# Best Kubernetes Cost Optimization Tools (2026): 13 Compared Canonical: https://www.pointfive.co/guides/best-kubernetes-cost-optimization-tools-2026 Kubernetes cost tools compared for 2026: OpenCost, Karpenter and cloud-native options vs IBM Kubecost, Cast AI, ScaleOps, PerfectScale, Sedai and more. By: PointFive Team Published: 2026-10-27 Updated: 2026-10-27 [All guides](https://www.pointfive.co/guides) # Best Kubernetes Cost Optimization Tools (2026): Visibility vs Autonomous Rightsizing PointFive Team October 27, 2026 11 min read ## TLDR - Kubernetes cost tools do three different jobs: show and allocate cost, rightsize pods (CPU and memory requests), and provision and consolidate nodes. Rightsize pods first, then let a node tool pack them onto fewer nodes. - Start with free or built-in options: your cloud's cost allocation, OpenCost, Goldilocks for request recommendations, and Karpenter or EKS Auto Mode for nodes. - Pick by gap: allocation with recommendations (IBM Kubecost), automated pod rightsizing (PerfectScale by DoiT, StormForge by CloudBolt, Zesty), pods and nodes together (Cast AI, ScaleOps, Flexera Ocean), autonomous tuning across Kubernetes and other services (Sedai), and Kubernetes waste found and fixed alongside the rest of your cloud, data and AI bill (PointFive). - PointFive has two complementary products: PointFive OS, the agentic FinOps platform for cloud, data and AI, which reviews EKS, AKS and GKE workloads without agents together with the cloud beneath them, and TokenShift, the AI agent control plane for employee workstations. Where PointFive fits: PointFive is for teams whose Kubernetes bill is one part of a larger cloud, data and AI bill, and who want workload, node and underlying cloud waste found and fixed in one place. PointFive OS runs 500+ deep detections across 40+ platforms, and Nubank saved $8.2M in 9 months with PointFive. [See how Nubank executed 3,000+ DynamoDB remediations](https://www.pointfive.co/case-studies/nubank-dynamodb-optimization) . Disclosure: PointFive wrote this guide, and PointFive is listed first because it is our platform, not because of a ranking. Every competitor statement comes from that vendor's own website, documentation or press release, checked on October 27, 2026, and linked in the sources. Where a vendor publishes nothing, we say so. ## The three jobs Kubernetes cost tools do Kubernetes cost starts with resource requests: "the kube-scheduler uses this information to decide which node to place the Pod on." Inflated requests become nodes you pay for. - Show and allocate cost: split spend by namespace, workload and label, and show idle capacity. These tools change nothing. - Rightsize pods: set CPU and memory requests, and sometimes limits and replicas, from observed usage. - Provision and consolidate nodes: pick instance types, use spot and remove underused nodes. Node tools work from the requests pods declare; they do not shrink them. For the step-by-step process, see our [Kubernetes cost optimization guide](https://www.pointfive.co/guides/kubernetes-cost-optimization) . ## How we evaluated We compared each option on five dimensions, unweighted: - Job: allocation, pod rightsizing, node optimization, or several. - Action: recommendations only, or automatic changes with guardrails. - Footprint: a component in the cluster, or agentless. - Breadth: Kubernetes only, or Kubernetes alongside the wider cloud, data and AI bill. - Pricing model: as publicly stated. ## The tools ### 1. PointFive (PointFive OS and TokenShift) Category: Agentic FinOps platform (waste detection and remediation across cloud, data and AI) Best for: Enterprises running Kubernetes alongside other clouds, data platforms and AI providers that want one place to find and fix waste. [PointFive OS](https://www.pointfive.co/products/pointfive-os) , "The agentic FinOps platform for your cloud, data, and AI", runs 500+ deep detections ([DeepWaste](https://www.pointfive.co/products/pointfive-os/deepwaste) ) across 40+ [platforms](https://www.pointfive.co/coverage) . For [Kubernetes](https://www.pointfive.co/coverage/kubernetes) it discovers EKS, AKS and GKE clusters through your cloud provider integration, with no DaemonSets, sidecars or agents. It checks requests and limits, node pool instance types and spot mix, idle deployments, orphaned volume claims and DaemonSet overhead, reviews them with the cloud capacity beneath, and