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Manage user access to your GPU clusters by adding team members who can SSH into Slurm clusters or access Kubernetes resources. Learn more about GPU Clusters →

Understanding Organizations and Projects

Before managing cluster access, it’s important to understand how Together AI organizes resources:

Organizational Hierarchy

OrganizationsProjectsClusters & Volumes
  1. Organization: Your company or team’s top-level account
  2. GPU Cluster Projects: The collaboration boundary for teams and workloads
    • Managed at api.together.ai/settings/gpu-projects
    • Contains GPU clusters and storage volumes
    • Each cluster and volume is tied to exactly one project
    • Access control is managed at the project level
  3. GPU Clusters: Individual Kubernetes or Slurm clusters
    • Viewed at api.together.ai/clusters
    • Inherit permissions from their parent project
    • Users see all clusters from all projects they have access to

How Access Control Works

Key Concept: Think of projects as the collaboration boundary. Your GPU clusters and volumes are mapped to a project, and users are granted access at the project level.
Adding users to a project grants them access to ALL resources within that project:
  • All GPU clusters in the project
  • All storage volumes in the project
  • SSH access to cluster nodes
  • In-cluster permissions based on their role (Member or Admin)
Example Scenario:
Organization: Acme Corp
├── Project: ML-Training
│   ├── Cluster: h100-cluster-1
│   ├── Cluster: h100-cluster-2
│   └── Volume: training-data
└── Project: Research
    ├── Cluster: b200-cluster
    └── Volume: research-data
If you add a user as a Member to the “ML-Training” project, they get access to both H100 clusters and the training-data volume, but NOT the Research project resources.

Access Control is Project-Based

  • Organization membershipProject access: Users must be explicitly added to individual projects
  • Project creators automatically become project admins
  • All clusters in a project share the same access control list
  • To grant cluster access, invite users to the cluster’s parent project

User Roles and Permissions

GPU Cluster projects support two user roles with different permission levels:

Admin

Admins have full control over both control plane and data plane operations. Control Plane Permissions (Full Write Access):
  • Create clusters
  • Delete clusters
  • Create storage volumes
  • Delete storage volumes
  • Modify cluster configurations
  • Scale up or down nodes
Data Plane Permissions (Full Access):
  • SSH into cluster nodes
  • Run workloads and jobs
  • Access Kubernetes Dashboard
  • Execute kubectl commands
User Management:
  • Add members to the project
  • Remove members from the project
  • Assign user roles

Member

Members have read-only access to control plane resources but full access to data plane operations. Control Plane Permissions (Read-Only):
  • ✓ View clusters
  • ✓ View storage volumes
  • ✓ View cluster configurations
  • ✗ Cannot create clusters
  • ✗ Cannot delete clusters
  • ✗ Cannot create storage volumes
  • ✗ Cannot delete storage volumes
  • ✗ Cannot scale the cluster - up or down
Data Plane Permissions (Full Access):
  • SSH into cluster nodes
  • Run workloads and view job status
  • Access Kubernetes Dashboard
  • Execute kubectl commands
  • View pod log and status
RBAC Enforcement: Member permissions for in-cluster operations may vary based on cluster configuration. Contact support to understand the specific RBAC policies applied to your cluster.
User Management:
  • ✗ Cannot add or remove users
Key Difference: Members have read-only access to control plane resources (cannot create/destroy clusters or volumes) and can SSH into nodes. In-cluster permissions (deploying pods, running jobs) depend on RBAC configuration.

Adding Users to Projects

Important: When you add a user to a project, they gain access to all clusters and volumes within that project. You cannot grant access to individual clusters - access is always project-wide.
Prerequisites: Users must have:Without these, users cannot be added to your project.

Step-by-Step Instructions

  1. Access Settings
    • Log in to your Together AI account at api.together.ai
    • Click your avatar in the top-right corner
    • Select Settings from the dropdown menu
  2. Navigate to GPU Cluster Projects
    • In the left sidebar, click GPU Cluster Projects
    • You’ll see a list of all projects you have admin access to
  3. Select Your Project
    • Click View Project on the project containing the clusters you want to share
    • This shows all users currently in the project and their roles
  4. Add a New User
    • Click the Add User button
    • A popup dialog will appear
  5. Enter User Email
    • Enter the email address of the user you want to add
    • Click Add User to confirm
Default Role: New users are added as Members by default. To grant admin access, you can change their role to Admin after adding them via the members table.
  1. Verify Addition
    • If successful, the user will appear in the members grid
    • They now have access to all clusters in this project
    • If the user doesn’t have a Together AI account, you’ll see an error message
Managing Multiple Clusters: If you need different access control for different clusters, create separate projects for each access boundary. For example:
  • “Production” project for production clusters
  • “Development” project for dev/test clusters
Note: Please contact this support if you need this capability, since this feature is currently in closed beta.

Removing Users from Projects

Removing a user from a project revokes their access to all clusters and volumes in that project.

Steps to Remove a User

  1. Navigate to Settings > GPU Cluster Projects
  2. Click View Project on the relevant project
  3. Find the user in the members grid
  4. Click the three dots (⋯) on the right side of their row
  5. Select Remove User from the dropdown menu
  6. Confirm the removal when prompted
Access Revocation: The user will lose access to:
  • All clusters in the project
  • All storage volumes in the project
  • SSH access (revoked within minutes as identity changes sync)
  • Any running jobs or pods will continue but the user cannot manage them

Frequently Asked Questions

Why can’t my team members see our cluster?

Users must be explicitly added to the GPU Cluster Project that contains the cluster. Being part of your organization is not enough - they need project-level access.

Can I grant access to just one cluster in a project?

No. Access control is at the project level. All clusters in a project share the same access control list. To have different access controls, create separate projects.

What’s the difference between Organization and Project access?

  • Organization: Your company’s top-level account. Used for billing and SSO. Does not grant cluster access.
  • Project: The collaboration boundary. Users added to a project can access all clusters and volumes in that project.

How do I see all my clusters across different projects?

Visit api.together.ai/clusters - this view aggregates all clusters from all projects you have access to.