Elastic Machine Pool

Run EKS workloads on 50% fewer compute resources

Elastic Machine Pool (EMP) is more than just an autoscaler or a FinOps tool. EMP’s unique approach creates a cost-optimized virtualization layer on AWS bare metal. It then uses VM over-provisioning and live migration to increase the resource efficiency of Java, AI, and other stateful workloads without disrupting pods or requiring changes to applications.

Utilize the true power of Virtualization to transform your cloud infrastructure

EMP deploys a pool of AWS bare metal nodes underneath to create an alternate hypervisor & virtualization layer. Using this, EMP creates alternate VMs called Elastic VMs (EVMs) as worker nodes for your EKS clusters.

A diagram showing the difference of EKS with & without using EMP. EMP deploys an alternate virtualization layer, using AWS bare metal underneath, creating  “Elastic VMs” (EVMs), that look and feel exactly like regular EC2 VMs

EMP over-provisions resources to maximize utilization

Diagram showing how EMP works to provide higher utilized bare metal capacity in aggregate
  • Your Kubernetes workloads and configurations stay the same. But underneath the hood, EMP packs more Elastic VMs (EVMs) on top of fewer bare metal servers to achieve resource over-provisioning.
  • This eliminates bin-packing overhead and the need to tweak your application’s request and limit values for appropriate resource configuration.

EMP auto-rebalances EVMs across the Bare Metal pool

  • When the resource usage for the EVMs on a bare metal node starts going up, EMP will “live migrate” some EVMs to another bare metal server in the bare metal pool.
  • This is done using real-time metrics and historical usage trend patterns. EMP collects these metrics at frequent intervals, 24/7.
  • Zero pod downtime! Your pods stay alive without churn, and the app SLA is not compromised.
A diagram showing how EMP rebalances resources in real-time

Zero pod disruption

EMP uses “Live Migration” technology to ensure movement of EVMs across AWS bare metal nodes without disrupting the pods. This is especially important for large Java-based monolithic applications.

Zero pod disruption

Existing tools don’t solve the fundamental problem of low utilization

CapabilityPlatform9KarpenterCloudHealthCloudabilityCloudZeroKubecost
Optimize usage via improved utilizationCheck / YesX / NoX / NoX / NoX / NoX / No
Zero pod disruptionCheck / YesX / NoX / NoX / NoX / NoX / No
Eliminate engineering and ops back and forthCheck / YesX / NoX / NoX / NoX / NoX / No
Optimize usage via bin packingCheck / YesCheck / YesX / NoX / NoX / NoX / No
Cost visibilityCheck / YesX / NoCheck / YesCheck / YesCheck / YesCheck / Yes
Resource taggingX / NoX / NoCheck / YesCheck / YesCheck / YesX / No
Unit cost allocationX / NoX / NoCheck / YesCheck / YesCheck / YesCheck / Yes

Achieve over 70% utilization using EMP

EMP’s unique approach works at the virtualization and Bare Metal layers, achieving utilization gains not possible with any other existing tools or technologies.

EMP advantages

EMP technical demo

Watch this video for a full demonstration of EMP’s over provisioning, autoscaling, and live migration without pod disruption on AWS bare metal.

Pay only when you see actual savings on your EKS bills

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Ready to start your FinOps journey with EMP?

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Getting Started

Jump start your Kubernetes FinOps journey. Learn how to create your first Elastic Machine Pool (EMP) instance and more.

Get started

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Frequently Asked Questions

Get answers for your technical, architectural, business, integration related questions.

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Additional Resources

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Run EKS workloads on 50% fewer nodes with Elastic Machine Pool

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Understanding Elastic Machine Pool

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EKS Cost Optimization Guide – steps to optimize costs with EKS

A collage graphic depicting the concept of "Kubernetes FinOps" showing Kubernetes and financial imagery connected via the "cloud"

Kubernetes FinOps: Right-sizing Kubernetes workloads

Ready to take action?

Meet with our founders (CTO and VP of Product) who built this product and solution experts to jointly explore the following areas:
  • Your current EKS infrastructure footprint, use cases, and workload characteristics.
  • Your organization’s Kubernetes efficiency goals.
  • Your EKS cluster CPU and memory utilization metrics.
  • How EMP can be used in your environment to achieve your desired outcomes, with a deeper dive into technical considerations such as networking, storage, performance, etc.
  • See the EMP product in action, including integration with EKS, cost-saving, and utilization dashboards.

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