Kubernetes has become the go-to platform for deploying and scaling modern applications, but it comes with a hidden problem: cost complexity. Dynamic workloads, autoscaling clusters, and shared infrastructure make it hard to understand who is spending what, and even harder to control that spend. 

In this blog, we’ll break down the challenges, explain how to get visibility optimize Kubernetes, and review 13 top tools that can help.

Why Kubernetes Cost Optimization Matters

Kubernetes introduces inefficiency at multiple layers. At the container level, teams often overprovision CPU and memory to avoid performance risks, which leads to wasted capacity. At the node and autoscaler level, clusters scale up inefficiently when pods don’t fit neatly, leaving unused resources stranded. At the pricing level, organizations underutilize Reserved Instances and Savings Plans or mismanage Spot diversification, resulting in double-paying or instability risks.

These inefficiencies compound quickly, driving cloud bills higher than expected. Engineers lose time debugging scaling issues or juggling manual rightsizing instead of shipping features. Optimizing costs eliminates both problems: engineering get stable, efficient clusters, and finance gets measurable savings.

13 Top Kubernetes Cost Management Tools

Let’s dive into the list of best Kubernetes cost optimization tools. 

1. nOps

nOps: the leading cost management tool for Kubernetes 2025

Most Kubernetes tools address only one layer of the problem—containers, nodes, or pricing—forcing teams to juggle multiple solutions. nOps is the first platform to optimize EKS end-to-end. By tackling inefficiency at every layer, it helps engineers run stable, efficient clusters while ensuring finance captures maximum savings automatically.

Kubernetes Cost Allocation

Automatically allocate Kubernetes costs down to namespaces, workloads, and products—without depending on manual tagging. Shared services like load balancers or data transfer are split accurately across teams, and reports can be generated by customer or business unit.

Screenshot of the cost analysis(Engineering Budget by Environment) dashboard.

Dynamic Container Rightsizing

nOps continuously rightsizes EKS workloads with policies tailored to your priorities, with support for all the latest EKS features like in-place container rightsizing and auto-mode. 

Benchmarking for EKS

nOps delivers detailed cost and performance benchmarks at the cluster, node, and workload level. Teams can compare efficiency across workloads, track improvements over time, and quickly spot where clusters are underutilized.

Intelligent Autoscaler Optimization

nOps works with Cluster Autoscaler, Karpenter, or both—tuning scaling in real time and placing workloads on the most cost-efficient nodes. This removes bin-packing gaps, reduces Pending pods, and avoids vendor lock-in.

Pricing Optimization

nOps maximizes Reserved Instance and Savings Plan utilization, blends On-Demand and Spot, and diversifies Spot fleets with machine learning. The result is stable performance with consistently higher savings than point tools can deliver.

nOps was recently ranked #1 with five stars in G2’s cloud cost management category, and we optimize $2+ billion in cloud spend for our customers. 

Try it out with your own AWS account by booking a demo with one of our AWS experts.

#2: Kubecost

Kubecost dashboard

Kubecost is the most widely adopted open-source Kubernetes cost monitoring tool, often used as the entry point for teams starting with Kubernetes FinOps. It’s built on Prometheus and focuses on visibility and allocation rather than deep automation.

Pros

  • Easy entry point with a free open-source edition.

  • Provides granular visibility by namespace, deployment, and label.

  • Strong community adoption and Prometheus-native integration.

  • Supports chargeback/showback reporting for basic accountability.

Cons

  • Recommendations aren’t automated—teams must manually act on them.

  • No native Spot orchestration or commitment management.

  • Enterprise features (multi-cluster, governance, support) are locked behind paid tiers.

Pricing

Kubecost starts free with its open-source edition, but costs escalate quickly as clusters scale. SaaS and enterprise pricing is based on cluster size and features, and larger users often find the total cost comparable to commercial FinOps platforms—despite Kubecost offering less automation.

Best For

Engineering teams that want quick visibility into Kubernetes costs and allocation without upfront investment, but who are prepared to manage optimization manually.

