Stop wasting money on overprovisioned pods and expensive nodes. Get pod-level visibility, automated right-sizing, and intelligent spot instance management for EKS, GKE, and AKS.
⚡ 5-minute deployment • 💰 Average 65% cost reduction • 🔒 Works with EKS, GKE, AKS
Most companies waste 60-80% of their Kubernetes budget on overprovisioned resources and inefficient cluster management.
Hundreds of pods running with unknown resource consumption and ownership
Requesting 4GB RAM but using only 500MB - wasting 87% of resources
Can't track costs by team, environment, or business unit
Paying for expensive on-demand nodes when spot instances could save 70%
From deployment to automated savings in four simple steps.
One-command deployment via Helm chart. Our lightweight agent monitors all pods, nodes, and namespaces without impacting performance.
AI analyzes actual CPU, memory, and network usage patterns over time to identify waste and optimization opportunities.
Automatically generate optimal resource requests and limits based on real usage data, eliminating overprovisioning.
Implement pod autoscaling, spot instance migration, and cluster right-sizing with one-click approval.
Complete visibility and control over your Kubernetes spending.
Average savings across pods, nodes, and cluster infrastructure
Track exact costs for every container, deployment, and service
Chargeback and showback by team, environment, or project
Safely migrate workloads to spot instances with fallback protection
Prevent runaway costs with intelligent namespace limits
Unified visibility across EKS, GKE, AKS, and self-hosted K8s
Everything you need to optimize and manage Kubernetes costs at scale.
Automatic recommendations for CPU/memory requests and limits based on actual usage patterns. Reduce overprovisioning by 60%.
Intelligent node scaling that balances performance and cost. Add/remove nodes based on actual workload demands.
Complete cost breakdown by namespace, team, environment, or custom labels. Enable showback and chargeback.
Automated spot instance adoption for stateless workloads with graceful fallback to on-demand during spot interruptions.
Set intelligent namespace limits based on historical usage patterns. Prevent cost overruns while allowing flexibility.
Detailed reports showing each team's Kubernetes spend. Encourage cost-aware development practices.
"DeepCost identified that 67% of our pods were overprovisioned by 4-10x. After implementing their right-sizing recommendations and migrating stateless workloads to spot instances, we cut our EKS bill from $18K to $6K monthly - a 67% reduction. The namespace cost allocation feature also helped us implement chargeback across engineering teams."
Deep integration with managed Kubernetes services for maximum cost savings.
We analyze 7-30 days of actual usage data (depending on workload patterns) to understand CPU/memory peaks and averages. Recommendations include safety buffers (typically 20-30% above peak usage) to prevent out-of-memory kills. You can test changes in dev/staging before production, and we provide rollback automation.
Yes. DeepCost works with any Kubernetes cluster (v1.19+) including managed services like EKS, GKE, and AKS, as well as self-hosted clusters. We integrate with existing HPA, VPA, and cluster autoscaler configurations.
Our spot management includes automatic fallback to on-demand instances when spot capacity is unavailable. We use pod disruption budgets and graceful termination handlers to ensure zero downtime during spot interruptions.
Cost allocation tracks actual resource consumption by namespace with real cloud billing data. Showback generates reports showing each team their spend (informational). Chargeback goes further by actually billing internal teams, which we also support.
No. Our agent uses less than 100MB RAM and 0.1 CPU cores per cluster. It monitors metrics already exposed by Kubernetes (kubelet, metrics-server) without adding overhead to your workloads.
Initial pod right-sizing recommendations appear within 24-48 hours. Most customers implement quick wins (idle pod removal, basic right-sizing) in week 1, seeing 20-30% savings. Full 65% average savings typically achieved in 30-60 days after implementing all recommendations.