Kubernetes wastes 60%.
We auto-fix it.

DevZero continuously right-sizes CPU, memory, and GPU at the workload level, eliminating idle capacity while keeping applications fast and stable. Deploy in minutes and start reducing cloud spend the same day.

Try it yourself

Current Spend

$576,542/mo

Optimized Spend

$176,542/mo

Annual Savings

$4.8M/yr

Companies who slashed their Kubernetes
spend
using DevZero

DATABAHN
Starburst
Fi
Outerbounds
Codilas
personality pool
Onnitech
DATABAHN
Starburst
Fi
Outerbounds
Codilas
personality pool
Onnitech

DevZero fixes overprovisioned Kubernetes

DevZero keeps your Kubernetes aligned to real demand.

CPU, memory, and GPU are continuously adjusted based on actual usage, eliminating idle capacity.

Begin with real-time cost visibility. Then let DevZero automatically reduce waste as your workloads run.

Get a real-time breakdown of infrastructure spend across clusters, workloads, nodes, and teams. Spot cost drivers, uncover inefficiencies, and make informed decisions across your stack.

  • View spend by cluster, namespace, workload and team
  • Identify cost outliers down to the individual node
  • Compare usage and requests to find waste
WorkloadCPUMemoryGPUVRAMMonthly
api-gateway

1.2 / 4 cores

2.1 / 8 GiB

$1,847Active
inference-server

3.8 / 8 cores

12.4 / 32 GiB

1.6 / 4 A100

48 / 160 GiB

$14,290Active
model-training

7.2 / 16 cores

28.1 / 64 GiB

3.1 / 8 A100

102 / 640 GiB

$31,520Active
postgres-primary

2.4 / 8 cores

6.8 / 16 GiB

$3,412Active
redis-cache

0.3 / 2 cores

4.2 / 8 GiB

$892Active
event-processor

1.8 / 4 cores

3.6 / 8 GiB

$1,623Active

Cost Overview

$1.29K/mo31%

Projected Monthly Cost

$303.45/mo115%

Actual Usage Monthly Cost

$35.38/moHIGH

Period Cost

Search and filter data
ClusterCPU RequestsMemory Requests
AWS
production

Connected Jun 19, 2025

21.13 cores19%
Utilization: 24%
71.18 GiB29%
Utilization: 21%
Showing: 1 Clusters
Showing: 1 Clusters
FAIRRead / Workload / Node / Security

Most of your cluster is idle. You're paying for all of it. Kubernetes encourages it.

To stay safe, teams request more CPU and memory than workloads actually need. Over time, those safety margins become persistent waste often with less than 20–30% real utilization.

The result: stalled systems, inefficient infrastructure, and cloud costs that keep growing.

Optimize Kubernetes costs across any cloud

DevZero works wherever your infrastructure lives. Our live rightsizing engine installs in minutes on AWS, Google Cloud, Azure, Oracle Cloud, OpenShift, and on-prem Kubernetes with no lock-in and no migration required.

  • Deploy our read-only operator (zxporter) in <45 seconds
  • Rightsize workloads with policy-backed, AI-driven tuning
  • Cloud-specific (Karpenter-based) node optimization/cluster autoscaling
  • Proactive + reactive binpacking using scheduler plugins and node operator
  • 30 to 60% cost savings regardless of cloud provider or cluster configuration
AWS(EKS)Google Cloud(GKE)Microsoft Azure(AKS)Oracle Cloud(OKE)OpenShiftKubernetes

Cluster • Pod Scaling vs.
Full-Stack Optimization

Cluster Autoscaler, Karpenter, VPA, HPA, KEDA each tackles one piece. DevZero combines workload rightsizing, node autoscaling, and bin packing into one system.

Cluster Autoscaler

Node-level scaling

idle
idle
6 nodes~12% utilized

Karpenter

Smarter node scaling + bin packing

4 nodes~35% utilized

DevZero

Workload rightsizing, node autoscaling + bin packing

2 nodes~75% utilized
Resource Efficiency100%
Cluster AutoscalerKarpenterDevZero

What our Customers say

DevZero slashed cloud costs by 60% in 30 days, — uncovering massive waste in seconds.

Lauren Glass Mullins

Lauren Glass Mullins

personality pool

We started applying DevZero’s recommendations on day 5, and within 24 hours our daily spend dropped by 30%. By day 30, we hit 60% total savings. That’s faster ROI than any other infrastructure investment we’ve made.

Frequently asked Questions

Run a free assessment to identify overprovisioned workloads, idle capacity, and your potential savings, in minutes.

Most clusters are overprovisioned.
Let's prove yours is.