Node Groups Recommendations

The Node Groups tab within the Cluster Analysis page provides recommendations for optimizing your Kubernetes node pools. This tab helps you identify opportunities to select more cost-effective instance types while maintaining the capacity your workloads require.

Supported Autoscalers

Akamas Insights supports node group recommendations for clusters using:

• Kubernetes Cluster Autoscaler - The standard autoscaler for Kubernetes clusters;

• Karpenter - A flexible, high-performance node provisioner.

How Node Groups Are Identified

Akamas Insights identifies node groups by reading Kubernetes node labels. The platform automatically detects the appropriate label based on your cloud provider:

• EKS: eks.amazonaws.com/nodegroup

• GKE: cloud.google.com/gke-nodepool

• AKS: agentpool

• Karpenter: karpenter.k8s.aws/instance-family and related labels

Nodes without the expected label are grouped as "Unlabeled Nodes" and can still receive recommendations. You can also select a custom label if your environment uses non-standard node pool identification.

Node Groups Analysis

Cluster Node Groups Tab

The Node groups tab provides recommendations for Kubernetes cluster autoscaler configuration:

Node Pool Configuration:

• Current node pool sizes;

• Recommended minimum and maximum nodes;

• Recommended instance types;

• Cost implications of changes.

Autoscaler Settings:

• Scale-up and scale-down thresholds;

• Resource utilization targets;

• Buffer capacity recommendations.

Adjusting the Recommendation Filters

Each node pool has a Recommendation filters panel that lets you narrow which instance types the engine considers when computing a recommendation.

• The panel header shows an "N / M Instance type matched" badge: how many of the node pool's available instance types satisfy your current filters. It sits next to the Recommendation filters toggle, so you can read it whether the panel is open or collapsed. The badge stays grey while no filter is active (all instance types are considered) and is highlighted once a filter narrows the set.

• Every active filter appears as a removable chip in an ACTIVE row that stays visible even when the panel is collapsed. Click a chip's ✕ to clear that single filter. When no filter is set, the open panel reads "No filters applied. The engine considers all instance types."

• While you have edits that have not yet been saved, the panel offers a way back: use "Reset to last saved" to revert just the Instance properties back to the values that were last applied, or "Discard changes" to revert all of your edits to the last saved state. "Discard changes" and "Save and Apply" stay in the footer at all times and simply enable once you have unsaved edits; the "Reset to last saved" link appears only while you have them.

Filters are saved centrally for the cluster, so applying them updates the recommendation that everyone viewing this cluster sees. To apply your changes, click Save and Apply (available only once you have unsaved changes). A confirmation dialog appears first — confirming saves the filters and recomputes the node groups recommendation, and you'll see a "Filters saved" notification. Nothing is changed for other viewers until you confirm.

Node groups recommendations require additional cluster autoscaler integration and may not be available in all deployments.