Monitoring
Last updated on
February 19, 2026
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OpenCost is a vendor-neutral open source project for measuring and allocating Kubernetes and cloud infrastructure costs. It provides real-time visibility into current and historical cluster spend, enabling accurate showback and chargeback across teams and departments. Organizations use OpenCost to break down costs by namespace, deployment, label, or container, making it straightforward to attribute spending to specific workloads. For example, a platform team running multi-tenant Kubernetes clusters can use OpenCost to generate per-team cost reports that drive informed capacity planning and budget decisions.
How does OpenCost differ from Kubecost?
OpenCost is the open source cost allocation engine originally developed by Kubecost and donated to the CNCF. It provides core cost monitoring, allocation by Kubernetes concepts, and cloud pricing integrations. Kubecost builds on this with commercial features like SSO, long-term storage, cross-cluster aggregation, and enterprise support. OpenCost is free under Apache 2.0 and community-maintained.
What cloud providers does OpenCost support?
OpenCost integrates with AWS, Azure, and GCP billing APIs for dynamic on-demand asset pricing. It also supports on-premises Kubernetes clusters using custom CSV pricing sheets, making it viable for hybrid and air-gapped environments. Cloud costs outside the cluster, such as managed databases and object storage, can also be monitored.
Can OpenCost handle multi-cluster environments?
OpenCost can be deployed per cluster, and each instance provides independent cost visibility. However, it does not natively offer a unified multi-cluster view. For centralized reporting across clusters, teams typically export metrics to Prometheus and aggregate via Grafana or a similar dashboard tool.
How does Shakudo enhance OpenCost for enterprise use?
Shakudo deploys OpenCost as part of a unified AI and data platform, eliminating the need to manually configure Prometheus or Helm charts. Cost data is automatically correlated with workload metadata across all tools in the stack, giving teams a single pane of glass for spend visibility alongside governance and access controls already built in.
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OpenCost on its own delivers granular Kubernetes cost visibility, but deploying and maintaining it requires configuring Prometheus, setting up Helm charts, integrating cloud billing APIs, and managing ongoing infrastructure for the monitoring stack.
On Shakudo, OpenCost runs inside the operating system for AI and data where Prometheus, authentication, and data connectivity are already unified across tools. That means cost data flows seamlessly alongside your ML pipelines and analytics workloads, allowing teams to correlate spending with actual model performance instead of managing monitoring infrastructure.
The result is instant cost transparency from day one without dedicated DevOps effort. Instead of weeks spent wiring together monitoring components, organizations can validate cost optimization strategies and derive actionable insights immediately, while maintaining flexibility to extend or swap tooling as their Kubernetes footprint evolves.
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