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--- |
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title: Overview |
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version: EN |
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--- |
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<img style={{ borderRadius: '0.5rem' }} |
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src="/images/clusters/overview/1_clusters.png" |
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/> |
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VESSL enables seamless scaling of containerized ML workloads from a personal laptop to cloud instances or Kubernetes-backed on-premise clusters.   |
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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-premise GPU servers, and (3) private clouds. You can then use VESSL as a single point of access to multiple clusters.  |
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VESSL Clusters simplifies the end-to-end management of large-scale, organization-wide ML infrastructure from integration to monitoring. These features are available under **🗂️ Clusters**. |
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* **Single-command Integration** — Set up a hybrid or multi-cloud infrastructure with a single command. |
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* **GPU-accelerated workloads** — Run training, optimization, and inference tasks on GPUs in seconds |
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* **Resource optimization** — Match and scale workloads automatically based on the required compute resources |
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* **Cluster Dashboard** — Monitor real-time usage and incident & health status of clusters down to each node. |
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* **Reproducibility** — Record runtime metadata such as hardware and instance specifications. |
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<img style={{ borderRadius: '0.5rem' }} |
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src="/images/clusters/overview/2_figure.png" |
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/> |
