You have adopted Kubernetes. Your teams are now deploying faster, scaling applications easily, and running microservices across different environments. But while your development speed has improved, cost visibility has not kept up.
Running Kubernetes across multiple clusters and cloud platforms adds a new layer of complexity. Resources scale automatically, workloads are shared across nodes, and cloud billing reports show usage but not who used what, why it was used, or how much it cost.
If you’ve ever asked yourself questions like, “Why are we spending more on dev than production?”, or “Who scaled this node group to 100 instances?”, or “Why did our non-production cluster cost more than we planned?”, then it’s time to adopt FinOps.
This blog will walk you through 3 high-impact FinOps strategies for Kubernetes, especially when working with complex multi-cluster and multi-cloud setups.
What is FinOps in Kubernetes and Why It Matters
FinOps stands for Cloud Financial Operations. It helps teams manage cloud costs by bringing together engineering, finance, and operations.
In Kubernetes, FinOps focuses on:
- Making costs visible at the namespace, application, or team level
- Setting limits on CPU, memory, and storage usage
- Helping engineers make cost-aware decisions while deploying workloads
Why is it important?
- Kubernetes resources are shared, so it’s easy to lose track of who’s spending what
- Without visibility, teams can over-provision, scale too fast, or forget to delete unused resources
- FinOps helps control waste and stay on budget
Why FinOps is Critical in Multi-Cluster and Multi-Cloud Kubernetes
When you run Kubernetes across many clusters or clouds:
- Each cloud has different pricing
- Resources can be duplicated
- Tracking spend becomes hard
Without FinOps:
- You get high, unexpected bills
- No clear ownership of cost
- Hard to control and plan budgets
FinOps gives you the visibility and control to stay on track.
Proven FinOps Strategies to Optimize Kubernetes Costs
1. Label Workloads Consistently for Cost Allocation
In Kubernetes, applying consistent labels like team, project, environment, and cost-center to workloads such as pods, deployments, and services enables accurate cost tracking and accountability. Since cloud providers bill at the VM level, labels help map resource usage back to specific teams or projects.
Proper labeling enables
• Cost allocation for showback and chargeback reporting
• Visibility across cost dashboards and monitoring tools
• Policy enforcement using tools like Cloud Custodian to detect missing or incorrect labels, enforce standards, or clean up non-compliant resources
Example:
metadata:
labels:
team: frontend
environment: staging
cost-center: cc-1040
If labels are missing or inconsistent, costs appear as “unallocated,” and it becomes impossible to identify which team is responsible for what spend, leading to poor accountability and wasted budgets.
2. Use Native Billing Exports to Gain Cost Visibility
To manage costs effectively across multiple cloud providers, enable their native billing export tools. These exports provide raw usage and cost data that can be centrally analyzed and correlated with resource labels. This is essential for identifying high-spend areas, detecting anomalies, and generating usage trends across teams and environments.
How to Enable Billing Exports
Centralized Visibility Steps
• Enable billing exports in each cloud account or project
• Standardize label keys across AWS, GCP, and Azure (example: team, env, cost-center)
• Set up scheduled queries or dashboards within Amazon Athena, BigQuery, or Azure Log Analytics
• Monitor label compliance using cloud-native policies like AWS Config, GCP Policy Analyzer, and Azure Policy
• Use this data for showback, chargeback, trend analysis, and anomaly detection
Without billing exports, centralized cost analysis becomes impossible, and you risk blind spots that lead to uncontrolled spending.
3. Centralize Cost Monitoring with OpenCost, Prometheus, and Thanos
For teams running Kubernetes clusters across multiple clouds or environments, it becomes difficult to get a unified view of resource usage and cost. To solve this, you can set up a centralized monitoring stack that aggregates cost metrics from all clusters in one place.
This setup enables real-time and historical cost monitoring across environments, providing true multi-cloud Kubernetes FinOps.
How It Works:
- Deploy Prometheus and OpenCost in each cluster to collect cost and resource metrics.
- Connect each Prometheus to a central Thanos instance to aggregate and store time-series data.
- Use Grafana to visualize metrics and costs across all clusters from a single dashboard.
Labeling Each Prometheus Instance
To ensure each cluster's metrics can be uniquely identified, add a cluster label to each Prometheus deployment. This label helps Thanos and Grafana distinguish data sources and enables filtering by cluster.
# prometheus.yaml
global:
external_labels:
cluster: "dev-cluster-1"
environment: "development"
These labels are critical for:
- Identifying which cluster a metric came from
- Filtering dashboards by cluster or environment
- Performing per-cluster cost analysis and chargebacks
OpenCost Deployment Example
apiVersion: apps/v1
kind: Deployment
metadata:
name: opencost
namespace: monitoring
spec:
replicas: 1
template:
spec:
containers:
- name: opencost
image: opencost/opencost
ports:
- containerPort: 9003
Benefits:
- Unified cost visibility across all Kubernetes clusters and cloud providers
- Long-term cost storage and historical analysis via Thanos
- Real-time dashboards using Grafana
- Better FinOps governance and accountability across teams and projects
Alternatively, you can use Terraform or Helm to automate this monitoring stack deployment across clusters. This ensures cost observability is built into your infrastructure pipeline from day one.
Tip: If you're not ready for a centralized stack, you can also deploy OpenCost individually on each cluster and sync data manually.
References
1. Labels and Selectors | Kubernetes
2. What are AWS Cost and Usage Reports? - AWS Data Exports
3. Export Cloud Billing data to BigQuery
4. Tutorial - Create and manage Cost Management exports
5. Resource Management for Pods and Containers | Kubernetes
6. Horizontal Pod Autoscaling | Kubernetes
7.Amazon Elastic Compute Cloud Documentation
9. Managing your costs with AWS Budgets
10. Create, edit, or delete budgets and budget alerts | Cloud Billing | Google Cloud
Conclusion
Kubernetes offers immense flexibility, but without a solid FinOps strategy, costs can quickly spiral out of control. These 8 strategies ranging from proper workload labeling to using Spot instances and setting budgets give you a structured approach to reducing cloud spend while improving accountability. With automation, visibility, and governance in place, your teams can build faster and smarter without wasting resources. Start small by applying one or two practices, then scale your FinOps maturity gradually.
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