OpenCost vs Kubecost — Which Kubernetes Cost Tool Should You Actually Run?

The confusing part of this comparison is that they're not really competitors — Kubecost donated the core cost-allocation engine to the CNCF as OpenCost, then kept building a commercial product on top of it. Understanding what's in the free core versus what's gated behind Kubecost's paid tiers is the actual question worth answering.

What OpenCost Gives You for Free

helm repo add opencost https://opencost.github.io/opencost-helm-chart
helm install opencost opencost/opencost --namespace opencost --create-namespace

Once running, OpenCost exposes cost allocation per namespace, deployment, pod, and label — pulling real cloud billing data (via AWS Cost and Usage Reports, GCP billing export, or Azure cost management) and mapping it to actual Kubernetes resource consumption.

# Query cost breakdown directly via the API
curl "http://localhost:9003/allocation/compute?window=7d&aggregate=namespace"

{
  "production": {
    "cpuCost": 142.50,
    "ramCost": 89.30,
    "gpuCost": 0,
    "pvCost": 12.40,
    "networkCost": 8.10,
    "totalCost": 252.30
  }
}

This core functionality — accurate per-namespace/pod/label cost allocation, idle cost detection, and a Grafana dashboard integration — is genuinely complete and free, no catch.

What Kubecost's Paid Tiers Add

Multi-cluster aggregation with a unified dashboard. OpenCost gives you cost data per cluster; if you run 10 clusters, you're querying 10 separate OpenCost instances unless you build the aggregation yourself. Kubecost's paid tiers do this natively.

Savings recommendations engine. Kubecost analyzes your actual usage patterns and recommends specific rightsizing actions — "this deployment requests 2 CPU but uses 200m on average, reduce to 500m" — with estimated savings attached. OpenCost shows you the cost; Kubecost's paid product tells you what to do about it.

Governance and budget alerts with approval workflows. Setting spend thresholds per team/namespace with Slack alerts and (in higher tiers) actual budget enforcement integrations.

Audit-ready reporting and chargeback exports. If finance needs a clean, auditable showback/chargeback report per team for internal billing, Kubecost's reporting layer is built for that; OpenCost gives you the raw data, you build the report.

SSO, RBAC, and enterprise support. Standard enterprise-tier gating — fine if you need it, irrelevant for most teams under ~50 engineers.

Side-by-Side

A Practical Setup That Costs Nothing

For teams under 5-10 clusters who mainly want visibility (not automated governance), you can get most of the value for free by combining OpenCost with your existing Grafana:

# Grafana dashboard panel querying OpenCost directly
- title: "Cost by Namespace (7d)"
  targets:
    - expr: opencost_namespace_cost_total
      legendFormat: "{{namespace}}"
  type: piechart

# Simple weekly Slack report using OpenCost's API — replaces 
# the chargeback reporting feature for teams that just need a number, not a polished PDF
import requests
 
def weekly_cost_report():
    resp = requests.get("http://opencost.opencost:9003/allocation/compute",
                         params={"window": "7d", "aggregate": "namespace"})
    data = resp.json()["data"][0]
    
    sorted_costs = sorted(data.items(), key=lambda x: x[1]["totalCost"], reverse=True)
    report = "\n".join(f"{ns}: ${cost['totalCost']:.2f}" for ns, cost in sorted_costs[:10])
    
    requests.post(SLACK_WEBHOOK, json={"text": f"Top 10 namespaces by cost (7d):\n{report}"})

This covers the "visibility" half of FinOps for free. What it doesn't replace is the recommendation engine and multi-cluster rollup — those genuinely require either Kubecost's paid product or meaningful engineering time to build yourself.

Honest Recommendation

Start with OpenCost, always. There's no reason to pay for cost visibility when the CNCF project gives it to you free and it's the same underlying engine.

Move to Kubecost paid tiers when: you're running enough clusters that manual multi-cluster aggregation becomes a real time sink, or when you need the rightsizing recommendation engine because manual analysis isn't scaling with your cluster count, or when finance specifically needs audit-ready chargeback reports you don't want to build yourself.

For most teams under 20-30 engineers running a handful of clusters, OpenCost plus a couple of custom Grafana panels and a Slack cron job covers 80% of what FinOps actually requires day to day.

Build the rightsizing logic yourself: Build a Kubernetes Cost Optimizer with Claude API + Prometheus