GKE Rightsizing Tools: Google Kubernetes Engine Rightsizing Software and GKE Cost Optimization Tools Compared
Rightsizing on Google Kubernetes Engine works differently from EKS and AKS because of how Google bills you. On a Standard cluster you pay for the Compute Engine VMs under your node pools, so smaller pod requests only save money once the cluster autoscaler removes a node. On Autopilot you pay for the CPU, memory and ephemeral storage your pods request, per second, so every request you trim comes straight off the invoice. Google also gives you more for free than AWS does: a GKE-specific Vertical Pod Autoscaler that is on by default in Autopilot clusters, workload rightsizing views in the console, and cost allocation by namespace in the billing export. This page lists ten GKE rightsizing tools, what each one changes, the GKE catch, and what each costs where a price is published.
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The short answer
The best GKE rightsizing tool for most teams starts with what Google already ships: the built-in Vertical Pod Autoscaler (in-place updates from GKE 1.34.0-gke.2201000), the console rightsizing views and the optimize-utilization autoscaling profile, all at no license cost. Buy CAST AI, ScaleOps, StormForge or PerfectScale when you need VPA and HPA on the same workloads, Java heap tuning, spot automation with fallback, or one controller across GKE, EKS and AKS. On Autopilot, rightsizing requests is the whole game, because Google bills pod requests at $0.0445 per vCPU-hour and $0.0049225 per GiB-hour in us-central1.
CostAnalyst is on this list, so here is the plain version first. We do not install a controller in your GKE clusters and we do not change pod requests or node pools. We read your Google Cloud billing export read-only, allocate GKE spend per team and product next to your AWS, Azure and SaaS spend, and show what the rightsizing tool you pick actually saved on the invoice. We publish our prices. Everything below about Google comes from the GKE documentation and the GKE pricing page, and everything about other vendors from their own sites or their public AWS Marketplace listings, read in September 2026.
How we compared
Five things that actually separate these tools
Standard or Autopilot: how Google bills the thing you are rightsizing
Start here, because the same rightsizing work saves money on one mode and does nothing on the other until a second step happens. On a Standard cluster Google bills the Compute Engine instances in your node pools per second with a one-minute minimum. Trim every pod request by half and the bill stays flat until the cluster autoscaler drains and deletes a node, so pod rightsizing on Standard only pays off when it is paired with node consolidation. On Autopilot the GKE pricing page puts general-purpose workloads on a pod-based billing model: you are charged in one-second increments for the CPU, memory and ephemeral storage your running pods request, with no charge for unscheduled pods, system DaemonSets or unallocated space. There, a smaller request is a smaller bill the same second. Google also warns that Autopilot raises requests that fall below its minimums or CPU-to-memory ratios, so a tool that sets a request lower than Autopilot allows saves nothing. Ask any vendor on your shortlist whether it knows those Autopilot rules before it writes to your specs.
What GKE gives you for free, and where it stops
Google covers more of the pod layer than AWS or Azure. GKE runs its own Vertical Pod Autoscaler, which the GKE documentation describes as based on the open source VerticalPodAutoscaler API but a separate implementation unique to GKE. It is enabled by default in Autopilot clusters and switched on per cluster in Standard. The InPlaceOrRecreate mode, which tries to resize a running pod before falling back to recreating it, needs GKE 1.34.0-gke.2201000 or later. The console adds cost-related optimization metrics and a view that flags underprovisioned and overprovisioned workloads, and Google publishes a tutorial for exporting VPA recommendations to Cloud Monitoring and BigQuery to rightsize at scale. The limits are in the same docs: keep VPA objects under 1,000 per cluster, do not use VPA with an HPA scaling on the same CPU or memory metric (Google points you to multidimensional pod autoscaling instead), JVM workloads are not recommended, and the dashboards recommend without applying anything. The export tutorial also lists Cloud Monitoring and BigQuery as billable.
