Predictable Kubernetes costs.
Uncompromised performance.
DevZero continuously optimizes CPU and GPU allocation in Kubernetes clusters, reducing waste and lowering costs for AI and compute workloads.
Current Spend
$576,542/mo
Optimized Spend
$176,542/mo
Annual Savings
$4.8M/yr
Companies who slashed their Kubernetes
spend using DevZero
The Problem
Kubernetes waste is structural, not accidental
Kubernetes optimizes for reliability, not efficiency. Datadog reports 83% of provisioned compute goes unused, creating persistent cloud waste.
Teams face an unscalable tradeoff between overprovisioning for safety and performance or manually tuning for savings.
The Solution
Continuous optimization, without tradeoffs
DevZero optimizes Kubernetes infrastructure in real time. The platform automatically adjusts CPU and GPU allocation as workloads change, scaling resources up during demand spikes and reclaiming waste as demand falls.
The result? Maximum efficiency without compromising performance. No manual tuning, scheduled guesswork required.
COST SAVINGS
$10.9M
AUTOMATION SAFETY
98.5%
AUTOMATIONS ACTIVE
11,354
DevZero slashed cloud costs by 60% in 30 days — uncovering massive waste in seconds.
See Case Study“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.”
Lauren Glass Mullins
personality pool
Why DevZero
Cost Monitoring
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
Workload Optimization
Traditional approaches require over-provisioning or risk performance issues, forcing engineers to constantly tweak configurations. Platforms like DevZero use AI to adjust CPU and memory in real time — without restarts — learning usage patterns to optimize cost and performance, enabling 30–80% savings, SLA compliance, and freeing engineers to focus on building features.
Intelligent Instance
DevZero dynamically selects the optimal node instance type for your workloads — maximizing bin packing efficiency and improving overall utilization. By analyzing workload behavior in real time, our system chooses the right CPU/memory profile to meet SLOs while minimizing resource waste.
The results? Higher density per node, fewer underutilized instances, and significant savings — without sacrificing performance. It’s automatic infrastructure efficiency, purpose-built for engineers who care about cost and scale.
Live Migration
Live migration moves running apps — CPU, memory, storage, and network — across nodes with zero downtime. Powered by CRIU and CRIUgpu, it supports even GPU workloads.
By eliminating cold starts and enabling true workload mobility, you can consolidate resources efficiently and reduce infrastructure waste in Kubernetes environments. Results: 30–50% cost savings, no cold start performance delays, and significantly higher cluster utilization.
Smart GPU Rightsizing
Get granular visibility into GPU infrastructure spend with real-time metrics across clusters, namespaces, and workloads. Track GPU utilization, memory usage, alongside cost allocation by team, model training job, and environment.
Identify GPU waste with precision: pods allocated full A100s but averaging 23% utilization, or GPU memory reservations at 80GB with only 12GB actively used. Detect idle GPUs between training runs, underutilized inference endpoints, and opportunities for GPU time-slicing or MIG partitioning.
Multi-Cloud Support
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)
OpenShift
Kubernetes
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
Karpenter
Smarter node scaling + bin packing
DevZero
Workload rightsizing, node autoscaling + bin packing
Free Kubernetes Assessment
Get a free self-serve assessment of your Kubernetes cluster — visualize costs by nodes, node groups and workloads. See which workloads are more expensive (and overprovisioned) and how much you can save.