traces each finding to its technical cause. TokenShift, the AI agent control plane for your employee workstations, works alongside it. - Strengths: Agentless, read-only discovery. [Remediation](https://www.pointfive.co/products/pointfive-os/agentic-remediation) as IDE prompts or as automation under the approval level each customer chooses: per change, per playbook or no approval. - Watch-outs: Not an in-cluster autoscaler; for continuous pod and node scaling, run a specialist below alongside it. No self-serve tier or public price list. Automated changes need customer-authorized write access. - Pricing: Annual contract, custom quote. Listed on AWS Marketplace. - Choose it if: Kubernetes is one of several large bills and the gap is getting waste fixed. Nubank saved $8.2M in 9 months with PointFive; Dolby is also a customer. ### 2. Cloud-native options: GKE, EKS and AKS (as of October 2026) Category: Built-in cost allocation and node management Best for: Every team, as the baseline on its own cloud. - GKE: cost allocation adds cluster, namespace and workload labels to the Cloud Billing export in BigQuery, "based on resource requests, not resources consumed." Autopilot manages nodes and bills general-purpose pods with a pod-based model rather than by node. - EKS: split cost allocation data adds pod-level CPU, memory and accelerator costs to the Cost and Usage Report. EKS Auto Mode uses Karpenter to add and remove nodes and "consolidates workloads onto other nodes." - AKS: the cost analysis add-on, "built on top of OpenCost," shows cost by cluster and namespace, including idle charges. Node auto-provisioning is based on Karpenter and preconfigured in AKS Automatic. - Strengths: First-party billing data, little or no procurement. - Watch-outs: One cloud each. Allocation resizes nothing. AKS cost analysis needs the Standard or Premium tier and an Enterprise Agreement or Microsoft Customer Agreement; GKE cost allocation can raise BigQuery costs. - Pricing: Billing features; EKS Auto Mode adds a per-instance fee on top of EC2. - Choose it if: Always, and first. ### 3. OpenCost (as of October 2026) Category: Open source cost allocation Best for: Teams that want free, vendor-neutral allocation. OpenCost is "Open source cost monitoring for cloud native environments" and a CNCF incubating project. It allocates cost down to containers, including CPU, GPU, memory, load balancers and persistent volumes, prices from AWS, Azure and Google Cloud billing APIs, and exports to Prometheus. It installs by Helm and includes an opt-in MCP server. - Strengths: Apache-2.0, free, and the base of AKS cost analysis. - Watch-outs: Allocation only; no recommendations or changes. You run it. - Pricing: Free. - Choose it if: You need allocation and will run it yourself. ### 4. Karpenter (as of October 2026) Category: Open source node autoscaler Best for: Teams that want node provisioning and consolidation without a vendor. Karpenter offers "Just-in-time Nodes for Any Kubernetes Cluster". It launches nodes for pending pods, removes underused nodes and replaces expensive ones with cheaper ones. Spot-to-spot consolidation is off by default. EKS Auto Mode and AKS node auto-provisioning are built on it. - Strengths: Apache-2.0, a kubernetes-sigs project, providers for AWS and Azure. - Watch-outs: It never changes pod requests. You own its configuration. - Pricing: Free; you pay for instances. - Choose it if: Node waste is the problem and your team can run it. ### 5. Goldilocks by Fairwinds (as of October 2026) Category: Open source request recommendations Best for: Teams that want a free starting point for requests and limits. Goldilocks runs the Vertical Pod Autoscaler in recommendation mode and shows suggested requests and limits in a dashboard. Fairwinds Insights, the commercial product, adds cost allocation. - Strengths: Apache-2.0 and simple. - Watch-outs: Recommendations only; engineers apply them. - Pricing: Open source; Insights pricing not published. - Choose it if: You want to measure the request gap before buying anything. ### 6. IBM Kubecost (as of October 2026) Category: Kubernetes cost visibility, allocation and recommendations Best for: Platform teams that need showback and savings recommendations across many clusters. IBM Kubecost ("Run fast. Spend smart.") breaks spend down by any Kubernetes object and flags over-provisioned workloads, nodes and storage on EKS, AKS, GKE