#3: Karpenter

Karpenter is an open-source Kubernetes node provisioning project maintained by AWS. Instead of static autoscaling rules, it makes rapid, real-time decisions about launching the right EC2 instances for pending pods. It’s fast, flexible, and designed for efficiency at the node layer.

Pros

  • Launches nodes in seconds vs. minutes with Cluster Autoscaler.

  • Flexible scheduling with fewer configuration rules to manage.

  • Supports diverse instance types, zones, and sizes to improve bin-packing.

  • Strong AWS backing, active open-source community, and tight EKS integration.

Cons

  • Optimizes only the node layer—no container rightsizing or pricing automation. 

  • Requires engineering expertise (or a solution like nOps) to tune provisioners and scheduling policies.

  • Stability depends on continuous updates and community contributions.

Pricing

Karpenter itself is free and open source, but running it still incurs EC2 costs. While it can lower spend by improving bin-packing and scaling speed, savings aren’t guaranteed—especially if commitments or Spot are not orchestrated alongside it. Enterprises often pair it with a FinOps platform to capture full savings.

Best For

Engineering teams on AWS that want faster, smarter node provisioning for Kubernetes and are comfortable managing cost efficiency at other layers with separate tools.

#4: CloudZero

CloudZero positions itself as a cloud cost intelligence platform rather than a Kubernetes-only tool. It emphasizes allocating costs back to products, features, and teams across multi-cloud environments, with Kubernetes cost visibility as part of its broader FinOps offering.

Pros

  • Strong at cost allocation and mapping spend to business dimensions.

  • Flexible reporting across AWS, Azure, GCP, and Kubernetes.

  • Focused on helping finance and product teams tie cloud costs to unit economics.

  • Integrates with engineering workflows through alerts and dashboards.

Cons

  • Less focused on deep Kubernetes optimization compared to purpose-built tools.

  • No container rightsizing or node autoscaler tuning.

  • Pricing transparency is limited; often considered expensive for what it delivers.

  • May require significant setup to align data models with business structure.

Pricing

CloudZero is priced as a SaaS platform with custom quotes. For midmarket and enterprise customers, costs can be significant.

Best For

Finance and product teams that want to connect Kubernetes spend to business outcomes, and organizations looking for a multi-cloud cost allocation solution rather than deep EKS optimization.

#5: Loft

Loft is a Kubernetes platform focused on multi-tenancy and developer self-service. It provides cost visibility and governance as part of its broader feature set, helping platform teams control spend while enabling developers to manage their own namespaces and clusters.

Pros

  • Strong support for Kubernetes multi-tenancy and self-service environments.

  • Built-in cost tracking by namespace and team.

  • Governance features for quotas, access control, and usage limits.

  • Helps platform teams manage developer environments more efficiently.

Cons

  • Cost management is secondary to its core multi-tenancy and platform features.

  • Lacks advanced optimization for containers, autoscalers, or pricing models.

  • May require significant engineering effort to integrate with FinOps workflows.

Pricing

Loft offers an open-source version and commercial plans. Pricing is typically seat- or cluster-based, which can grow quickly in large environments. 

Best For

Platform teams that already use Loft for multi-tenancy and want built-in cost visibility as part of their developer self-service workflows.

#6: Spot by NetApp

Spot by NetApp is a cloud optimization platform that automates infrastructure management across compute, containers, and storage. For Kubernetes, it focuses on running workloads on the most cost-efficient mix of Spot, On-Demand, and Reserved capacity while maintaining application reliability.

Pros

  • Automates Spot orchestration to improve reliability and utilization.

  • Integrates with Kubernetes for workload-aware scheduling.

  • Includes complementary products for storage and cloud infrastructure optimization.

  • Backed by a large vendor (NetApp) with enterprise support.

Cons

  • Broader focus on Spot management rather than Kubernetes-specific optimization.

  • Limited container-level rightsizing and cost allocation features.

  • Can feel heavy or complex compared to lighter-weight, Kubernetes-native tools.

  • Pricing and packaging across NetApp’s product suite can be difficult to navigate.

