> ## Documentation Index
> Fetch the complete documentation index at: https://docs.vessl.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Overview
**VESSL Cluster** enables seamless scaling of containerized ML workloads from a personal laptop to cloud instances or Kubernetes-backed on-premises clusters.
Take a quick tour of **VESSL Cluster** with the demo below.
While VESSL comes with an out-of-the-box, fully managed AWS, you can also integrate **an unlimited number** of (1) personal Linux machines, (2) on-premises GPU servers, and (3) private clouds. You can then use VESSL as a single point of access to multiple clusters.
**VESSL Clusters** simplifies the end-to-end management of large-scale, organization-wide ML infrastructure from integration to monitoring. These features are available under the **Cluster** tab.
* **Single-command integration** — Set up a hybrid or multi-cloud
infrastructure with a single command.
* **GPU-accelerated workloads** — Run training, optimization, and inference
tasks on GPUs in seconds
* **Resource optimization** — Match and scale workloads automatically based on the
required compute resources
* **Cluster dashboard** — Monitor real-time usage and incident & health status
of clusters down to each node.
* **Reproducibility** — Record runtime metadata such as hardware and instance
specifications.
