Skip to Content
Core InfraReplicas OptimizationWorkloads

Workloads

ScaleOps Replicas Optimization helps you optimize Horizontal Pod Autoscaler (HPA) workloads by analyzing historical patterns and automatically adjusting minimum replica counts to improve resource utilization and reduce costs.

Optimize HPA Workloads

Explore Potential Savings

  • The Predictive HPA Workloads page offers an overview of potential resource cost savings, the number of under-optimized minimum replicas, and predictable workloads identified within the cluster. By reviewing the workloads table, you can identify workloads’ available savings by cost and resources, as well as replicas recommendation.
  • The Workload overview HPA tab provides an over-time visualization of current replicas, recommended replicas, minimum replicas, replicas by triggers, and more. In this tab, you can determine whether a workload is classified as predictable and view the minimum replica calculation method defined in the associated policy.

Automate Workloads

To optimize the workloads, click the Automate Now button. The action will apply to all current and future workloads.

Alternatively, automate specific workloads in the HPA workloads table.


How it works

ScaleOps uses historical metric data to predict the required replicas for the workload. The prediction is used to adjust the minimum replicas for the workloads attached HPA, ensuring that the workload is running with the right number of replicas.

  • For predictable workloads: ScaleOps set the min replicas based on a percentile of the historical usage data. ScaleOps predicts the peak usage and scales up the replicas ahead of the predicted peak.
  • For static workloads: ScaleOps set the min replicas based on a percentile of the historical replicas data. We recommend to set the percentile to max, so the scaling decision is identical to the highest HPA original scale decision, for the configured window.
  • In any case, the minimum replicas recommendation will not be higher than the original minimum replicas.

ScaleOps manage the .spec.minReplicas attribute on the HPA itself for HPA optimization. KEDA ScaledObject is also supported.

Prerequisites & Limitations

  • HPA must be configured on the workload
  • Only Deployment, StatefulSet and Argo Rollout workload types are supported
Replicas OptimizationPolicies