Organization
The top-level entity that owns billing, clusters, teams, and policies. Admins manage organization-wide settings and resources.Team
A logical grouping of members who share resources such as shared volumes and cost controls. Teams enable collaboration within an organization.Admin
An organization-level role with permissions to manage members, teams, volumes, billing, and policies. Admins have organization-wide scope.Member
A user role with permissions to create and use workspaces, use team volumes, and accept team invites. Members operate within their assigned teams.Workspace
An isolated, containerized environment with GPU/CPU where you develop and run code. You can open Jupyter notebooks or connect using SSH in a workspace.Volume
A persistent storage resource managed by VESSL. Volumes can be attached to workspaces to store data, datasets, models, and artifacts.Workspace volume
A persistent volume attached 1:1 to a single workspace. Data persists across restarts and pauses of that workspace. Typically PVC-backed with read-write-once (RWO) semantics.Shared volume
An S3-backed, POSIX-compatible volume that can be shared across teams and multiple workspaces. Shared volumes use read-write-many (RWX) semantics for concurrent access.Temporary volume
An ephemeral volume created alongside a workspace session. Data is cleared when the workspace stops or terminates.Cluster
The compute backend that schedules GPU/CPU resources for your workspaces. Clusters provide the infrastructure for running workspaces.Jupyter Notebook
An interactive environment for writing and running code cells. On VESSL, Jupyter runs inside a workspace and is accessible in the browser.SSH
Secure Shell protocol for terminal access to your workspace. Useful for CLI workflows and advanced debugging.Connect
The workspace tab from which you open Jupyter or fetch SSH connection instructions.Billing states
Workspaces have three billing states that affect cost:- Running: compute is billed while the workspace is active
- Paused: compute is stopped; workspace volume charges may still apply
- Terminated: the workspace is deleted; no further charges accrue
GPU
Graphics Processing Unit, a specialized processor originally designed for rendering graphics but now widely used for machine learning. GPUs can perform many calculations in parallel, making them ideal for training and running AI models. VESSL provides on-demand access to various GPU types (like NVIDIA A100, H100) for your workloads.Docker
A container platform for packaging and running workspace environments. Docker images help ensure consistent environments across teams and projects.Resource spec
A predefined hardware configuration specifying GPU type, CPU cores, memory, and temporary storage. When creating a workspace, you select a resource spec that matches your computational needs. Each spec shows estimated hourly cost.Credit
Prepaid balance used to pay for VESSL resources. Credits are consumed based on workspace runtime and resource usage. You can top up credits through the billing page.Credit buffer
A $10 negative balance allowance before workspace termination. If your credits run out, workspaces continue running until the balance reaches -$10. This buffer amount is deducted from your next top-up.Container image
A packaged environment containing the operating system, libraries, and tools needed to run your code. VESSL offers official images (PyTorch, CUDA, etc.) or you can use custom images. Images ensure consistent, reproducible environments.Port
A network endpoint for accessing services running inside your workspace. You can expose custom ports (HTTP, TCP) to access web servers, APIs, or other applications from outside the workspace.Mount path
The directory location where a volume is attached in your workspace file system. Workspace volumes mount at/root ($HOME), while shared volumes typically mount at /shared.
PyTorch
A popular open-source deep learning framework developed by Meta. VESSL provides pre-configured PyTorch images so you can start training models immediately without setup.CUDA
NVIDIA’s parallel computing platform and toolkit for GPU acceleration. CUDA enables software to use NVIDIA GPUs for general-purpose processing, essential for most deep learning workloads.pip
The standard package manager for Python. Use pip to install libraries and dependencies (e.g.,pip install numpy). Install packages in a persistent volume to preserve them across workspace restarts.