---
name: fabric-notebook-loop-7fb051d0ff30
description: Develop Fabric notebooks using a local closed-loop cycle — author in .py locally, build to .Notebook format, deploy via REST API, execute, monitor, diagnose errors, fix, and redeploy. Use for iterative notebook development without portal interaction. Typically converges in 1–3 iterations. Cold-start time varies by capacity tier (≈3 min on F64, up to 8–12 min on F2/F4).
links:
  - skills/fabric-notebook-loop/must
  - skills/fabric-notebook-loop/prefer-avoid
  - skills/fabric-notebook-loop/the-loop
  - skills/fabric-notebook-loop/diagnosing-opaque-failures
  - skills/fabric-notebook-loop/mlflow-platform-limits
  - skills/fabric-notebook-loop/full-example
---

# fabric-notebook-loop

Iterative Fabric notebook development without portal interaction. The skill is split into focused sections — traverse the linked nodes to pick up only what you need:

- [[skills/fabric-notebook-loop/must]] — non-negotiable rules (cell markers, build/deploy/monitor, fetch-then-stop, kernel + sentinel rules)
- [[skills/fabric-notebook-loop/prefer-avoid]] — recommended preferences and the explicit anti-patterns
- [[skills/fabric-notebook-loop/the-loop]] — the author → build → deploy → smoke → fetch cycle, individual commands, cell structure, run-status interpretation
- [[skills/fabric-notebook-loop/diagnosing-opaque-failures]] — three diagnostic paths for `System cancelled the Spark session` and the catalogue of common silent causes
- [[skills/fabric-notebook-loop/mlflow-platform-limits]] — Fabric MLflow experiment-name validation and the SPN `MwcTokenValidationException` that blocks closed-loop MLflow
- [[skills/fabric-notebook-loop/full-example]] — end-to-end CSV-to-Bronze example

For diagnosing opaque smoke-test failures, also see `memory/skill-fixes/smoke-test-cell-errors.md`. For MLflow specifics: `memory/skill-fixes/fabric-mlflow-spn-blocked.md`, `memory/skill-fixes/fabric-mlflow-experiment-name.md`.


---
Source attribution: scardoso-lu
Original project: https://github.com/scardoso-lu/fabric-skills-settings/blob/33534eb185fda573125308a0129457bd65419d13/server/skills/fabric-notebook-loop/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Silvio Cardoso

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: scardoso-lu
Original project: https://github.com/scardoso-lu/fabric-skills-settings/blob/33534eb185fda573125308a0129457bd65419d13/server/skills/fabric-notebook-loop/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Development & Engineering
Roles: Backend Developer, Data Scientist, ML / AI Engineer
Specialties: API, Backend
Tools: Fabric, Mlflow
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 3bb14061622abad8f031a3319d9a6a045ef1fac7ef08c3ca5c34c30409b5ac41