rhoai-basic-workbenches

name	rhoai-basic-workbenches
metadata	{"author":"rhoai3-demo","version":"1.0.0","platform-family":"rhoai","platform-baseline":"repo","ocp-baseline":"repo","skill-group":"RHOAI Platform"}
description	Use when documenting, reviewing, or operating Red Hat OpenShift AI basic workbench administration: opening the Start basic workbench administration interface, starting another user's basic workbench, accessing a user's running basic workbench for troubleshooting, stopping one or all basic workbenches, configuring idle workbench timeout, adding workbench pod tolerations, verifying notebook-controller-culler-config, and troubleshooting Jupyter 404 access errors, workbench startup failures, and database or disk full errors. Do NOT use for project workbench creation or lifecycle (use rhoai-project-workflows), user-facing JupyterLab or code-server IDE workflows (use rhoai-data-science-ide-workflows), user-facing Start basic workbench access from the Enabled applications page (use rhoai-connected-applications), custom workbench image authoring, workbench image import, Gateway API migration, project connections, cluster default PVC size, storage class administration, or live cluster changes without the OpenShift safety guard.

RHOAI Basic Workbenches

Use this skill for administrator workflows around basic workbenches on the active product baseline in docs/PLATFORM_BASELINE.md.

Source Grounding

Read references/source-capture.md before using product behavior details. Official Red Hat documentation is product authority. This skill adapts the official Managing resources chapter to this repo's operations and GitOps review model.

Scope

This skill covers:

• accessing the administration interface for basic workbenches
• starting a basic workbench owned by another user
• accessing another user's running basic workbench to fix configuration errors or troubleshoot environment issues
• stopping one user's basic workbench, multiple selected workbenches, or all running basic workbenches
• configuring idle workbench timeout from cluster settings
• verifying the notebook-controller-culler-config ConfigMap
• adding a toleration key to new workbench pods
• understanding that existing workbench pods receive the toleration only after restart
• troubleshooting common basic workbench administrator issues:
  • Jupyter 404 caused by missing OpenShift AI user group membership
  • workbench startup failure caused by failed pods or insufficient resources
  • database or disk full errors caused by exhausted workbench storage

Use other skills for adjacent work:

• rhoai-project-workflows for project workbench creation, start, update, deletion, connections, and project cluster storage
• rhoai-connected-applications for user-facing Start basic workbench access, image/container/accelerator selection, and settings restart workflow
• rhoai-data-science-ide-workflows for user-facing JupyterLab and code-server IDE workflows and initial symptom capture
• rhoai-workbenches-custom-images for workbench image and Notebook resource authoring
• rhoai-workbench-image-import for dashboard import of existing custom workbench images
• rhoai-workbench-gateway-api-migration for custom workbench image path-prefix behavior
• rhoai-users-groups-access for adding users to OpenShift AI user groups
• rhoai-dashboard-customization for showing or hiding the Start basic workbench tile
• rhoai-cluster-pvc-size and rhoai-storage-classes for storage size and storage class behavior
• env-troubleshoot for broader live cluster diagnostics

Demo Policy

For this repo:

• Prefer project-scoped workbenches for the main demo architecture when the workflow needs projects, connections, data, models, or pipelines.
• Treat basic workbenches as an administrator-managed connected application for lightweight Jupyter workflows and troubleshooting support.
• Document any use of administrator access to another user's workbench as a support action, not a normal collaboration pattern.
• Use idle timeout and stop-all workflows to reduce cluster resource consumption before shutdown or when resource pressure affects the demo.
• Configure tolerations only after the target node taints and intended workbench node pools are documented.
• Do not claim a workbench troubleshooting case is resolved until the user can open the JupyterLab interface or the failure has been escalated to Red Hat Support with logs.

Workflow

1. Confirm the active baseline in docs/PLATFORM_BASELINE.md.
2. Read references/source-capture.md and references/official-doc-extraction.md.
3. Confirm the operator has OpenShift AI administrator privileges.
4. Decide whether the task is:
   • basic workbench administration interface access
   • start, access, or stop another user's basic workbench
   • idle timeout configuration
   • workbench pod toleration configuration
   • one of the documented administrator troubleshooting cases
5. Follow the relevant runbook in examples/basic-workbench-admin-patterns.md.
6. Validate with references/validation-checklist.md.

References

• references/source-capture.md
• references/official-doc-extraction.md
• references/validation-checklist.md
• examples/basic-workbench-admin-patterns.md