ScaleOps vs StormForge for Kubernetes Pod Rightsizing: Pricing, In-Place Resize and Automation Compared

Best for: Teams that want pods, nodes, spot and GPUs run hands-free by one self-hosted platform

ScaleOps is the incumbent on most rightsizing shortlists in 2026, and its pitch is breadth: one self-hosted platform that continuously manages CPU, memory, GPU, storage and network for every workload in production, plus the nodes underneath them. Its site claims cost cuts of up to 80 percent and names Maxar (now Vantor) at 62 percent CPU savings and 40 percent memory savings and Outbrain at over 40 percent cost savings. It is listed on the AWS, Google Cloud and Azure marketplaces and offers self-hosted, ScaleOps Cloud and air-gapped deployment. The price is the surprise. scaleops.com/pricing is a custom-quote form using almost the same sentence CAST AI uses, but the AWS Marketplace listing publishes a fixed platform fee of $50,000 a year (or $4,167 a month, so no annual discount) plus a metered fee of $9.00 per vCPU, and states that ScaleOps does not currently support refunds. The listing does not say what period the $9.00 covers, so ask before you model it. CloudBolt's comparison credits ScaleOps with a 7-day trial; ScaleOps's own site does not state a trial length. Budget for the Prometheus footprint as well, because it is per cluster and it is yours to run.

Best for: Rightsizing only, without restarts, with a staged rollout and a published per-vCPU rate

StormForge is the narrow, careful option, and it publishes more about price than anyone else in this category. CloudBolt completed the StormForge acquisition on 31 March 2025 and sells Optimize Live as per vCPU, billed annually, with volume discounts, pay-as-you-go on AWS Marketplace and a 30-day free trial. The contract listing prices a 1,000 vCPU block at $2,700 a month or $32,400 a year, which is $2.70 per vCPU per month. The pay-as-you-go listing meters $0.0041 per requested vCPU per hour, which works out to about $2.99 per vCPU per month at 730 hours and roughly $35,900 a year for the same 1,000 vCPUs, with no upfront or minimum cost and billing based on requested CPU cores per cluster including every HPA replica. Technically it is built around in-place pod resizing with automatic rollback, patented bi-dimensional autoscaling that moves requests and HPA targets together, per-workload machine learning models trained on 28 or more days of usage, and Java heap rightsizing. Three lightweight pods run in the cluster and everything else runs in CloudBolt's cloud. What it does not do is nodes, spot or GPUs; CloudBolt says GPU support is on the roadmap. Two cautions: the AWS listing states SaaS subscription fees are non-refundable, and the brand name collides with an unrelated game server in search, so write "StormForge Optimize Live" when you brief procurement.

Best for: Multi-cloud estates that want the autoscaler, spot and pod sizing from one independent vendor

CAST AI is the third name on almost every ScaleOps shortlist, and it competes with ScaleOps far more than with StormForge because it also takes over the node layer: cluster autoscaling, bin-packing, spot automation with fallback to on-demand, commitments utilization, container live migration and vertical plus horizontal pod autoscaling, across Amazon EKS, Google GKE, Azure AKS and Oracle Cloud. Its pricing page is a quote form, but its own AWS Marketplace listing (prodview-vtvxyzbzs3huy, sold by Cast AI) publishes a rate card: a Free plan for monitoring, Growth at $1,000 a month or $12,000 a year for up to 4 managed clusters and 500 CPU, GrowthPro at the same $1,000 a month for unlimited clusters and up to 2,000 CPU, Enterprise at $5,000 a month or $60,000 a year, a Cost Monitoring add-on at $200 a month, and an additional hourly charge per managed CPU of $0.00694444, which is $5.00 per CPU per 720-hour month. The listing states that CAST AI does not currently offer refunds. If you are choosing between ScaleOps and StormForge because you want the whole cluster managed, CAST AI belongs in the same evaluation; if you only want pod rightsizing, it is more product than you need.

Best for: Grading the idea before you sign an annual contract

PerfectScale is the cheapest way to find out whether automated rightsizing will actually pay for itself in your clusters. It publishes a free tier, free up to 200 vCPU a month with unlimited clusters, nodes and pods, and its paid Advanced and Expert tiers are quoted per vCPU. Run it in recommend-only mode for a few weeks against workloads you understand, compare its suggested requests to what ScaleOps's or StormForge's trial produces, and you walk into the negotiation with your own waste number instead of the vendor's. It can apply changes too, but its role on this page is the grader.

Best for: Platform teams that will operate the free baseline themselves

VPA is the number every paid tool on this page has to beat. It recommends CPU and memory requests from observed usage and can apply them, and with in-place pod resize stable in Kubernetes v1.35 the restart penalty that made VPA painful in production is disappearing. What it lacks is exactly what the vendors sell: HPA coordination (VPA and HPA on the same metric still fight), seasonality-aware models, rollback on health degradation, Java heap awareness, and anyone to call. Note that VPA's Auto update mode was deprecated in VPA 1.4.0, so read the current docs before you build a rollout plan around it. If your platform team has the capacity, benchmark VPA first and make ScaleOps or StormForge show what they add on top.

Best for: Measuring Kubernetes cost per team before and after you buy rightsizing automation

We are the read-only option, and we are here for one situation. ScaleOps and StormForge both report their own savings, and ScaleOps is priced on the vCPUs it manages while StormForge is priced on the vCPUs your workloads request, so each vendor's number is entangled with its invoice. Costanalyst connects your AWS, Azure and Google Cloud billing plus Kubernetes cost data read-only, allocates it by cluster, namespace, team and product, forecasts it and flags anomalies, with no controller in the cluster and no write access anywhere. Run it before the trial to get a defensible waste number, keep it running after go-live to check the vendor's savings claim against the bill finance actually pays, and use the same view to catch the spend that rightsizing does not touch: managed databases, storage, egress and the SaaS bill next to the cluster.