Pricing

Spot pricing is custom and typically aimed at midmarket and enterprise accounts. While it can deliver strong savings on compute, customers often find they’re paying for a larger product suite than they need if their primary goal is Kubernetes optimization.

Best For

Organizations running workloads on Spot that want enterprise-grade automation for managing cloud compute fleets, with Kubernetes integration included as part of a broader optimization stack.

#7: Harness

Next on the list of Kubernetes cost monitoring and observability tools is Harness. Harness is a software delivery platform that includes a FinOps module alongside CI/CD, feature flags, and other DevOps capabilities. Its Kubernetes cost management features are part of a broader toolset rather than the sole focus, offering cost visibility and governance integrated with deployment pipelines.

Pros

  • Combines cost management with CI/CD and broader DevOps workflows.

  • Provides Kubernetes cost visibility at the workload and namespace level.

  • Governance features help tie deployment activity to spend.

Cons

  • Cost optimization is not as deep as dedicated Kubernetes FinOps tools.

  • Limited container rightsizing or autoscaler tuning.

  • Can be expensive if adopted solely for cost management.

  • Best results when paired with other Harness modules, which increases complexity.

Pricing

Harness pricing is modular, with FinOps features bundled into the broader platform. Costs can escalate as organizations adopt more modules.

Best For

Enterprises already using Harness for CI/CD or DevOps workflows and looking to layer in cost visibility and governance within the same platform.

#8: Stormforge

Stormforge logo

StormForge specializes in Kubernetes performance testing and automated optimization. It combines load testing with machine learning to recommend and apply resource configurations, helping teams improve efficiency and stability while controlling costs.

Pros

  • ML-driven recommendations for CPU and memory requests/limits.

  • Integrates performance testing with optimization to balance cost and reliability.

  • Can run experiments on workloads to simulate real-world traffic.

  • Focused specifically on Kubernetes, with strong technical depth.

Cons

  • Optimization focuses mostly on resource configuration, not pricing or autoscaler management.

  • Requires integration with workflows to apply recommendations effectively.

  • More complex setup compared to visibility-focused tools.

  • Best suited for teams with performance-sensitive workloads, not general cost reduction.

Pricing

StormForge pricing is enterprise-oriented and typically custom-quoted. 

Best For

Engineering teams running performance-sensitive Kubernetes workloads that need ML-driven tuning to optimize both cost and reliability.

#9: Densify

Add the tools’ Kubecost for their respective images

Densify is an enterprise optimization platform that uses predictive analytics to match workloads with the best-fit infrastructure. For Kubernetes, it focuses on container rightsizing and scheduling guidance, with a strong emphasis on policy enforcement and governance.

Pros

  • Predictive analytics engine recommends optimal CPU/memory for containers.

  • Policy-driven governance enforces resource standards across teams.

  • Supports hybrid environments (VMs, containers, cloud) in one platform.

  • Enterprise-grade reporting and integrations with IT operations tools.

Cons

  • Recommendations are advisory—no automated execution in Kubernetes.

  • Interface and workflows can feel designed more for IT ops than developers.

  • Limited depth on pricing optimization (e.g. Spot, RIs).

  • Best features are gated behind enterprise contracts.

Pricing

Densify is sold as an enterprise subscription, with pricing that reflects its IT operations roots. It can be cost-effective for large enterprises with strict governance requirements.

Best For

Enterprises with established IT ops practices that want predictive rightsizing and governance for Kubernetes as part of a broader infrastructure optimization program.

#10: Yotascale

Total Platform Cost Management with Yotascale - Yotascale

Yotascale is a cloud cost management platform with support for Kubernetes, multi-cloud, and containerized environments. It emphasizes allocation and reporting, positioning itself as a FinOps solution that connects engineering and finance around shared cost data.

Pros

  • Strong Kubernetes cost allocation across namespaces, clusters, and teams.

  • Multi-cloud support (AWS, Azure, GCP) for hybrid environments.

  • Dashboards and alerts tailored for both engineering and finance stakeholders.