and on-premises. Through the optional Cluster Controller, recommendations can become actions such as request sizing and namespace turndown; Kubescaler continuous request rightsizing is in alpha and supports Deployments. - Strengths: Mature allocation, free tier, self-hosted. - Watch-outs: Recommendation-first; automation needs write access. Foundations caps at 250 cores and 15-day retention. - Pricing: Foundations "Always free" up to 250 cores; Enterprise not published. - Choose it if: Allocation and showback are your main gap. ### 7. Cast AI (as of October 2026) Category: Kubernetes automation for nodes and workloads Best for: Teams that want nodes, spot and pod requests automated together. Cast AI provisions and consolidates nodes, moves eligible workloads to spot and sets CPU and memory requests from usage, alongside or instead of Cluster Autoscaler or Karpenter. You start with a read-only agent that "can't modify your cluster configuration without explicit permission," then enable automation. - Strengths: Pods and nodes in one tool; AWS, Google Cloud, Azure, Oracle Cloud and on-premises. Free cost monitoring once connected. - Watch-outs: Kubernetes only. Automation needs write access. - Pricing: Custom quote; 30-day free trial. - Choose it if: You want one vendor for pods and nodes. ### 8. ScaleOps (as of October 2026) Category: Autonomous Kubernetes resource management Best for: Teams that want pod, replica and node automation in a self-hosted tool. ScaleOps adjusts CPU and memory requests in real time, manages replicas, consolidates nodes, tunes Karpenter, moves workloads to spot and shares GPUs. It is self-hosted via one Helm command, with cloud and air-gapped options. - Strengths: Broad automation including GPU; on AWS, Azure and Google Cloud marketplaces. - Watch-outs: Kubernetes only. - Pricing: Custom quote; free trial after a demo. - Choose it if: You want deep automation inside your environment. ### 9. Sedai (as of October 2026) Category: Autonomous optimization across Kubernetes and other cloud services Best for: Teams that want one autonomous system for Kubernetes, serverless and VMs. Sedai, "The Optimization Platform for Cloud & AI", rightsizes workloads, tunes scaling and optimizes nodes, in Datapilot (recommendations), Copilot (one-click approval) or Autopilot mode. For EKS, AKS and GKE it recommends its Smart Agent, with agentless setup as an option. It also tunes serverless, VMs and storage. - Strengths: Graduated autonomy; coverage beyond Kubernetes. - Watch-outs: Annual commitment; unit price not published. - Pricing: 1 Sedai Billing Unit per managed vCPU, annual, custom quote. - Choose it if: You want autonomous tuning across Kubernetes and other compute. ### 10. PerfectScale by DoiT (as of October 2026) Category: Kubernetes pod rightsizing Best for: Teams that want automated request rightsizing with a free entry tier. DoiT acquired PerfectScale in February 2025. PerfectScale ("Autonomous Kubernetes optimization") shows waste and risk per workload in PodFit, and its automation adjusts pod CPU and memory requests within policies you set. Node recommendations are shown for you to apply. - Strengths: Free tier, policy controls, throttling and memory risk indicators. - Watch-outs: Node changes are not automated. - Pricing: Free up to 300 vCPU per month; paid tiers per vCPU by quote. - Choose it if: Requests are your biggest leak and you want to start free. ### 11. StormForge by CloudBolt (as of October 2026) Category: Machine learning pod rightsizing Best for: Teams using HPA that want vertical rightsizing that works with it. CloudBolt acquired StormForge in March 2025. StormForge ("Kubernetes automation at the speed of trust") rightsizes container CPU and memory requests and limits and coordinates them with horizontal scaling. Changes deploy automatically by annotation, on demand, or as CI/CD patches, with health checks and rollback. - Strengths: Works with HPA; several ways to apply changes. - Watch-outs: Pod rightsizing only. Changes are manual during a 7-day learning period. - Pricing: Not published; 30-day trial on one cluster. - Choose it if: HPA-scaled workloads need rightsizing without conflicts. ### 12. Zesty (as of October 2026) Category: Kubernetes workload optimization and commitments Best for: Teams that want pod rightsizing and commitment management together. Zesty ("Cut Kubernetes Costs. Automatically.") rightsizes