FinOps in Kubernetes with OpenCost

Kubernetes makes it easy to scale workloads, but it also makes costs… slippery. Pods scale up, nodes scale down (hopefully), and suddenly you get a cloud bill that looks like an unsolved puzzle.

That’s where FinOps (Financial Operations) comes in — a practice of bringing financial accountability to cloud spend. And for Kubernetes clusters, OpenCost is one of the best open-source tools to track and optimize your workloads’ cost.

In this workshop, we’ll set up OpenCost in a Kubernetes cluster, collect cost metrics, and build a Grafana dashboard to visualize them. By the end, you’ll have a working FinOps setup for your K8s workloads.

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FinOps in Kubernetes – Why it Matters

FinOps is not just about saving money — it’s about creating financial visibility, accountability, and optimization across engineering, operations, and finance.

In Kubernetes, costs are tricky because:

• Resources are shared across namespaces, teams, and services.
• Autoscaling makes spend dynamic and unpredictable.
• Cloud bills don’t map neatly to Kubernetes objects (pods, nodes, namespaces).

FinOps helps bridge that gap by answering questions like:

• How much does each team/namespace cost per month?
• Which workloads are over-provisioned?
• What is the cost impact of autoscaling?
• Can we charge back costs to product teams?

Enter OpenCost: the open-source project that measures Kubernetes costs in real-time.

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Prerequisites

Before diving in, make sure you have:

• A running Kubernetes cluster (on-prem or cloud, minikube works too).
• kubectl installed and configured.
• helm (Helm 3).
• Prometheus + Grafana installed in your cluster. (If not, you can install using the Prometheus & Grafana Helm charts.)

Installing OpenCost on Kubernetes

kubectl create namespace opencost

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

This deploys OpenCost as a service inside the cluster.

Verifying OpenCost Installation

Check if pods are running:

kubectl get pods -n opencost

You should see something like:

opencost-xxxxxxx   1/1   Running   0   2m

Exploring the OpenCost UI

OpenCost exposes a built-in UI for visualizing cost allocations in real-time.

Port-forward the OpenCost UI

Run:

kubectl port-forward -n opencost svc/opencost 9000:9090

Now open your browser:

http://localhost:9000

You should see the OpenCost dashboard.

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Integrating OpenCost with Prometheus

OpenCost exposes cost metrics in Prometheus format at:

http://<opencost-service>:9003/metrics

Add a scrape config so Prometheus pulls OpenCost metrics.

Edit your Prometheus config (prometheus.yaml or Helm values):

scrape_configs:
  - job_name: 'opencost'
    honor_labels: true
    static_configs:
      - targets: ['opencost.opencost:9003']

Apply the updated config and restart Prometheus.

Now you can query OpenCost metrics in Prometheus UI.

Adding Custom Pricing in OpenCost

By default, OpenCost uses public cloud list prices (AWS, GCP, Azure) to estimate costs. But in real-world FinOps, you often want to use:

• Discounted rates (Reserved Instances, Savings Plans, enterprise agreements)
• On-prem pricing (your internal cost per vCPU, GB RAM, GB storage)
• Spot instance prices
• Blended costs across regions

OpenCost lets you override default prices with a custom pricing configuration file.

Create a custom pricing config

Create a file named custom-pricing.json:

{
  "description": "Custom pricing for on-prem Kubernetes cluster",
  "CPU": "0.02", 
  "RAM": "0.005", 
  "GPU": "0.95", 
  "storage": "0.0002",
  "zoneNetworkEgress": "0.01",
  "internetNetworkEgress": "0.12"
}

Here’s what the fields mean:

• CPU → price per vCPU per hour (e.g., $0.02/hr)
• RAM → price per GB RAM per hour
• GPU → price per GPU per hour
• storage → price per GB storage per hour
• network egress → per GB network cost

Mount custom pricing in the Helm chart

When installing/upgrading OpenCost with Helm, mount your custom pricing config:

helm upgrade opencost --repo https://opencost.github.io/opencost-helm-chart opencost \
  --namespace opencost \
  --set opencost.customPricing.enabled=true \
  --set-file opencost.customPricing.configMap=custom-pricing.json

Now your cost metrics reflect your actual business costs, not just public cloud pricing. This is critical for accurate chargeback/showback in FinOps.

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FinOps Best Practices in Kubernetes

Now that you have visibility, here’s how to turn data into savings:

Showback & Chargeback

• Attribute costs to namespaces, teams, or applications.
• Create monthly dashboards for finance + engineering.
• Use showback (reporting) or chargeback (actual billing).

Rightsizing Workloads

• Identify workloads requesting more CPU/Memory than needed.
• Use OpenCost + Metrics Server to compare requests vs actual usage.
• Tune resource requests/limits to reduce waste.

Eliminate Idle Resources

• Spot unused PVCs, idle nodes, or old namespaces.
• Set policies for automatic cleanup.

Use Autoscaling Wisely

• Scale workloads up/down with HPA/VPA, but track the cost impact.
• Sometimes autoscaling saves money, sometimes it spikes spend.

Set Alerts

• Use Prometheus + Alertmanager to notify when spend per namespace crosses thresholds.
• Example: “Alert if namespace cost > $500/day”.

Optimize Node Mix

• Compare workloads to spot if GPU nodes or high-memory nodes are underutilized.
• Shift to cheaper node pools when possible.

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Optimize & Automate

Once your FinOps dashboards are live, you can take it further:

• Budgets & Forecasting → align costs with business units.
• Cross-Cluster Costing → monitor multiple clusters at once.
• Integrations with Cloud Billing → map OpenCost data to AWS, GCP, or Azure invoices.

With this, you’re not just observing Kubernetes costs — you’re bringing accountability and efficiency to your platform. That’s true FinOps in action.

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{
    "author"   :  "Kartik Dudeja",
    "email"    :  "[e-mail]",
    "linkedin" :  "https://linkedin.com/in/kartik-dudeja",
    "github"   :  "https://github.com/Kartikdudeja"
}