  • Emphasis on unit economics and shared accountability.

Cons

  • Optimization features are limited—primarily focused on visibility and allocation.

  • Lacks deep automation for autoscaling, Spot orchestration, or rightsizing.

  • Feature set overlaps with broader FinOps tools, making differentiation harder.

  • May require integration with other platforms for full optimization workflows.

Pricing

Yotascale pricing is SaaS-based and typically midmarket-focused. It can be cost-effective for organizations that want multi-cloud cost visibility, but the value proposition weakens if advanced optimization is a requirement since it leans heavily toward reporting over execution.

Best For

Organizations with multi-cloud Kubernetes deployments that need consistent cost allocation and reporting across clouds, but don’t require automated optimization.

#11: OpenCost

OpenCost is the open-source standard for Kubernetes cost monitoring. Backed by the CNCF and supported by Kubecost contributors, it provides basic visibility into cluster spend with a focus on transparency and community-driven development.

Pros

  • Free and open source, easy to get started.

  • Provides baseline cost visibility by namespace, workload, and label.

  • Widely supported by the Kubernetes and CNCF community.

  • Serves as a foundation for other tools, including Kubecost.

Cons

  • Limited to visibility—no advanced optimization or automation features.

  • Requires manual setup and ongoing maintenance.

  • No enterprise support unless paired with commercial solutions.

  • Data granularity and polish lag behind paid platforms.

Pricing

OpenCost is free to use. Many teams adopt it as a low-cost entry point before graduating to commercial platforms for broader capabilities.

Best For

Teams that want a no-cost way to start measuring Kubernetes spend and are comfortable managing open-source tools themselves.

#12: Amnic

Amnic is a newer entrant in Kubernetes cost management, positioning itself as a lightweight, developer-friendly platform. It focuses on giving teams quick visibility and actionable recommendations without the overhead of large enterprise FinOps suites.

Pros

  • Simple, modern interface geared toward developers.

  • Provides cost visibility and allocation at the workload and namespace level.

  • Offers recommendations for rightsizing and efficiency improvements.

  • Easier to adopt compared to heavy enterprise platforms.

Cons

  • Still maturing—feature set is narrower than established players.

  • Limited automation; recommendations often need manual follow-up.

  • Smaller ecosystem and community support.

  • Best fit for smaller teams, less proven at enterprise scale.

Pricing

Amnic pricing is SaaS-based and designed to be accessible for startups and midmarket teams. It’s generally lower cost than enterprise FinOps tools but scales up as clusters grow, which may eventually narrow the gap.

Best For

Startups and growing teams that want lightweight Kubernetes cost visibility and recommendations without committing to a larger, more complex platform.

#13: Zesty

FinOut: FinOps Cloud Costs Management

Zesty is a cloud cost optimization platform best known for automating commitments and storage management. While not Kubernetes-specific, it integrates with containerized environments to improve savings by dynamically adjusting Reserved Instances and managing EBS volumes in real time.

Pros

  • Automates commitment management (RIs and Savings Plans).

  • Strong storage optimization with real-time EBS resizing.

  • Can reduce manual effort for managing long-term pricing models.

  • Useful complement to Kubernetes cost tools focused only on visibility.

Cons

  • Not purpose-built for Kubernetes—features are mostly infrastructure-level.

  • No container rightsizing, autoscaler tuning, or native Kubernetes allocation.

  • Works best as an add-on, not a standalone Kubernetes solution.

  • Savings depend heavily on AWS usage patterns.

Pricing

Zesty uses a performance-based pricing model, charging as a percentage of savings delivered. 

Best For

AWS users who want automated savings on commitments and storage, and who are looking to complement Kubernetes cost visibility tools rather than replace them.

14. Cast.ai

Next on the list of cost-effective tools for managing multiple Kubernetes clusters is Cast.ai. Cast is a Kubernetes automation platform that emphasizes cost optimization through intelligent cluster management. It automates rightsizing, autoscaling, and Spot orchestration, aiming to cut cloud bills without requiring heavy manual tuning.