CPU, memory and minimum replicas, adds spike protection, fractional GPUs and persistent volume autoscaling, and works with "any node autoscaler." It also manages AWS and Azure commitments. Setup installs an agent by Helm and reads the Cost and Usage Report. - Strengths: Workloads, storage and commitments in one product. - Watch-outs: Node provisioning is left to your autoscaler. - Pricing: "Usage-based pricing. Never more than the value delivered."; rates not published. - Choose it if: You want pod automation plus commitment coverage. ### 13. Flexera Ocean, formerly Spot Ocean by NetApp (as of October 2026) Category: Kubernetes infrastructure automation Best for: Teams that want spot-heavy node automation with pod rightsizing. Flexera completed its acquisition of Spot from NetApp on March 3, 2025. Ocean autoscales nodes, uses spot and committed capacity, bin-packs pods, and can rightsize pod requests and limits automatically or as recommendations, on EKS, ECS, AKS and GKE. - Strengths: Nodes, spot and pods in one product across three clouds. - Watch-outs: Names are moving from Spot to Flexera; check packaging. - Pricing: Not published; on AWS and Azure marketplaces. - Choose it if: Spot capacity is your main node lever. ## Side-by-side comparison | Tool | Allocation | Pod rightsizing | Nodes | In-cluster component | Public pricing | | --- | --- | --- | --- | --- | --- | | PointFive (PointFive OS + TokenShift) | Yes | Detects, fixes with approval | Detects, fixes with approval | No (agentless) | No | | Cloud-native (GKE, EKS, AKS) | Yes | No | Autopilot, Auto Mode, NAP | Varies | Billing features | | OpenCost | Yes | No | No | Yes | Free | | Karpenter | No | No | Automated | Yes | Free | | Goldilocks | No | Recommends | No | Yes | Free | | IBM Kubecost | Yes | Recommends, alpha automation | Recommends | Yes | Free tier | | Cast AI | Monitoring | Automated | Automated | Yes | No | | ScaleOps | Not documented | Automated | Automated | Yes | No | | Sedai | Not documented | Automated | Automated | Optional | Model only | | PerfectScale by DoiT | Not documented | Automated | Recommends | Yes | Free tier | | StormForge by CloudBolt | No | Automated | No | Yes | No | | Zesty | Visibility | Automated | Your autoscaler | Yes | Model only | | Flexera Ocean | Cost analysis | Automated or recommends | Automated | Not documented | No | "Not documented" means we did not find it on the vendor's own pages, not that the capability is absent. ## How to choose - You cannot say who spends what: turn on your cloud's cost allocation or run OpenCost; add IBM Kubecost for recommendations and support. - Requests are inflated: measure with Goldilocks, then automate with PerfectScale by DoiT, StormForge by CloudBolt, Zesty or ScaleOps. - Nodes are underused: Karpenter, EKS Auto Mode or AKS node auto-provisioning; Flexera Ocean if spot is your main lever. - Pods and nodes together: Cast AI, ScaleOps, Flexera Ocean or Sedai. - Kubernetes is one of many large bills: PointFive to find and fix Kubernetes waste with the cloud, data and AI spend around it, plus a specialist where you want continuous in-cluster automation. Never let two tools change the same workload's requests, and separate estimated from realized savings. See our [Kubernetes cost optimization guide](https://www.pointfive.co/guides/kubernetes-cost-optimization) and [how to choose a cloud cost tool](https://www.pointfive.co/guides/how-to-choose-a-cloud-cost-tool) . ## FAQ ### What is the best tool to reduce Kubernetes costs? It depends on the missing job: native allocation, OpenCost or IBM Kubecost to see cost; PerfectScale by DoiT, StormForge by CloudBolt, Zesty or ScaleOps for pod requests; Karpenter, EKS Auto Mode, Cast AI or Flexera Ocean for nodes. If Kubernetes is one of several large bills and the problem is fixing waste, PointFive covers it alongside 40+ other platforms. ### Are OpenCost and Karpenter enough? They cover allocation and nodes for free, but neither changes pod requests. Add Goldilocks or a rightsizing tool. ### What is the difference between pod rightsizing and node autoscaling? Pod rightsizing changes what each pod requests. Node autoscaling changes the machines that hold those pods, based on those requests. Get requests right first. ### Do Kubernetes cost tools need an agent in my cluster? Most run a component in the cluster. Sedai offers agentless setup for EKS, AKS and GKE, and PointFive