# Organization, Account, and Team Settings
One of the greatest challenges throughout the machine learning (ML) field is collaboration. With large datasets, various projects, complicated file structures, and hundreds of different models, managing a team can present further difficulties to a successful data science workflow.
Addressing this issue is at the heart of cnvrg. The cnvrg platform has comprehensive organization and team management features which allow you to streamline your workflow and enhance your collaboration. Within cnvrg, you can set access levels for global users as well as for specific datasets and projects, ensuring your team has access to only the necessary files. It also centralizes all work and maintains versioning to ensure the entire team is up-to-date.
cnvrg is designed to give certain users complete control over all the settings on both organization and account levels.
The topics in this page:
# Organization Settings
To access and change your organization's settings, click the Settings tab on the left sidebar.
Here you can change and set:
- Default Computes: Set the default compute of a project when created. If a project does not have default computes set in its settings, jobs use the default computes of the organization.
- Install Job Dependencies Automatically: Enable for your custom Docker images to automatically work with all cnvrg features. Read more here.
- Slack Webhook URL: Enter the URL for yor Slack API. Used to enable experiment notifications.
- Debug Time: Set the number of minutes an experiment stays in debug mode. When in debug mode, the user can extend the length for additional 15-minute periods, as desired.
- Queued Compute Wait Time: Set the time for the compute to wait and be available before the job moves to the next compute in the queue.
- Set max duration for: Set timeout periods in minutes for the different job types: workspaces, experiments, endpoints, and webapps.
- Automatically Clear Cached Commits: Set the number of days when inactive caches are automatically cleared from NFS. (Only when Commit Caching is enabled).
Click Update to save any modified settings.
You can edit max duration only if you are an administrator in the organization.
# LDAP Support
cnvrg also supports authorizing users through an LDAP server. If you provide cnvrg access to your LDAP server, cnvrg can query it and authorize user access. To set this up, please contact cnvrg.io support.
# Account Settings
To access and update your account settings, click your profile's name in the top left of the side bar.
You may need to expand the sidebar if it is currently collapsed.
Here you can edit and save all the important details of your account, including:
- Username: Enter your account's name.
- Profile Picture: Click the Choose File button to select a display photo for your account.
- Password: Change your password.
- Bio: Enter a description of your account.
- Company: Enter your company name.
- Time Zone: Enter your local time zone. Used for scheduling jobs.
- Git Access Token: Provide your OAuth token for communicating with Git.
- VSCode Settings: Upload a Visual Studio Code settings file for use with any VSCode workspace you start.
- Default Homepage: Select an organization page that loads upon login.
# Team Page
# New Users of the Platform and an Organization
To add new users to your organization, click the Team tab on the sidebar.
Click Add Members on the top right, add their email, and select their access level. cnvrg sends an email invitation to them.
If the email address is already affiliated with a cnvrg account, cnvrg sends an invitation to the associated organization.
If the email address isn't already affiliated with a cnvrg account, cnvrg sends an invitation to set up a new cnvrg account. By following the link in the invitation, the new member can create an account and automatically become a member of the current organization.
New users can also be added in the cnvrg configuration file within Kubernetes. For assistance, please contact cnvrg.io support.
# Access Levels
cnvrg supports many levels of access that you can set for users in your organization. This allows you to control the content your users can see and the read/write permissions they have. Leveraging the permission levels provides control of what your developers, analysts, and business managers can see and do.
|Provides access to datasets and projects, as well as the ability to manage users and change organization settings.
|Provides access to all datasets and projects.
|Allows access only to datasets and projects they have created or have been added to.
|Provides read only access to datasets and projects they have been added to.
|Revoke Member Access
|Removes the user from your organization.
# Other Team Settings
On the Team page, you can also see each user's:
- Projects (the number of projects they collaborate on)
- Last Seen (the time they last logged into cnvrg)
- Email Invite (the status of the invitation)
- Usage Limit (the user cloud compute budget)
# Project Collaboration
While administrators and managers have automatic access to all projects, data scientists and reviewers must be added to projects as collaborators.
To add another user as a collaborator on a project, navigate to the project's homepage. On the top right, a list of all the current collaborators displays. Click the + to display the project's collaborator management panel. This can also be displayed by navigating to the Project's Settings and selecting Collaborators on the left.
From here, add or delete collaborators for this specific project. This action does not affect their access to other projects.
Data scientists are automatically collaborators on projects they create.
# Dataset Collaboration
Like projects, while administrators and managers have automatic access to all datasets, data scientists and reviewers also must be added to datasets as collaborators.
To add another user as a collaborator on a dataset, navigate to the dataset's homepage, go to its Settings, and select Collaborators on the left.
From here, add or delete collaborators for this specific dataset. This action does not affect their access to other datasets.
Data scientists are automatically collaborators on datasets they create.