What Autopilot costs per request, next to a Standard node
The GKE pricing page lists Autopilot general-purpose pods in us-central1 at $0.0445 per vCPU-hour and $0.0049225 per GiB-hour of memory, with a 1-year Kubernetes Engine committed use discount at $0.0356 and $0.003938, a 3-year CUD at $0.024475 and $0.002707375, and spot pods at $0.0133 and $0.0014767. Balanced compute class pods cost more, $0.0645 per vCPU-hour. Every cluster also pays $0.10 an hour for management, with a $74.40 monthly free tier credit per billing account, and $0.60 an hour in total once a cluster on the Extended channel passes standard support. Here is the comparison that matters for rightsizing: a pod requesting 4 vCPUs and 16 GiB costs about $0.257 an hour on Autopilot, while an e2-standard-4 VM with the same shape costs about $0.134 an hour on-demand in us-central1. Standard is cheaper only if your requests fill more than roughly half of every node. If your Standard node pools run below that, either rightsize and consolidate the nodes, or move the workload to Autopilot and rightsize the requests.
What the commercial tools cost, where they publish it
Most rightsizing vendors show a quote form on their own site and a full public rate card on AWS Marketplace, sold under their own seller name. Those cards are the best published benchmark you will get for a GKE negotiation, but they are AWS listings: on GKE you buy direct from the vendor or through Google Cloud Marketplace at a price you agree with them, so use the AWS card as the anchor, not the invoice. CAST AI lists Growth at $1,000 a month for up to 500 CPUs and four clusters, plus $5.00 per managed CPU per 720-hour month, and Enterprise at $5,000 a month. ScaleOps lists a platform fee of $50,000 a year plus $9.00 per vCPU, with the metering period not stated. StormForge Optimize Live, now owned by CloudBolt, lists $0.0041 per requested vCPU-hour pay-as-you-go, about $2.99 per vCPU a month, with no minimum. PerfectScale by DoiT is free up to 300 vCPUs a month and lists Advanced at $2 and Expert at $4 per vCPU a month. IBM Kubecost is free up to 250 cores.
What access the tool needs in your Google Cloud project
Security review is where GKE rightsizing projects stall, so get the access model in writing first. Recommendation-only tools need read access to the cluster and a metrics source, which on GKE is usually Cloud Monitoring or a Prometheus you already run. Pod-level automation needs write access inside Kubernetes, because it mutates pod specs through an admission webhook and patches running pods. Node-level automation needs write access in Google Cloud itself, because CAST AI and similar controllers create and delete Compute Engine instances and node pools, so they need a Google service account, usually bound through Workload Identity Federation for GKE, with Compute and GKE admin permissions scoped to the project. If you are on Autopilot, node access mostly disappears from the question, because Google owns the nodes and bills requests; the tool only needs to set requests well. If your security team will not approve an external controller this quarter, the realistic shortlist is GKE VPA in Off mode, the console rightsizing views, GKE cost allocation and a bill-level view of the result.
At a glance
10 GKE rightsizing tools compared
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| Tool | Best for | What it rightsizes | The GKE catch | Pricing |
|---|---|---|---|---|
| GKE Vertical Pod Autoscaler (built in) | GKE teams that want request recommendations or automatic resizing with no license | Pod CPU and memory requests; in place from GKE 1.34.0-gke.2201000 | Under 1,000 VPA objects per cluster; not with a CPU or memory HPA; not advised for JVMs | No charge; on by default in Autopilot |
| GKE Autopilot | Teams that want Google to own nodes and bill only what pods request | Nothing by itself; bills your pod requests, so rightsizing them cuts the bill directly | Raises requests below its minimums or CPU-to-memory ratios; specific hardware is billed per node | $0.0445 per vCPU-hour and $0.0049225 per GiB-hour in us-central1, plus $0.10 per cluster-hour |
| GKE cluster autoscaler and node auto-provisioning | Standard clusters whose node pools were sized once and never revisited | Node counts, and with node auto-provisioning, node pool machine shapes | Removes nodes only when pods fit elsewhere; the default profile scales down cautiously | No charge; you pay for the Compute Engine VMs |
