Pod Rightsizing

Autoscale pods with precision
Proactively optimize CPU and RAM at the container level to match real-time demand, reduce waste, and maintain peak performance.

The Problem

When vertical
scaling falls short

As demand constantly shifts, keeping CPU and RAM requests accurate requires nonstop manual tuning, hard to keep up with and even harder to get right. Some teams turn to Kubernetes-native VPA to prevent throttling, OOM crashes, and wasted spend. But it has limits and often clashes with HPA, making it a poor fit for most.

Product Capabilities

Keep CPU and RAM optimized
with accurate scaling

CPU and RAM
rightsizing

Automatically allocate the precise amount of CPU and RAM needed to eliminate waste and ensure peak performance.

Precise container-level optimization

Ensure each container in a multi-container pod—sidecars, adapters, or helpers—gets the exact CPU and RAM needed for optimal performance.

Compatibility
with HPA

Boost performance and cost efficiency with VPA working alongside HPA for seamless resource optimization.

Workload-level
Insights

Gain real-time insights over your workloads’ utilization, costs, and savings opportunities, to reduce CPU & RAM overprovisioning and optimize allocations.

How It Works

Real-time
Pod Rightsizing

Our solution continuously monitors pod usage and uses advanced algorithms to adjust resources at the workload level. Designed with performance in mind, it lets you tailor scaling to your buffer needs, an auto-healing mechanism ensures stability, while gradual rollouts minimize the impact of scaling. With Zesty, CPU and RAM optimization is more accurate than ever.

Benefits

Discover what sets us apart

Cut CPU &
RAM costs

Allocate just the right amount of CPU and RAM resources needed to boost cost efficiency and reduce waste.

Enhance app
performance

Optimize resource distribution across containers within a pod to mitigate CPU throttling and OOM cases.

Eliminate
manual tasks

Save time on usage monitoring and resource adjustments with real-time automation, not just recommendations.

Integrations

Supporting tools that DevOps teams love
Zesty ensures seamless integration across your Kubernetes infrastructure to reduce overprovisioning and boost efficiency.

Interested to learn more?
Download the solution brief

If you’ve made it this far, these questions are for you

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 managed by Zesty. Importantly, you’re only billed for the CPU 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 gain visibility into your environment and provide accurate recommendations. For our automated Pod Rightsizing solution, an additional agent is needed to enhance efficient automation, requiring permissions to apply changes on resource requests and enforce these changes.

No, our platform is designed to maintain performance, ensure stability, and preserve SLAs, while optimizing costs. Automation keeps CPU and RAM available when needed, monitoring events like OOM or throttling, and 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.

Recommendations are available about 24 hours after connecting a cluster to Kompass. Once a recommendation is activated, Pod Rightsizing is fully automated. Users start seeing measurable savings as early as one hour after activation.