Legacy cloud workflows

This page is retained as a signpost for deployments that still operate the older OpenStack-based CANFAR Cloud workflow. It is not the recommended path for new research workloads. The current user-facing model is the CANFAR Science Platform: launch a Session from a Container Image and use mounted storage or configured VOSpace Services.

If you already have a legacy VM

Follow the instructions supplied by the operator of that deployment for VM creation, network access, firewall rules, quotas, and image selection. Those values are deployment configuration and are not defined by the Python client or CLI documentation in this repository.

Use the legacy VM only for work that depends on its existing environment. Keep new scripts and data in a supported persistent location, and do not assume that a VM path is mounted in a Science Platform Session.

Moving a workflow to Sessions

1. Put the command and its dependencies in a Container Image.
2. Store persistent inputs and outputs under /arc or a VOSpace Service.
3. Use a Notebook or Desktop Session for exploration and a headless Session for unattended commands.
4. Stage remote files to /scratch when a path-oriented program needs a local file, then copy results to persistent storage.

For deployment and operator documentation, see OpenCADC Deployments. For help choosing a supported workflow, contact CANFAR support.