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Intermediate90 to 180 minutesInstructor visible

AI Engineer Career Path Intermediate lab 2

A learner provisions an isolated ai engineer career path environment and completes a guided operational task.

Business context

Ultiblob uses this exercise to train ai engineer and applied ml engineer candidates on realistic private-cloud lab operations rather than static videos.

Technical objective

Configure the core ai engineer career path services, verify health, and record the result in the lab progress view.

Student instructions

  1. 1Open the lab workspace and review the topology map.
  2. 2Launch the required templates and wait for all provisioning checks to complete.
  3. 3Complete the configuration task in the course module.
  4. 4Run validation and capture the result for instructor review.
  5. 5Create a snapshot before any risky troubleshooting or failure exercise.

Troubleshooting

  • If access fails, confirm the bastion session is active and the instance is not expired.
  • If validation fails, inspect the lab event log before rerunning the check.
  • If configuration drifts, restore the latest clean snapshot and repeat the module task.

Cleanup

  • Export notes or reports required by the instructor.
  • Restore or delete temporary snapshots created during the exercise.
  • Use the teardown action when the module is complete or allow the TTL policy to expire the lab.
Launch flow

Provisioning readiness

Pending
Waiting for launch

Click Launch lab to start the provisioning flow and watch each stage complete.

0%
  1. Request accepted
  2. Capacity reserved
  3. Templates queued
  4. Validation running
  5. Workspace ready
notebook-reachable
Pending
ai-endpoint-reachable
Pending

Required templates

  • Python data science workstation - defined
  • Vector database/RAG node - defined
  • Ollama/LiteLLM client node - defined

Validation checks

  • Notebook reachable: JupyterLab returns a valid login page or authenticated health response.
  • AI endpoint reachable: The model gateway returns at least one allowed model for the tenant.

Expected result

The lab reaches Healthy state for Notebook reachable, AI endpoint reachable.

Reset policy: Student can reset to the last clean snapshot; instructor can force reset from admin view. Teardown policy: Automatic teardown at TTL expiry with manual instructor override for cohorts.