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Version: 25.3

Import from Git repository

Prerequisites

You will need the following to get started:

  • Maintain role permissions (minimum)
  • A compute environment with sufficient resources (scale based on data volume)
  • Data Explorer enabled
  • Git credentials configured in your workspace
  • A Git repository containing a seqera folder

Limitations

  • Compute environments are Platform-specific and cannot be defined in external Git repositories. Select the compute environment when you add a Studio.
  • Data-links currently cannot be referenced in Git repositories. Define data-links when adding a Studio.
  • Git repositories with multiple Studio configurations are not supported. However, it is possible to use a Git repository with multiple branches and a single configuration per branch.

Create configuration files​

.seqera/studio-config.yaml configuration file

Create a .seqera/studio-config.yaml file in the the .seqera/ directory in your repo. Your studio-config.yaml should contain at least schemaVersion , kind and session.template.kind. All other fields are optional.

schemaVersion: "0.0.1"
kind: "studio-config"
session:
    name: "studio-name"                          # Must be unique to a workspace. If undefined, an auto-generated name is used
    description: "desc"                          # Short description of what the Studio is for
    template:
        kind: "registry"|"dockerfile"|"none"     # Required
        registry: "cr.seqera.io/image:latest"    # Ignored for `dockerfile` and `none`
        dockerfile: "Dockerfile"                 # Ignored for `registry` and `none`
    clone:
        enabled: true                            # Clone the contents of the repository to the Studio. Defaults to `true`
        path: "/workspace"                       # Defaults to `/workspace`. If you want to clone to `/workspace/repository` then you need to specify this
    dependencies:
        condaEnvironmentFile: "environment.yaml" # Define additional libraries (and versions). Ignored for `dockerfile`
    computeRequirements:
        awsBatch:                                # Ignored for non-AWS batch CE
            cpu: 2                               # Number of CPUs to use. Defaults to 2
            gpu: 0                               # Number of GPUs to use (if the CE supports GPUs). Defaults to 0
            memory: 8192                         # Memory allocated in MiB. Defaults to 8192.
    environmentVariables:                        # Ordered sequence of elements that are objects (or mappings) of key-value pairs
        -   name: "var1"
            value: "value1"
        -   name: "var2"
            value: "value2"
    management:                                  # Session management settings
        lifespanHours: 1                         # Ignored if workspace lifespan is set
        isPrivate: false                         # Defaults to `false`

The schema can define a Dockerfile, which must be in the .seqera folder. The following limitations apply:

  • You must configure a target repository using the TOWER_DATA_STUDIO_WAVE_CUSTOM_IMAGE_REGISTRY and TOWER_DATA_STUDIO_WAVE_CUSTOM_IMAGE_REPOSITORY environment variables. If no repository configuration is specified, the build will fail.
  • Each workspace must contain credentials with permissions to push to the repository you've specified.
  • The only supported repository and compute environment combination for a fully private Dockerfile-based Studio is ECR and AWS.
  • The files pulled for Dockerbuild context have individual and total file size limits:
    • Individual files cannot be larger than 5 MB.
    • Total file size cannot be more than 10 MB.

Add a Studio​

You can add a Studio by referencing a Git repository containing Studio configuration files. You can also configure the following fields:

  • Git repository: Enter the full URL to your Git repository (e.g., https://github.com/your-org/your-repo).
  • Revision: Select a branch, tag, or commit from the dropdown. The dropdown is dynamically populated based on the repository URL. If no revision is selected, the default branch is used.
  • Install Conda packages: A list of conda packages to include with the Studio. For more information on package syntax, see conda package syntax.
note

You need to configure a target repository using the TOWER_DATA_STUDIO_WAVE_CUSTOM_IMAGE_REGISTRY and TOWER_DATA_STUDIO_WAVE_CUSTOM_IMAGE_REPOSITORY environment variables. If no repository configuration is specified, the build will fail.

  • Resource labels: Any resource label already defined for the compute environment is added by default. Additional custom resource labels can be added or removed as needed.
  • Environment variables: Environment variables for the session. All variables from the selected compute environment are automatically inherited and displayed. Additional session-specific variables can be added. Session-level variables take precedence. To override an inherited variable, define the same key with a different value.
  • Studio name: The name for the Studio.
  • Description (optional): A description for the Studio.
  • Collaboration: Session access permissions. By default, all workspace users with the launch role and above can connect to the session. Toggle Private on to restrict connections to the session creator only.
    note

    When private, workspace administrators can still start, stop, and delete sessions, but cannot connect to them.

  • Session lifespan: The duration the session remains active. Available options depend on your workspace settings:
    • Stop the session automatically after a predefined period of time: An automatic timeout for the session (minimum: 1 hour; maximum: 120 hours; default: 8 hours). If a workspace-level session lifespan is configured, this field cannot be edited. Changes apply only to the current session and revert to default values after the session stops.
    • Keep the session running: Continuous session operation until manually stopped or an error terminates it. The session continues consuming compute resources until stopped.
note

When the Git URL or Revision fields are changed, form field values dynamically update.

Mount data​

Mount data to make them accessible in your session:

  1. Select Mount data to open the data selection modal.
  2. Choose the data to mount.
  3. Select Mount data to confirm.

Once the Studio session is running, mounted data are accessible at /workspace/data/<DATA_LINK_NAME> using the Fusion file system. Data doesn't need to match the compute environment region, though cross-region data transfer (ingress and egress) may increase costs.

Sessions have read-only access to mounted data by default. Enable write permissions by adding AWS S3 buckets as Allowed S3 Buckets in your compute environment configuration.

Files uploaded to a mounted bucket during an active session may not be immediately available within that session. More information.

Repository cloning​

When a Studio session starts from a Git repository, the repository contents are cloned into the session, using the same commit that was selected, or resolved, when the Studio was first created. For example, repository https://github.com/seqeralabs/studio-templates.git clones to /workspace/studio-templates/ with README.md at /workspace/studio-templates/README.md.

You can disable cloning, which allows you to share a public/private template. You can define the clone path configuration in the schema without the need to build a different Docker image.

Limitations​

  • Platform credentials are not shared with the Studio.
  • The .git folder is not synced and you cannot push/pull from the configured repository after initial Studio creation.
  • There are no preprovisioned Git credentials available to use in the Studio.

Save and start​

  1. Review the configuration to ensure all settings are correct.
  2. Save your configuration:
    • To save and immediately start your Studio, select Add and start.
    • To save but not immediately start your Studio, select Add only.

Studios you create will be listed on the Studios landing page with a status of either stopped or starting. Select a Studio to inspect its configuration details.