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PerfectScalePerfectScale

Autonomous Kubernetes Optimization. Efficient. Reliable. Effortless.

PerfectScale continuously optimizes every workload and node, keeping production stable while it cuts waste.

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Trusted by DevOps, SRE and platform engineering teams

  • Paramount
  • Snyk
  • Fiverr
  • Exabeam
  • NOS
  • PicnicAI
  • Stefanini
  • OneFootball
  • Luma Health
  • PlayHQ

The platform

One agent. Every layer of the cluster.

Kubernetes cost optimization and rightsizing

Kubernetes cost optimization and rightsizing

Right-size workloads, tune autoscaling and optimize node utilization.

Performance and resilience

Performance and resilience

Fix the misconfigurations behind SLA breaches and burned error budgets.

Kubernetes cost visibility and monitoring by team

Kubernetes cost visibility and monitoring by team

Cost and risk by cluster, namespace, workload and team. Built for Kubernetes FinOps.

Karpenter and node autoscaling optimization

Karpenter and node autoscaling optimization

Fewer nodes and better-fit node types, where the biggest dollars are saved. Works with Karpenter, Cluster Autoscaler and NAP.

GPU optimization

GPU optimization

Real-time visibility into how GPU nodes are actually used.

Cloud commitments for EKS and GKE nodes

Cloud commitments for EKS and GKE nodes

Automate AWS and GCP commitment savings for the EKS and GKE nodes you keep.

Go deeper: Karpenter optimization · Kubernetes rightsizing · OOMKilled pods · CPU throttling · Kubernetes autoscaling

What teams get from PerfectScale

Lower bill. Fewer incidents.

Up to 50%

lower Kubernetes cost

99.99%

K8s availability, protected

1

Helm chart to install

How it works

From install to first fix in one sitting.

1

Install one Helm chart.

A lightweight agent on each cluster. No fleet of microservices, no extra Prometheus to run, no node migration.

$ helm install perfectscale perfectscale/exporter agent running · read-only by default cluster prod-eu-west-1 connected first recommendations ready
Install timeMinutes
2

It learns how pods really behave.

Usage, OOM kills, throttling, evictions and node fit, per container and per revision, across every cluster.

checkout-api · rev 41p95 410m
orders-consumer · rev 18OOM ×3
api-gateway · rev 102thr 31%
3

It keeps optimizing, safely.

Recommendations, or autonomous changes under your policy. Your autoscaler then consolidates nodes on accurate requests.

Waste removed this month$18.4k
Resilience issues fixed27
Nodes consolidated14
Free to start. Automation stays off until you turn it on. See my cluster's waste, freeBook a demo →

Platform teams run on PerfectScale

See all customer stories
SNCF
30%
lower Kubernetes costs, about €500K a year, without risking uptime
Read SNCF case studyRiftweaver
59%
less CPU throttling, with six critical APIs made more reliable
Read Riftweaver case studyLuma Health
1,700+ hrs
of engineering time saved each year, with 90% less manual rightsizing
Read Luma Health case study
Prioritized by impact

Turn automation on. The fix list clears itself.

PerfectScale ranks every workload by waste and risk, then applies the right change under the policy you set. Flip the switch to see it work, or keep a person in the loop and approve each change yourself.

Automation Interactive demo · sample dataChanges wait for someone to review and apply them. Flip the switch to see the difference.
Off
Waste removed this month$0Turn automation on to start removing waste
Risks resolved0 of 2
Potential savings$6,150
WorkloadSignalLast 14 daysRecommended changeImpact / monthStatus
ml-feature-store
StatefulSet
 Over-provisioned
CPU4000m → 1500m
Memory8Gi → 3Gi
 −$3,940waste removed Waiting for review
orders-consumer
Deployment
 OOM risk
Memory limit1Gi → 1.5Gi
Auto-shrink paused: leak pattern
 +$41to prevent OOM kills Waiting for review
ci-runners-arm64
RunnerSet
 Over-provisioned
CPU4000m → 1800m
Memory8Gi → 5Gi
 −$2,210waste removed Waiting for review
api-gateway
Deployment
 Throttled
CPU request500m → 800m
CPU limitremoved
 +$58to stop throttling Waiting for review
Sample data for illustrationImpact shown per month

Ranked by dollars and risk

Waste and resilience issues on one list, biggest first.

The change, not a chart

Exact requests and limits to set, per container.

Visibility by owner

Cluster, node group, workload, namespace and team.

Routed to the team

Alerts go to the people who run the workload.

See what PerfectScale would fix in your clustersHow PerfectScale prioritizes fixes →
Autonomous, safety-first

You set the policy. Automation acts only when it's safe.

Choose maximum savings, or extra headroom for your most critical services. PerfectScale applies changes once it's confident they won't hurt performance, so you never trade stability for savings.

  • Revision-aware: it never fights a fresh deploy.
  • Stops on its own when it sees a memory-leak pattern.
  • Policies per cluster, namespace or workload.
  • Recommend-only mode for teams that review first.
How safe automation works →
Automation policy · namespace: paymentsActive

Balanced automation policy

A healthy buffer above observed usage. Strong savings without trading away stability.

Try a policy
Max savings Balanced Max headroom
Headroom above observed usageModerate
Observed usageHeadroom buffer

Est. monthly savings

$18,420
✓
Waits for new revisions to stabilizeNo changes during or right after a rollout
✓
Memory-leak auto-stopPauses shrinking and alerts the owner
✓
OOM and throttling guardRaises requests where workloads are starved

Integrations

Fits the stack you already run.

Your clouds, the autoscaler you chose, and the tools your team already watches.

See all integrations
AWS
Google Cloud
Microsoft Azure
Red Hat OpenShift
DigitalOcean
Helm
Argo CD
GitHub (GitOps)
Datadog
Grafana
Prometheus
Slack
Microsoft Teams
Jira
Works with your autoscaler
Works with Karpenter, Cluster Autoscaler and GKE NAP
No autoscaler migration.
14 shown · all integrations

Frequently asked
questions

What is Kubernetes cost optimization?

It means matching CPU and memory requests and limits to what workloads actually use, and letting your autoscaler consolidate nodes on those accurate requests. PerfectScale does this continuously, per container and per revision.

How does PerfectScale work with Karpenter?

PerfectScale works alongside Karpenter, Cluster Autoscaler and GKE NAP. It right-sizes workload requests, and your autoscaler then consolidates nodes. No autoscaler migration is needed.

Is automated Kubernetes rightsizing safe for production?

Automation stays off until you turn it on, and you set the policy. PerfectScale waits for new revisions to stabilize, pauses shrinking when it detects a memory-leak pattern, and guards against OOM kills and CPU throttling. Recommend-only mode is available.

How long does it take to install?

One Helm chart, installed in minutes. The agent is read-only by default, and first recommendations appear shortly after.

How much can teams save?

Up to 50% lower Kubernetes cost. SNCF cut 30% (about €500K a year), NOS cut more than 50% off its largest cluster, and Luma Health cut 40% off total EKS spend.

Cut cloud cost. Keep peak performance.

Install in minutes and see where your clusters are over-provisioned, under-provisioned and at risk.

Start for freeRequest a demo