Cut Kubernetes cost
at every layer

Reduce costs, sustain peak performance, and eliminate manual work through autonomous multi-layer optimization of compute, storage, and commitments.

Trusted by the best to optimize at scale

Unified automation for reliable Kubernetes optimization

Zesty unifies multiple automation layers to optimize both resources and commitments, delivering deeper waste reduction, greater stability, and a more holistic approach to Kubernetes optimization.

Pod Rightsizing

Intelligent Pod Rightsizing automation

Dynamically adjusts CPU and memory to match real-time workload demand—eliminating waste and performance lag.

Headroom Reduction

Faster, Smarter Scaling with Karpenter

Automatically handles unpredictable traffic spikes, accelerating scaling with Karpenter up to 5× faster and eliminating the need for 40–50% CPU buffers.

PV Autoscaling

Real-Time PV autoscaling

Automatically adjusts PVs capacity in real time to match workload needs, maintaining uptime while eliminating overpayment for unused storage.

Spot Protection

Spot Instance protection

Run critical workloads on Spot Instances with confidence. Automatically moves pods to new nodes up to 40 seconds before interruption, maintaining uptime, increasing Spot Instance coverage, and keeping costs low

Commitment Manager

Continuous commitments optimization

Automatically optimize micro Savings Plans, dynamically adjusting commitment coverage in real time to match usage patterns and financial policies

Insights

Workload-level visibility and Insights

Streamline monitoring with real-time visibility into resource consumption, costs, and potential savings, all from a single interface designed to support fast, data-driven optimizations.

Optimized for any application or workload

Our automation engine uses purpose-built technologies to scale intelligently, eliminate overprovisioning, and maintain performance.

Multi-Layer Automation

Simultaneously apply multiple automation techniques to seamlessly adjust compute, storage, and commitments, driving cost efficiency at every layer of your infrastructure.

Advanced predictive scaling

AI-powered algorithms analyze historical and real-time utilization patterns to accurately forecast workload demand, proactively adjusting resources before usage spikes occur.

Fast application boot time

Boost efficiency with FastScaler™ Technology. Hibernated nodes spin up in under 30 seconds with pre-cached container images, speeding application boot time and maintaining SLAs.

Engineers trust it. Finance loves it.

Trusted by winning teams worldwide

Managed cloud spend
Optimizing billions of dollars for engineers teams across the globe.
$ 0 billion
Accounts
Delivering optimized solutions across thousands of k8s environments.
1000 +
Customer Satisfaction Rate
Highly rated by teams worldwide for
reliability, innovation, and support.
0 /5

Quick answers
for curious minds

How does the pricing model work?

Our pricing model is designed to be straightforward and transparent. We charge a base fee plus a fee per CPU or Storage managed by Zesty. Importantly, you’re only billed for the CPU or storage capacity managed after optimization. This ensures that you pay only for the resources we actively manage, delivering clear value with every CPU optimized.

Yes, security is a priority. The platform complies with industry standards, encrypts all data, and offers role-based access controls, ensuring only authorized users can access your Kubernetes cost data and settings. Only meta-data and usage metrics are collected, Zesty doesn’t have access to any data on the disk or the EC2 instance. These metrics are reported to an encrypted endpoint, and sent unidirectionally to Zesty’s backend. All of Zesty’s architecture is serverless meaning there are no servers or databases involved and all data collected resides within AWS.

Zesty requires an agent with read-only permissions to function. This agent allows Zesty to gain visibility into your environment and provide accurate recommendations. For our automated headroom reduction solution, an additional agent is needed to enhance efficient automation, requiring permissions for creating nodes, reading logs from Cloudwatch, events from SQS, and more.

No, our platform is designed to maintain performance, ensure stability and preserve SLAs, while optimizing costs. Automation keeps CPU and storage available when needed, ensuring applications run smoothly even as costs are reduced.

No, our platform is designed for a quick and simple onboarding process. Most customers are up and running within minutes, with full support to ensure a smooth start on our platform.

Users start seeing measurable savings 10 days after connecting the CUR and completing the onboarding process. Typically, Headroom reduction or Spot automation takes about three days for the initial data to populate, followed by an additional 7 days to generate recommendations and start automation.