Klustercost

Klustercost is a free, GPL-3.0 open-source service for allocating Kubernetes costs by workload. It fits teams willing to operate a self-hosted Kubernetes stack, especially on Azure. The strongest case is application-level cost visibility with optional read-only natural-language queries; teams on AWS or GCP will find its current pricing coverage incomplete.

Overview

Klustercost combines real-time cluster observation, a pricing service, PostgreSQL storage and an optional AI layer in one Helm deployment. Its allocation granularity is the workload, so costs can be related to applications instead of presented only as a cluster total. That focus is useful for engineering and platform groups that need ownership-oriented reporting without buying a hosted subscription.

The trade-off is operational responsibility. Installation assumes a running Kubernetes cluster, Helm 3.x, reachable Prometheus and Metrics Server instances, plus a StorageClass. This is a practical fit for Kubernetes operators, not for a team seeking a turnkey SaaS dashboard.

Key features

Go-based observers use Kubernetes informers and Prometheus to follow pods, nodes and namespaces in real time. Pod and node data is persisted to PostgreSQL every 10 minutes, providing a regular historical record for cost analysis while leaving the system less granular than an event-by-event ledger.

Nodes receive hourly virtual-machine prices from Azure retail pricing APIs. Azure users therefore get infrastructure-rate context alongside workload allocation. AWS and GCP enrichment are planned rather than supported now, so multi-cloud teams cannot treat the current pricing view as uniform across providers.

Natural-language questions become plain-language answers and structured JSON. Queries are described as read-only, which suits reporting and investigation where changing cluster state would be unacceptable. Results can be reached through WhatsApp, Teams, Slack, Power BI, an HTTP API and the MCP protocol. The MCP assistant requires an OpenAI API key, so that route adds an external credential and dependency.

The Helm chart deploys the monitor, pricing service, database and optional AI layer together. That packaging simplifies assembling the components, but the underlying prerequisites still make this a platform-managed deployment rather than a plug-in for an existing billing portal.

Pricing

The Open source plan costs 0.00 USD per free. It is open source under the GPL-3.0 License, with no paid tier or seat quota stated. The zero price is compelling for teams that can supply their own Kubernetes, database and observability infrastructure. It does not remove the engineering work of installation, upgrades or operations, and the GPL-3.0 terms matter if you plan to distribute modified software.

Platforms

Klustercost is offered through an API, a self-hosted deployment and the web. Its installation prerequisites center on Kubernetes, Helm, Prometheus, Metrics Server and persistent storage, making those platforms most relevant to organizations already running that stack.

Who it's for

Choose Klustercost if you run Kubernetes on Azure and want workload-level cost attribution, open-source control and several reporting or chat interfaces. It is also a sensible choice for platform teams that value read-only queries and can manage Helm-based services.

Look elsewhere if you need AWS or GCP pricing enrichment today, a managed service with minimal infrastructure work, or a narrowly scoped free tier with explicit resource limits and vendor support.

Pros and cons

Pros

• Free and open source: the GPL-3.0 release avoids subscription charges and permits self-managed deployment.
• Workload allocation: application-oriented costs are more actionable for ownership and chargeback discussions than an undivided cluster figure.
• Azure hourly pricing: retail VM rates add concrete infrastructure context for Azure clusters.
• Multiple access paths: chat tools, Power BI, HTTP API and MCP can fit existing reporting workflows.
• Read-only AI queries: natural-language exploration is designed without write access to the cluster.

Cons

• Azure-only enrichment today: AWS and GCP users lack equivalent current pricing coverage.
• Self-hosting burden: Kubernetes, Helm, Prometheus, Metrics Server and a StorageClass are required before deployment.
• Ten-minute persistence interval: PostgreSQL updates are periodic rather than a record of every instantaneous change.
• AI credential requirement: MCP natural-language access needs an OpenAI API key.
• GPL-3.0 obligations: redistribution plans must account for the project’s copyleft license.

Alternatives

The broader Kubernetes Cost Management Software list is useful when you want to compare more tools. Atmosly Kubernetes Cost Optimization suits a small personal setup: its free plan is billed $0 forever for one cluster, one cloud account, one seat, one project, two environments and ten applications, with cost recommendations view.

KubeAdapt is the better fit when a first 100 vCPU are covered at no cost, all features are included and email support matters; paid startup pricing is $0.60. Choose Krossboard if its freemium offering and API, self-hosted and web platforms match your needs.

OpenCost is a straightforward alternative for open-source Apache 2.0 deployment with Kubernetes and Prometheus. PerfectScale fits teams wanting up to 200 vCPU per month free across unlimited clusters, nodes and pods, with an expert plan priced by quote. CloudBolt is preferable when a broader cloud-management platform with up to 100 resources forever is the priority.

KubeLedger offers free internal use with source code, but it cannot be sold as a managed service. Podledger is an option for a forever-free, self-hosted single-cloud community plan with basic dashboards and pod-level visibility.

Verdict

Klustercost is a strong choice for Azure-focused Kubernetes teams that want free, open-source workload costing and read-only query access under their own control. Its main reason to choose it is the combination of application-level allocation and Azure hourly pricing without a subscription. Its main reason to look elsewhere is equally clear: AWS and GCP enrichment is not available yet, and operating the required Kubernetes-based stack remains your responsibility.