| GKE cost allocation and console cost views | Seeing GKE cost per cluster, namespace and label before and after rightsizing | Nothing; measures cost per namespace and flags over and underprovisioned workloads | Must be enabled per cluster; detail lands in the BigQuery billing export | No charge for GKE cost allocation; BigQuery and Cloud Monitoring are billed |
| CAST AI | GKE estates that want nodes, spot capacity and pod requests managed by one controller | Nodes, spot capacity, bin packing and pod requests | Takes over node provisioning, so plan how it coexists with the GKE cluster autoscaler | Free monitoring; Growth $1,000 per month plus $5.00 per CPU per month on AWS Marketplace; Enterprise $5,000 per month; GKE via quote |
| ScaleOps | Large GKE estates that want continuous pod rightsizing and keep Google's node tooling | Pod requests, replicas and pod placement | Metering period for the $9.00 per vCPU charge is not stated on the listing | $50,000 per year platform fee plus $9.00 per vCPU on AWS Marketplace; GKE via quote |
| StormForge Optimize Live (CloudBolt) | Teams that want ML pod rightsizing priced per vCPU with no minimum, including JVM services | Pod requests and limits, including Java heap settings | Priced on requested vCPUs, including HPA replicas | $0.0041 per requested vCPU-hour pay-as-you-go on AWS Marketplace, about $2.99 per vCPU a month; 30-day trial |
| PerfectScale by DoiT | Smaller GKE estates that want automated rightsizing with a free entry tier | Pod requests, limits and node utilization | Paid rates are published on AWS Marketplace, not on its own site | Free up to 300 vCPUs per month; Advanced $2 and Expert $4 per vCPU a month on AWS Marketplace |
| Kubecost (IBM) | Namespace chargeback and rightsizing recommendations across GKE clusters | Nothing; recommends requests and flags idle capacity | Recommends only; an engineer applies the change | Free to 250 cores with 15-day retention; Enterprise $15,000 per year to 250 cores on AWS Marketplace |
| CostAnalyst | Finance and FinOps teams proving what GKE rightsizing saved on the Google Cloud invoice | Nothing in the cluster; allocates Google Cloud and GKE spend per team | Kubernetes allocation is on the Scale plan | $99, $299 and $799 per month, published; Kubernetes on the Scale plan |
Product facts checked July 2026. Vendors change pricing and packaging often, so confirm before you buy.
Tool by tool
What each tool is genuinely best at
GKE Vertical Pod Autoscaler (built in)
Best for: GKE teams that want request recommendations or automatic resizing with no license
Google runs its own VPA on GKE, a separate implementation of the upstream API, and it is already on in every Autopilot cluster. Start it in Off mode to read recommendations, then switch workloads to InPlaceOrRecreate on 1.34.0-gke.2201000 or later so most changes land without a restart. Google points you to multidimensional pod autoscaling when you also need horizontal scaling on CPU or memory.
GKE Vertical Pod Autoscaler (built in) compared to CostAnalystGKE Autopilot
Best for: Teams that want Google to own nodes and bill only what pods request
Autopilot is the GKE mode where rightsizing and billing are the same thing. General-purpose pods are billed on their requests per second, so a request cut from 2 vCPUs to 1 halves that pod's CPU charge immediately, with no node consolidation step. Pods that select specific hardware, such as GPUs or a machine series, move to node-based billing with an Autopilot premium, and there the whole node is billed whether your pods fill it or not.
GKE Autopilot compared to CostAnalystGKE cluster autoscaler and node auto-provisioning
Best for: Standard clusters whose node pools were sized once and never revisited
On Standard, this is the half of rightsizing that turns smaller requests into a smaller bill. The optimize-utilization autoscaling profile removes underused nodes more aggressively than the default balanced profile, and node auto-provisioning creates node pools shaped to what pending pods need instead of the one machine type you picked at launch. Neither changes a pod request, so pair it with VPA or a commercial pod tool.
GKE cluster autoscaler and node auto-provisioning compared to CostAnalystGKE cost allocation and console cost views
Best for: Seeing GKE cost per cluster, namespace and label before and after rightsizing
GKE cost allocation adds the cluster name and namespace to the labels in your Cloud Billing export to BigQuery, and puts node overhead in a kube:system-overhead namespace so it is not hidden inside a team's number. The GKE console adds cost-related optimization metrics and a workload view of requested versus used resources. It is the measurement half of rightsizing, and the numbers you will want in front of finance.