is agentless, reading Kubernetes metadata and usage through the cloud provider integration. ### How are Kubernetes cost tools priced? Open source tools are free. IBM Kubecost is free up to 250 cores and PerfectScale up to 300 vCPU. Sedai and paid PerfectScale price per vCPU, Zesty is usage-based, and the rest quote custom prices. ### Does PointFive optimize Kubernetes? Yes. PointFive OS finds oversized requests, node pool issues, idle deployments and DaemonSet overhead on EKS, AKS and GKE without agents, and fixes them through IDE prompts or approved automation. ## Methodology and sources We reviewed each vendor's own website, pricing pages, documentation and press releases on October 27, 2026, and did not use third-party sites for competitor claims. If something is out of date, tell us at info@pointfive.co and we will correct it. - PointFive: [Kubernetes coverage](https://www.pointfive.co/coverage/kubernetes) , [Nubank DynamoDB case study](https://www.pointfive.co/case-studies/nubank-dynamodb-optimization) , [AWS Marketplace listing](https://aws.amazon.com/marketplace/pp/prodview-xmaaw4f7qya3i) - Kubernetes: [Resource management for pods and containers](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/) - Google Cloud: [GKE cost allocation](https://docs.cloud.google.com/kubernetes-engine/docs/how-to/cost-allocations) , [Autopilot overview](https://docs.cloud.google.com/kubernetes-engine/docs/concepts/autopilot-overview) - AWS: [EKS Auto Mode](https://docs.aws.amazon.com/eks/latest/userguide/automode.html) , [EKS pricing](https://aws.amazon.com/eks/pricing/) , [Split cost allocation data](https://docs.aws.amazon.com/cur/latest/userguide/split-cost-allocation-data.html) - Microsoft: [AKS cost analysis](https://learn.microsoft.com/en-us/azure/aks/cost-analysis) , [AKS node auto-provisioning](https://learn.microsoft.com/en-us/azure/aks/node-auto-provisioning) - OpenCost: [homepage](https://www.opencost.io/) , [GitHub](https://github.com/opencost/opencost) - Karpenter: [homepage](https://karpenter.sh/) , [disruption and consolidation](https://karpenter.sh/docs/concepts/disruption/) - Goldilocks: [GitHub](https://github.com/FairwindsOps/goldilocks) , [Fairwinds Goldilocks](https://www.fairwinds.com/goldilocks) - IBM Kubecost: [product page](https://www.apptio.com/products/kubecost/) , [pricing](https://www.apptio.com/pricing?src=kc-com) , [Kubescaler docs](https://www.ibm.com/docs/en/SSW0JQG_2.x/install-and-configure/advanced-configuration/controller/kubescaler.html) - Cast AI: [homepage](https://cast.ai/) , [pricing](https://cast.ai/pricing/) , [read-only agent](https://docs.cast.ai/docs/about-the-read-only-agent) - ScaleOps: [homepage](https://scaleops.com/) , [pricing](https://scaleops.com/pricing) - Sedai: [homepage](https://www.sedai.io/) , [pricing](https://www.sedai.io/pricing) - PerfectScale by DoiT: [homepage](https://www.perfectscale.io/) , [pricing](https://www.perfectscale.io/pricing) , [PodFit docs](https://docs.perfectscale.io/podfit-or-vertical-pod-right-sizing) , [node group view](https://docs.perfectscale.io/infrafit-or-node-right-sizing/node-group-view) , [DoiT acquisition](https://www.doit.com/blog/press-release-doit-uplevels-kubernetes-capabilities-with-acquisition-of-perfectscale) - StormForge by CloudBolt: [product page](https://www.cloudbolt.io/stormforge-by-cloudbolt/) , [CloudBolt acquisition](https://www.cloudbolt.io/company/news/cloudbolt-acquires-stormforge/) - Zesty: [homepage](https://zesty.co/) , [pricing](https://zesty.co/pricing/) - Flexera: [Container Optimization (Ocean)](https://www.flexera.com/products/flexera-one/container-optimization) , [Spot acquisition](https://www.flexera.com/more/spot) ## Related reading [All guides](https://www.pointfive.co/guides) - ### [Best Databricks Cost Optimization Tools (2026): An Honest, Comparison-Driven Guide](https://www.pointfive.co/guides/best-databricks-cost-optimization-tools-2026) October 27, 2026 - ### [Best Snowflake Cost Optimization Tools (2026): An Honest, Comparison-Driven Guide](https://www.pointfive.co/guides/best-snowflake-cost-optimization-tools-2026) October 9, 2026 - ### [Best Cloud Cost Optimization Tools (2026): An Honest, Comparison-Driven Guide](https://www.pointfive.co/guides/best-cloud-cost-optimization-tools-2026) June 2, 2026 --- Source: the public page above. Product screenshots and illustrative interfaces are examples, not live customer data.