scaling policies that match your workload needs, accelerate your time to value and start saving in minutes.

Simplified Cost Visibility

Easily analyze cluster costs, set alerts for budget deviations, with a simplified cost showback dashboard.

Your workloads, for 80% less

Disclaimer: a 30-minute demo might blow your mind

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30 day free trial

The Bottom Line

The right compute at the right time

Worry less about your cloud infrastructure

Easy and simple to use

Give engineers their time back with automation that works 24/7

Maximize DevOps productivity

Onboard in minutes, and start saving immediately


What level of automation does the platform provide?

ScaleOps was developed to eliminate the need for any manual configuration, so engineers can put their workloads on auto-pilot and achieve the most optimal utilization of compute resources.

Is ScaleOps secured?

ScaleOps is not a SaaS platform, it is a light agent installed locally on the Kubernetes cluster, so all the data is stored locally.

Can ScaleOps integrate with Open-source auto-scalers?

Yes! ScaleOps seamlessly integrates with Karpenter, Cluster auto-scaler, HPA, or Keda to deliver that extra layer of optimization.