GKE cost allocation and console cost views compared to CostAnalystCAST AI
Best for: GKE estates that want nodes, spot capacity and pod requests managed by one controller
CAST AI supports GKE alongside EKS, AKS and Oracle Cloud and starts with a read-only agent that estimates savings before it gets write access. It rightsizes both layers: it picks Compute Engine instance shapes, moves eligible workloads to Spot VMs with fallback to on-demand, bin-packs pods and resizes requests. It fits Standard clusters best, because on Autopilot Google already owns the nodes.
CAST AI compared to CostAnalystScaleOps
Best for: Large GKE estates that want continuous pod rightsizing and keep Google's node tooling
ScaleOps works at the pod layer and leaves nodes to the GKE cluster autoscaler or Autopilot: continuous request rightsizing, replica tuning and placement, with VPA and HPA running together on the same workloads. It runs self-hosted, as ScaleOps Cloud or air-gapped. On Autopilot its request changes pay off directly, which makes the platform fee easier to justify on a large estate than on a small one.
ScaleOps compared to CostAnalystStormForge Optimize Live (CloudBolt)
Best for: Teams that want ML pod rightsizing priced per vCPU with no minimum, including JVM services
StormForge learns request and limit settings from weeks of usage and resizes pods in place, and it tunes Java heap alongside the container request, which covers the JVM case Google's own VPA documentation advises against. The 30-day trial runs full optimization on one cluster, enough to measure the effect on an Autopilot invoice before you sign anything.
StormForge Optimize Live (CloudBolt) compared to CostAnalystPerfectScale by DoiT
Best for: Smaller GKE estates that want automated rightsizing with a free entry tier
PerfectScale supports GKE, EKS, AKS, OpenShift and Rancher and has the only free tier among the automated vendors sized for a real cluster: 300 vCPUs a month. DoiT is also a large Google Cloud partner, which matters if you already buy Google Cloud through them. Paid tiers are priced per vCPU a month.
PerfectScale by DoiT compared to CostAnalystKubecost (IBM)
Best for: Namespace chargeback and rightsizing recommendations across GKE clusters
Kubecost allocates GKE cost per namespace, deployment and label, reconciles it with your Google Cloud bill and lists request recommendations per container. IBM owns it now. It is a strong reporting and chargeback layer and a weak rightsizing layer, because every change still needs someone to apply it.
Kubecost (IBM) compared to CostAnalystCostAnalyst
Best for: Finance and FinOps teams proving what GKE rightsizing saved on the Google Cloud invoice
CostAnalyst reads your Google Cloud billing export read-only, allocates GKE spend to teams and products next to the rest of your cloud and SaaS spend, and flags cost anomalies. It does not rightsize anything. It gives you the before and after on the invoice, so the rightsizing tool you buy is judged on the bill, not on its own dashboard.
See how CostAnalyst worksHow to choose
Pick by the problem you actually have
You run Autopilot and want to spend nothing on licenses
Use what is already on. VPA is enabled by default in Autopilot, so create VPA objects in Off mode, read two weeks of recommendations, then move stable workloads to InPlaceOrRecreate on GKE 1.34.0-gke.2201000 or later. Every request you trim cuts the bill the same second.
You run Standard clusters with node pools sized at launch
Fix the node layer first: switch the cluster autoscaler to the optimize-utilization profile and turn on node auto-provisioning, then rightsize requests with GKE VPA. Or compare the result against moving the workload to Autopilot, which wins when your requests fill less than about half of each node.
You need VPA-style rightsizing and horizontal autoscaling on the same workloads
GKE VPA should not run with an HPA scaling on the same CPU or memory metric. Google offers multidimensional pod autoscaling; ScaleOps and StormForge both manage requests while the HPA scales replicas, with ScaleOps suited to large estates and StormForge priced per vCPU.
You run Java services on GKE
Google's VPA documentation does not recommend VPA for JVM workloads, because the heap hides real memory use. StormForge tunes heap settings with the container request. Test it pay-as-you-go on one namespace before a contract.
