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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 →

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Understanding Organizations and Projects

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

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Organizational Hierarchy

Organizations → Projects → Clusters & 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

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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
  • Ability to create new workloads and jobs
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.

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Access Control is Project-Based

  • Organization membership ≠ Project 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

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User Roles and Permissions

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

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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

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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 jobs
  • Access Kubernetes Dashboard
  • Execute kubectl commands
  • Deploy pods and manage resources
User Management:
  • ✗ Cannot add or remove users
Key Difference: Members can fully utilize clusters for their work (SSH, run jobs, scale nodes) but cannot create or destroy infrastructure resources.

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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.

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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 Details
    • Enter the email address of the user you want to add
    • Select their role (Admin or Member)
    • Click Add User to confirm
  6. 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.

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Removing Users from Projects

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

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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
Immediate Effect: The user will immediately lose access to:
  • All clusters in the project
  • All storage volumes in the project
  • Any running SSH sessions will be terminated
  • Any running jobs or pods will continue but the user cannot manage them

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Frequently Asked Questions

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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.

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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.

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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.

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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.