Why Kubernetes Costs Spiral Out of Control

Kubernetes adds abstraction layers that make cloud costs harder to track. Developers set CPU and memory requests based on guesswork, rarely revisit them, and the cluster autoscaler provisions nodes to meet that inflated demand. The result: clusters running at 20-40% actual utilization while you pay for 100% of the provisioned capacity.

Shared clusters make cost attribution nearly impossible. When multiple teams deploy to the same cluster across dozens of namespaces, nobody knows which team is driving the bill. Namespace sprawl creates orphaned workloads that run indefinitely. Resource requests and limits drift from reality as workloads evolve but specs stay frozen.

Traditional cloud cost management tools show you the EC2 bill but cannot tell you which pods are wasting that compute. You need Kubernetes-native cost visibility that connects pod-level utilization to actual cloud spend. That is exactly what SpendZero delivers — and it works across EKS, GKE, and AKS. If you are looking for managed Kubernetes cost optimization services, SquareOps offers that too.

K8s Cost Waste
Detection

SpendZero scans your Kubernetes clusters to find the six most impactful sources of container cost waste.

Overprovisioned Pods

Detect pods where CPU and memory requests are far above actual usage. A pod requesting 2 CPU cores but using 0.3 is wasting 85% of its reserved capacity — and blocking that capacity from other workloads.

Idle Nodes

Identify underutilized worker nodes that can be consolidated. When autoscalers scale up for peak traffic but do not scale down efficiently, you end up paying for empty nodes around the clock.

Namespace Cost Allocation

Break down actual cloud costs per namespace, team, and project. See exactly which namespaces are driving spend, enable chargeback and showback, and identify orphaned dev/staging namespaces running production-tier resources.

Right-Sized Resource Requests

Get specific recommendations for optimal CPU and memory requests and limits based on actual utilization patterns. Maintain application stability while eliminating the padding that inflates your cluster size.

Spot / Preemptible Opportunities

Identify stateless workloads — batch jobs, CI/CD runners, dev environments — that are suitable for spot or preemptible instances. Save 60-70% on compute for workloads that can tolerate interruption.

Cluster Autoscaler Tuning

Optimize scale-down thresholds, scan intervals, and utilization targets. Misconfigured autoscalers are one of the top reasons clusters stay over-provisioned long after traffic peaks subside.

Multi-Platform

Supported Kubernetes Platforms

SpendZero provides platform-specific cost optimization tailored to each managed Kubernetes service's pricing model and capabilities.

Amazon EKS

Full EKS cluster cost visibility with node group optimization, Fargate vs EC2 cost analysis, and Savings Plan coverage recommendations. Identify which EKS workloads should run on Fargate for simplicity vs EC2 for cost efficiency.

EKS Optimizations

Node group rightsizing, Fargate task analysis, Karpenter configuration tuning, and Spot instance recommendations for stateless workloads.

Google GKE

GKE Autopilot vs Standard cost comparison to determine which mode saves more for your workload mix. Optimize sustained use discounts and committed use discount coverage across your GKE fleet.

GKE Optimizations

Autopilot pod-level cost analysis, Standard mode node pool rightsizing, sustained use discount tracking, and preemptible VM recommendations.

Azure AKS

AKS node pool rightsizing with reserved instance recommendations for steady-state workloads. Analyze system vs user node pool costs and optimize VM SKU selection across your AKS clusters.

AKS Optimizations

Node pool consolidation, Azure Reserved VM Instance gap analysis, Spot VM migration for batch workloads, and node auto-provisioning tuning.

Real Kubernetes Savings

Actual optimization outcomes from teams using SpendZero to reduce Kubernetes costs.

01

Pod Rightsizing

Reduced resource requests by 40% across 200+ pods after SpendZero identified that average CPU utilization was 12% of requested capacity. The cluster autoscaler automatically scaled down 5 nodes that were no longer needed, saving $8,400/mo in EC2 costs with zero impact on application performance.

02

Node Consolidation

Consolidated 12 underutilized m5.xlarge nodes into 7 by rebalancing pod scheduling and tightening autoscaler scale-down thresholds. Five nodes were running below 15% utilization due to pod affinity rules that SpendZero flagged as unnecessarily strict. Result: $3,200/mo saved with improved cluster efficiency.

03

Spot Instance Migration

Moved stateless workloads — CI/CD runners, batch processors, and dev environments — to Spot instances after SpendZero identified them as interruption-tolerant. Compute costs for these workloads dropped by 60%, saving $5,100/mo while maintaining the same throughput with graceful interruption handling.

04

Namespace Governance

Identified 3 development namespaces running production-tier resources — m5.2xlarge nodes with high-IOPS storage classes — that were provisioned during a load test months ago and never scaled back. SpendZero's namespace cost allocation made the waste immediately visible to engineering leadership, prompting cleanup that saved $2,800/mo.

How K8s Cost Optimization Works

Four steps from cluster connection to optimized Kubernetes spending. No agents, no sidecars, no disruption.

Connect Your Cluster

Connect your EKS, GKE, or AKS cluster with read-only credentials. For EKS, provide an IAM role with CloudWatch and Pricing API access. SpendZero never needs kubectl write access for scanning — your workloads stay untouched.

Analyze Utilization

SpendZero pulls resource metrics from the Kubernetes Metrics API and correlates them with cloud provider billing data. It compares actual CPU and memory usage against requests and limits across every pod, node, and namespace in your cluster.

Review Recommendations

Browse pod rightsizing recommendations, node consolidation opportunities, spot migration candidates, and namespace cost breakdowns. Every recommendation includes estimated monthly savings and risk assessment so you can prioritize confidently.

Optimize & Monitor

Apply recommendations to your Kubernetes manifests and watch savings materialize. SpendZero continuously monitors your clusters, flags new waste as workloads change, and tracks savings over time so you can prove ROI to leadership.

See Your Kubernetes Waste

Connect your EKS, GKE, or AKS cluster and get a free cost analysis with per-namespace breakdowns, pod rightsizing recommendations, and estimated savings. No credit card required.

Start Free K8s Scan

Why SpendZero for Kubernetes

SpendZero is not another cost dashboard. It is built by engineers who run production Kubernetes clusters every day.

Built by K8s Engineers

SpendZero is built by the SquareOps team that manages Kubernetes clusters for dozens of companies. We built this tool because generic cost dashboards do not understand pod scheduling, resource requests, or namespace boundaries. Learn more about SpendZero.

Multi-Cluster Visibility

See cost data across all your clusters in one dashboard — production, staging, and development. Compare per-cluster costs, identify which clusters are over-provisioned, and track optimization progress across your entire Kubernetes fleet.

Per-Namespace Cost Allocation

Break down shared cluster costs by namespace, team, or project. Enable chargeback and showback without complex tagging schemes. Give engineering leaders clear answers to "which team is driving our Kubernetes bill?"

Works with EKS, GKE & AKS

One tool for all your managed Kubernetes platforms. SpendZero handles the pricing differences between AWS, GCP, and Azure so you get accurate cost data regardless of which provider you use. Cross-link with AWS cost optimization for full coverage.