Zesty
Autonomous Kubernetes optimization platform that continuously reduces infrastructure costs across compute, storage, and cloud commitments without sacrificing application stability.
At a Glance
About Zesty
Zesty is a Kubernetes optimization platform built to autonomously reduce cloud infrastructure costs across every layer — compute, storage, and cloud commitments — without requiring manual tuning or application code changes. Founded by Maxim Melamedov (CEO) and Alexey Baikov (CTO), the company has raised $116M in funding and, according to its About page, manages over $5B in AWS spend across more than 3,000 AWS accounts.
What It Is
Zesty sits in the Kubernetes cost optimization and FinOps category. Its core job is to continuously right-size and autoscale Kubernetes workloads in real time, eliminating idle capacity and cloud waste while keeping SLOs intact. Unlike point solutions that address only one dimension of waste, Zesty's platform coordinates horizontal scaling, vertical rightsizing, pod placement, persistent volume sizing, and cloud commitment purchasing in a single system.
Platform Architecture: Multi-Dimensional Optimization
Zesty's platform is organized around several interconnected capabilities:
- Multi-dimensional autoscaling — simultaneously optimizes HPA (horizontal) and VPA (vertical) autoscaling to match actual workload demand
- Adaptive pod placement — repositions unevictable pods that block node consolidation, reducing fragmentation and enabling higher node utilization
- PV autoscaling — automatically scales persistent volumes up or down based on real-time usage to cut idle storage costs
- FastScaler — reduces application start time by up to 5x for clusters running Karpenter or Cluster AutoScaler, absorbing traffic spikes without throttling or OOM kills
- AWS and Azure commitment optimization — continuously aligns Reserved Instance and Savings Plan commitments with shifting usage to maximize coverage and minimize lock-in risk
- Compute cost visibility — per-workload cost and resource usage analysis with actionable recommendations
Setup Path
Zesty is designed for fast deployment with minimal engineering overhead. The setup flow involves installing a lightweight Insights Agent via a Helm chart, connecting a Cost and Usage Report (CUR) with read-only access, reviewing generated recommendations, defining guardrails and optimization strategies per workload, and then enabling full automation. The platform states no application code changes are required.
Integrations and Compatibility
Zesty works alongside existing Kubernetes tooling without replacing it. The platform is compatible with HPA, KEDA, and any node autoscaler, and integrates with Git-based workflows and common observability stacks. It holds AWS Advanced Technology Partner status and is SOC 2 certified.
Customer Evidence
Zesty's website publishes several attributed customer outcomes. According to a case study, Printify's Program Operations Manager states the company "saved 40% on compute costs." Wildflower Health's VP of Engineering is quoted saying cost reduction exceeded expectations at roughly 65%. Sennder's Platform Engineering Lead reports "up to 43% optimization in cluster size, without having to manage it ourselves." These are vendor-published claims on the Zesty website.
Pricing Model
Zesty uses usage-based pricing tied to realized savings rather than fixed subscription tiers. The pricing page states a minimum 1:3 ROI guarantee across its customer base and offers an ROI projection based on actual workload data and CUR analysis before any commitment is made. All pricing is custom and requires contacting sales.
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Pricing
Usage-Based
Usage-based pricing tied to realized infrastructure savings. Requires contacting sales for an ROI projection based on actual workload data and CUR analysis.
- ROI projection before any commitment
- Pricing based on actual usage and realized savings
- Minimum 1:3 ROI guarantee
- Full platform access including autoscaling, commitment optimization, and cost visibility
Capabilities
Key Features
- Multi-dimensional autoscaling (HPA + VPA coordination)
- Adaptive pod placement for node consolidation
- Persistent volume (PV) autoscaling
- FastScaler for unpredictable spike protection
- AWS commitment optimization (Reserved Instances, Savings Plans)
- Azure commitment optimization
- Kubernetes compute cost visibility
- CPU and memory rightsizing
- Min replicas optimization
- Per-workload guardrails and automation controls
- Helm-based lightweight agent installation
- Read-only CUR integration for cost analysis
- OOM kill and CPU throttling detection and remediation
- No application code changes required
