Kubernetes optimization platform

Autonomous Kubernetes efficiency across every layer

Vertical rightsizing, horizontal scaling, and commitment coverage continuously co-optimized in a single engine, acting on real demand to maximize infrastructure efficiency and cut costs.

Trusted by the best to optimize at scale

The Problem

Isolated optimization isn’t efficient.
It’s managed waste.

VPA, HPA, storage, and cloud commitments run on different signals, react slowly, conflict, and require manual tuning instead of aligning to real demand. The result: higher infrastructure costs, SLA risk, and engineers stuck tuning instead of shipping.
Isolated, reactive, manual optimization
Performance Degradation
Wasted Spend / mo $0
Workload Demand
No. of Pods
Pod size
Cloud Commitments

Tweaks

The Solution

One Platform. Every Layer

Multi-dimensional Autoscaling

Simultaneously optimizes horizontal and vertical autoscaling to ensure peak performance while eliminating resource stranding.

Adaptive Pod Placement

Reposition unevictable pods that block node consolidation, reducing fragmentation and enabling higher utilization without risking downtime.

Compute cost visibility

Analyze cost and resource usage per workload, identify waste, and act with clear, data-driven insights and recommendations.

PV Autoscaling

Automatically scale persistent volumes up or down based on real-time usage. Cut idle storage costs while keeping your applications always available.

FastScaler: unpredictable spike protection

Reduce application start time by up to 5x for clusters running with Karpenter and Cluster AutoScaler, so pods become ready faster during scaling events, absorbing spikes without throttling or OOMs.

AWS Commitment optimization

Continuously align compute and database commitments with shifting usage to maintain high commitment coverage, maximize savings, and minimize lock-in risk.

Azure Commitment optimization

Continuously align compute commitments with shifting usage to maintain high commitment coverage, maximize savings, and minimize lock-in risk.

Autonomous Optimization
Built for Production at Scale

Cut infrastructure costs

Keep compute resources and cloud commitment in sync to remove idle capacity and cut infrastructure costs instead of optimizing each layer in isolation.

No more OOM kills at 2am

Automatically detect CPU throttling and OOM pressure at the pod level and remediate before your on-call gets paged. We track actual resource consumption, not just averages.

Full automation, Full control

Define guardrails, rules, and intent based on application-aware decisions. Switch from recommendations to full automation at the workload level. No black box. No surprises.

Customer Story

Our customers
say it best

Installation

Minimal setup. Fast deployment. Full control

Connect
your sources

Install the Insights Agent via a lightweight Helm chart and connect your CUR with read-only access for full workload and cost visibility.

Review
findings

Receive actionable recommendations to optimize CPU, memory, minimum replica, and commitments.

Set
strategies

Define workload scope, optimization strategies, and guardrails so changes align with your standards.

Apply
automation

Execute, and let Zesty continuously optimize your compute resources.

Integrations

Works with the tools
you use and trust

Works with HPA, KEDA and any node autoscaler, as well as Git tools and common observability stacks.
No app code changes required.

Built for engineers. Backed by results.