Overview
Gradient clusters are private clusters that run machine learning workloads. Gradient clusters can be created on Paperspace Cloud, on any other cloud provider (AWS, GCP, Azure), or on your own servers via the Gradient Installer.
Find out more about Gradient's multi-cloud capabilities here.
You can create a managed cluster using the Web UI in a couple of clicks.
| Managed Service (multi-tenant) | Managed Private Clusters | Self-Hosted Clusters |
Infrastructure: | Shared, managed by Paperspace | Private, managed by Paperspace | Private, self-hosted |
Setup time: | None | Setup time: 10 minutes | Setup time: 20-30 minutes |
Features: | Notebooks (including Free GPUs!), basic experiments | Notebooks, experiments, deployments, model repo, data management, GradientCI | Notebooks, experiments, deployments, model repo, data management, GradientCI |
Target audience: | Hobbyists & students | Startups & SMBs running production workloads | Mid-market & enterprise businesses conducting ML at scale |
This section of our documentation covers the private cluster options. If you are looking to use our managed service, just create an account to get started right away.
Compute, Storage, & Networking The Kubernetes master node, storage, and networking cost to run the cluster is $0.12/hr. Private Clusters require a minimum of one CPU node for cluster orchestration and clusters include 500GB of storage by default.
In addition, instances used to run workloads are charged at the regular rate (see instance pricing) plus a small compute premium.
Compute, Storage, & Networking Customers are responsible for their infrastructure costs. Gradient does not bill for any compute, storage, and networking costs other than the compute premium.
Subscription Gradient Private Clusters require a Essentials or great subscription.