You run GKE next to EKS or AKS and want one tool
CAST AI, ScaleOps, StormForge and PerfectScale all support the three managed Kubernetes services. Price the whole estate on one card instead of three native toolsets, and check which one owns the node layer on each cloud.
Finance wants the savings proven by someone other than the vendor
Keep the measurement outside the cluster the vendor changes. Turn on GKE cost allocation, allocate GKE spend per team from the billing export before the rollout, and compare the same view after it. CostAnalyst does that read-only, next to your other cloud and SaaS spend.
Questions buyers ask
GKE rightsizing tools, answered
What is the best GKE rightsizing tool?
For most GKE teams the best rightsizing tool is the one already built in: GKE's Vertical Pod Autoscaler, which is on by default in Autopilot and resizes pods in place from GKE 1.34.0-gke.2201000. Buy CAST AI, ScaleOps, StormForge or PerfectScale when you need VPA and HPA together, Java heap tuning, spot automation with fallback, or one tool across GKE, EKS and AKS.
Does GKE have a built-in vertical pod autoscaler?
Yes. GKE runs its own Vertical Pod Autoscaler, based on the open source VerticalPodAutoscaler API but implemented separately by Google. It is enabled by default in Autopilot clusters and enabled per cluster in Standard. It supports Off, Initial, Recreate, Auto and InPlaceOrRecreate modes, and Google recommends keeping VPA objects under 1,000 per cluster.
Does GKE support in-place pod resizing?
Yes. GKE VPA's InPlaceOrRecreate mode tries to resize a running pod without restarting it and falls back to recreating it when the node lacks capacity, the QoS class would change or the update times out. It requires GKE 1.34.0-gke.2201000 or later, according to Google's VPA documentation.
Does rightsizing save money on GKE Autopilot?
Yes, directly. Autopilot bills general-purpose pods on the CPU, memory and ephemeral storage they request, per second, at $0.0445 per vCPU-hour and $0.0049225 per GiB-hour in us-central1. A smaller request is a smaller bill immediately. Keep requests above Autopilot's minimums and CPU-to-memory ratios, or Google raises them for you.
Is GKE Autopilot cheaper than Standard?
It depends on how full your nodes are. A pod requesting 4 vCPUs and 16 GiB costs about $0.257 an hour on Autopilot in us-central1, while an e2-standard-4 VM costs about $0.134 an hour on-demand. Standard is cheaper when requests fill more than roughly half of each node; below that, Autopilot usually wins.
Can I use VPA and HPA together on GKE?
Not on the same metrics. GKE VPA should not be combined with a Horizontal Pod Autoscaler that scales on the same CPU or memory usage, because each undoes the other. Google offers multidimensional pod autoscaling for that case, and ScaleOps and StormForge manage requests while an HPA scales replicas.
How do I see cost per namespace on GKE?
Enable GKE cost allocation on the cluster. It adds the cluster name and namespace to the labels in your Cloud Billing export to BigQuery, and groups node overhead under a kube:system-overhead namespace. You then query the export or load it into a cost tool that allocates it per team.
How much does GKE cost per cluster?
Every GKE cluster pays a flat management fee of $0.10 per cluster per hour, billed per second, whatever its mode or size. The free tier gives $74.40 of monthly credit per billing account, enough for one zonal or Autopilot cluster. Clusters on the Extended channel past standard support pay $0.60 an hour in total.
Does CAST AI support GKE?
Yes. CAST AI supports GKE alongside EKS, AKS and Oracle Cloud. On GKE it picks Compute Engine instance shapes, uses Spot VMs with fallback to on-demand, bin-packs pods and resizes requests. It starts with a read-only agent that estimates savings. Its public AWS Marketplace card lists Growth at $1,000 a month plus $5.00 per CPU.
Is Kubecost free on GKE?
Yes, up to 250 cores. IBM Kubecost's free Foundations tier covers unlimited clusters up to 250 cores with 15 days of metric retention, and it runs on GKE. Above that, IBM's AWS Marketplace Enterprise public offer lists $15,000 a year to 250 cores, and larger estates are quoted.
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