Pros

  • Automates cluster optimization, including Spot instance selection.

  • Provides real-time rightsizing and workload placement.

  • Multi-cloud support across AWS, GCP, and Azure.

Cons

  • Platform-first approach can feel opinionated and harder to customize.

  • Limited visibility and reporting compared to dedicated FinOps tools.

  • Focused on infrastructure automation; less depth in cost allocation and finance workflows.

  • Some users report that it requires trust in the platform’s automation “black box.”

Pricing

Cast.ai offers a usage-based pricing model.

Best For

Engineering teams that want automation-first Kubernetes optimization across clouds, and are comfortable letting the platform make most of the scaling and pricing decisions.

15. ScaleOps

ScaleOps is a Kubernetes optimization platform designed to automate resource management in real time. It focuses on dynamically adjusting pod requests and limits, bin-packing workloads efficiently, and optimizing node usage to cut waste while maintaining application performance.

Pros

  • Automates container rightsizing with continuous adjustments.

  • Simple, developer-friendly interface with actionable insights.

  • Integrates with existing Kubernetes autoscalers for smoother adoption.

Cons

  • Primarily focused on resource efficiency—less depth in pricing, commitments, or multi-cloud reporting.

  • Still maturing compared to larger FinOps platforms.

  • Limited finance-facing features like chargeback/showback.

  • May require complementary tools for full FinOps coverage.

Pricing

ScaleOps pricing is SaaS-based and designed to scale with the number of clusters. ROI depends on how aggressively workloads can be rightsized.

Best For

Engineering teams that want lightweight, automated Kubernetes rightsizing and scheduling improvements without adopting a larger FinOps or cloud management platform.

The Bottom Line: nOps is the only all-in-one Kubernetes optimization platform

When companies try to manage Kubernetes costs with multiple tools — like Lens for visibility, Zesty for commitment management, etc. — complexity grows instead of shrinking. Each subscription introduces another data source, another workflow, and another subscription. The data doesn’t always agree, and the fixes often work at cross-purposes. Engineers are left sorting out inconsistencies and repeating work, while costs continue to creep upward.

nOps eliminates that sprawl by bringing the entire optimization process into a single platform. You get visibility, benchmarking, cost allocation, container rightsizing, autoscaling optimization, pricing & commitment optimization, and an AI agent all in one — all using a lightweight agent that costs a fraction of Kubecost. The result is truly maximium efficiency and minimum engineering overhead.

nOps is rated 5 stars on G2 and manages $2 billion in AWS spend — try it out for yourself with a free trial and personalized demo. 

Frequently Asked Questions

Let’s dive into some FAQ on the best Kubernetes cost management tool.

What’s the leading tool for cost management in Kubernetes?

While open-source tools like Kubecost provide surface-level visibility, they leave gaps around autoscaling, pricing, and container optimization. nOps has emerged as the leader for teams running Kubernetes on AWS because it delivers full-stack EKS optimization—covering containers, nodes, and pricing—with automation and AI-driven insights that extend beyond basic cost allocation.

What’s the best Kubernetes cost management tool?

The “best” tool depends on whether you need metrics or full optimization. Point solutions offer visibility, but nOps unifies every layer of EKS cost management. By dynamically rightsizing containers, optimizing autoscalers, and balancing pricing models, nOps helps engineering and finance achieve efficiency, stability, and savings in one comprehensive solution.

How much does it cost to use Kubernetes?

Kubernetes itself is open source, but the costs come from the infrastructure it orchestrates. Compute, storage, and networking drive spend, and managed services like Amazon EKS add control-plane fees. The bigger challenge is inefficiency—overprovisioned pods, unused commitments, or unmanaged Spot risks—which platforms like nOps are built to automatically reduce.

What is the AWS tool for cost management?

AWS Cost Explorer is the native tool for analyzing spend and usage across services, including EKS infrastructure. While it provides budgeting and forecasting, it doesn’t optimize containers or autoscaling. That’s why many organizations pair AWS Cost Explorer with nOps to achieve actionable, automated cost management tailored to Kubernetes workloads.