PerfectScale gives us the confidence to automate Kubernetes optimization while letting our engineers focus on building what matters.
Josh Zarrabi, Infrastructure Engineer
PerfectScale for Kubernetes
Kubernetes optimization on every layer. Without the risk.
We optimize pods, nodes and the rates you pay for them together, with stability first, and our sensor shows which workload, team or customer drives your network spend. Cut EKS and GKE costs by up to 50%.
Workloads · Nodes · Rates · Network
prod-eks · us-east-1 · last 30 days● 0 SLO breaches
1WorkloadsPodfit1,284 pods rightsized · CPU requests −41%$31,400
2NodesInfrafit96 → 61 nodes · bin-packing 58% → 83%$22,900
3RatesCommitments74% of node hours on Savings Plans and Spot$14,800
Saved per month, all three layers
$69,100 · 47% lower
Workloads 45%Nodes 33%Rates 22%
Network · seen by the sensorCross-AZ traffic flagged$6,240/moTop driver
checkout-api → redisTrusted by platform engineering teams
three layers, not one
Most tools stop at the pod. We optimize the whole stack.
Rightsizing pods alone leaves money on half-empty nodes and on-demand rates. We optimize workloads, the nodes they run on and the rates you pay for those nodes, together, so savings from one layer aren't lost in the next.
Get a free savings analysisSavings by cluster and layer · $K/mo
$152K a month across four clusters
prod-eksprod-gkestaging-eksml-gpu-eksWorkloadsNodesRates
Pods, nodes and the rates you pay, optimized together.
other tools can't see the network
We can.
Network is often a fifth of Kubernetes spend, and there's no tag on a packet. Our sensor traces every traffic path to the workload, team and customer behind it, and flags cross-AZ and cross-region traffic you can move or remove.
Traffic pathType$/mo
checkout-api → redisteam: PaymentsCross-AZ$2,910search-indexer → kafkateam: SearchCross-AZ$1,870reporting-etl → s3 (eu-west-1)team: DataCross-region$1,460orders-worker → postgresteam: PaymentsSame AZ$120Network spend, attributed
$6,240 a month crosses zones it doesn’t need to
Payments
$3,030
Search
$1,870
Data
$1,460
Workloads
Network cost per service.
Teams
Who drives the egress bill.
Customers
Network cost to serve.
Optimization
Cross-AZ and cross-region, flagged.
built for production clusters
Everything Kubernetes optimization needs
Podfit
Rightsizes CPU and memory requests and tunes HPA and KEDA.
Infrafit
Removes idle capacity and picks the right node types.
Rate optimization
Savings Plans, CUDs and Spot for the nodes you keep.
Network attribution
Traffic cost by workload, team and customer.
Cross-AZ and cross-region flags
Find traffic that crosses zones it doesn't need to.
Every cluster, including GPU
EKS, GKE and more, with GPU utilization included.
live in minutes
How PerfectScale for Kubernetes works
1
Install with one Helm command.
A lightweight agent per cluster. Recommendations start within minutes.
2
See every layer.
Workloads, nodes, rates and network in one view, across every cluster.
3
Automate with guardrails.
Choose what to automate. Health comes first, always.
SOC 2 Type 2, ISO 27001, FinOps Certified Platform.
Free savings analysisHow Rapyd solved observability gaps to cut Kubernetes costs by 40%
40%
Kubernetes cost reduction
30
days implementation effort
What they say
Without PerfectScale by DoiT, I don't know how we would do it. We'd have to have twice the number of people on my team to stay on top of it. With PerfectScale, we can focus on the more strategic issues.
David Adkins, Stefanini Group
PerfectScale by DoiT has become an important part of how we optimize Kubernetes at scale at OneFootball. It gives our platform team the visibility, automation, resiliency insights, and confidence we need to balance cost efficiency with production readiness, especially as we prepare for major global football moments like the 2026 FIFA World Cup.
Andrea Benfatto, OneFootball
PerfectScale cut 40% off our total EKS spend, and the automations handle what used to take our team 20 hours a month. Now we spend that time on reliability and performance instead of chasing cost metrics.
Caio Cristo, Director of Infrastructure/SRE
Every customer has unique usage patterns. Manual resource optimization simply didn't scale—we needed automation to ensure every customer, regardless of size, had right-sized infrastructure without consuming our team's capacity.
Brad Quinn, Lead Platform Engineer, PlayHQ
PerfectScale allowed us to grow capacity without growing cost. We effectively absorbed 30% more usage for free.
Thomas Comtet, Senior Staff Engineer, SNCF
I believed in the product the first time I saw it. I still show it to everyone. It was the only solution that combined smart automation with real cost savings, without putting performance at risk.
Joao Soares, Platform Engineering Lead, NOS
PerfectScale gave us the answers we needed on a silver platter. The insights saved us time and money.
Jason Berk, Platform Operator, K1x
Frequently asked
questions
What does optimizing on three layers mean?
We rightsize workloads (pod CPU and memory requests), optimize the nodes they run on (idle capacity, node types, autoscaler tuning), and optimize the rates you pay for those nodes with commitments and Spot. Doing all three together keeps savings from one layer from being lost in another.
How do you see network costs?
Our sensor observes traffic at runtime and traces each path to the workload, team and customer behind it. Cross-AZ and cross-region traffic is flagged so you can move or remove it.
Will optimization hurt reliability?
No. Recommendations are health-first: under-provisioned workloads get more resources, not less, and you choose which namespaces and workloads to automate.
Which Kubernetes platforms are supported?
Amazon EKS and Google GKE, among others, across any number of clusters, including GPU workloads.
How long does it take to start?
One Helm command per cluster. Recommendations start within minutes, and a free savings analysis shows what each layer can save.
Three layers of savings. Zero compromise on reliability.
Get a free Kubernetes savings analysis.