Kubernetes optimization platform
every layer.
Automatically scale compute, storage, and cloud commitments to match real workload demand.
No resource overprovisioning. No performance risk. No engineering overhead.
One Platform. Every Layer
Multi-dimensional Autoscaling
Simultaneously optimizes horizontal and vertical autoscaling to ensure peak performance while eliminating compute spend.
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.
Turn Kubernetes efficiency into measurable impact
Cut infrastructure costs
Ensure every resource is used efficiently by continuously matching capacity to demand, reducing waste and lowering infrastructure spend.
Protect performance at scale
Automatically detect and remediate CPU throttling and OOM pressure before they impact performance. We track actual resource usage, not averages.
Automate the work, keep control
Free engineers from constant monitoring, rightsizing, and resource tuning. Define your guardrails and let automation continuously optimize within them.
Our customers say it best
“Zesty keeps us flexible. It’s fully automated but doesn’t lock us in. We have saved 40% on compute costs.”
Program Operations
Manager at Printify
“I was looking for a 30% reduction.
It’s going to be more like 65%”
VP of Engineering at Wildflower Health
“We got up to 43% optimization in cluster size, without having to manage it ourselves”
Platform Engineering Lead at Sennder
“Zesty’s Commitment Manager keeps us flexible. It’s fully automated but doesn’t lock us in. We have saved 40% on EC2 costs.”
Program Operations Manager at Printify
“I was looking for a 30% reduction.
It’s going to be more like 65%”
VP of Engineering at Wildflower Health
“We got up to 43% optimization in cluster size, without having to manage it ourselves”
Platform Engineering Lead at Sennder
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.
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.
“Zesty is a game-changer.
It ensures cost savings while keeping everything stable and secure.”
Principal Cloud Architect,
Architecture & Operations
“The onboarding and value we got from Zesty was immediate, and the professional support we received from the team was beyond words.”
Head of DevOps
“Zesty gave us savings without compromising ownership or security.
It’s a hassle-free solution I can trust and rely on.”
Program Operations Manager
“Zesty helped us lower waste in our compute resources, both with rightsizing and commitment management.”
Platform Engineering Lead
VP of Engineering
“We increased coverage from 85% to 99%. Today I’m just checking everything is alright for five minutes and then moving on.”
Infra R&D Director
“With simple integration and zero effort, we were able to cut down our compute costs by 53%.”
Head of DevOps
