Hands-on Labs
Training track
Deploy and execute OSCAR services step by step
This section is designed as a practical training path for users. Each lab follows a repeatable sequence: deploy an OSCAR service (either via the Dashboard or the CLI), review the generated resources, execute the service synchronously or asynchronously, and analyse the generated output data.
Proposal
What are these labs?
- Short context and learning goals for the selected OSCAR services.
- A deployment flow based on the Dashboard so new users can follow it without preparing an FDL first.
- Two validation tracks: synchronous invocation for immediate feedback and asynchronous execution through MinIO events.
- A final checkpoint with logs, expected outputs, and cleanup steps.
Audience
Optimized for onboarding and workshops
- Users only need an OSCAR deployment, Dashboard access, and a sample file to upload.
- The guides stay close to the visual workflow already documented in the Dashboard and invocation sections.
- The same structure can be reused later for other domain-specific OSCAR services.
- Each lab links back to the relevant reference pages instead of duplicating every detail.
Available labs
Lab 01
Deployment and Execution in OSCAR
Deploy the ImageMagick example from OSCAR Hub, run a synchronous smoke test, and then validate the asynchronous file-processing workflow by uploading images to the generated input bucket.
Lab 02
Interactive Analysis
Reuse the ImageMagick service outputs inside a mounted Jupyter environment, then explore the generated images and metrics through an interactive notebook-based analysis workflow.