Kubernetes (K8S) operator

CloudHiro's Kubernetes (K8S) operator for monitoring and optimization.

Designed to allow attribution of K8S cost and optimize the K8S cluster usage.

The operator is built from scratch to adhere to the most rigorous security requirements, as per our customers' requirements. CloudHiro's K8S operator allows customers to see a breakdown of their cluster costs. If enabled (default to no), the operator optimizes the resource allocation inside the cluster by right-sizing pods. The operator is compatible with all flavors of Kubernetes, including but not limited to EKS, AKS, GKE, and OpenShift.

Here's a sneak peek

How does it work?

  • The operator utilizes data and metrics published by Kubernetes API and metrics API.
  • Aggregate metadata is sent back to CloudHiro, processed against billing data, and results are shown in our Visualizer.
  • CPU, GPU, Memory, Storage, and Network data are collected, normalized, and projected onto cost data.
  • Cost can be attributed to different vectors like namespace, pod name, or tag. A Variety of cost breakdowns are displayed in the visualizer dashboards to provide end-to-end cost visibility.
  • Visualization supports multiple clusters and namespaces with filters and drill-downs.
  • If enabled, the operator will adjust the request and limit for each pod based on its past usage pattern.
  • By default, the operator will only monitor the cluster
  • Enabling the optimization will improve cluster performance and reduce cost.

The operator is part of the platform and carries no additional cost!

How to use CloudHiro's K8S operator

Installation is as simple as deploying a Helm chart. Actually, it is just deploying A Helm chart. Before you do that, you will need an API key, which you can easily get from our console.

New customers

  • First, please register to CloudHiro.
  • Then, please follow the guide for existing customers.

Existing customers

Please log in to your CloudHiro account and follow the guide under optimize->K8S operator.

If you need help, we are always here.