Pelanor’s Kubernetes sensor delivers granular cost allocation for every cluster, namespace, workload, and even individual network endpoint.

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Key Capabilities

  • Cost by namespace & workload – CPU, memory, storage, and network
  • Network cost attribution – cluster → namespace → workload → endpoint
  • eBPF-powered traffic mapping
    • DNS – map cloud resources (e.g., ALB, RDS) to workloads
    • HTTP – link workloads to S3 buckets / object stores
    • SQL – attribute database queries to the calling pods

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Architecture Overview

A lightweight DaemonSet runs on each node. Using eBPF plus the Kubernetes API it gathers:
Data collectedPurpose
K8s object state (namespaces, deployments, pods, etc.)Identity & ownership
Pod/container CPU & memory requests & usageCost & right-sizing
Per-pod network statisticsInternal vs external traffic
DNS, HTTP, SQL tracesResource → workload mapping
The DaemonSet consumes ~50 MB memory and < 2% CPU per node. It captures only metadata, never payloads.

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Installation

After signing in to Pelanor, go to Integrations → Kubernetes and copy the pre-filled Helm command. 
helm repo add pelanor https://assets.pelanor.io/v1/charts

helm install pelanor pelanor/pelanor \
  --create-namespace -n pelanor \
  --set clusterName=<CLUSTER_NAME> \
  --set deployKey=<DEPLOY_KEY> \
  --set ingress=https://ingress.pelanor.io

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Required values

ParameterNotes
deployKeyUnique per Kubernetes integration. Create one per cluster for better status tracking, or reuse if desired.
clusterNameHuman-readable & unique. For EKS, the cluster ARN works well.
clusterName must be unique across all clusters in your tenant; duplicates will merge data.

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Troubleshooting

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Helm chart installed but some pods are not scheduled

1

Check for taints

Ensure pods aren’t unschedulable due to node taints (configure tolerations if needed).
2

Verify node resources

Confirm that all nodes have enough available CPU and memory to schedule the Pelanor pods.