monitors #4
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| name: monitors | |
| # Runs the operational loop -- build, row-level monitors, arrival SLAs, and | |
| # the dry-run ops agent -- on a schedule. This is the check that fires when | |
| # every row-level quality check is silent because nothing new landed: an | |
| # empty delta has no nulls, no duplicates, and nothing out of range. | |
| # | |
| # Every step below gates on a genuine failure (a breach or a crash), never | |
| # on which forecast model won. The scheduled build runs reduced | |
| # (N_TRANSACTIONS=20000, for a fast run), and reduced scale starves the spend | |
| # features: at 5,000 transactions roughly 59% of training rows have every | |
| # spend feature NULL, and 20,000 is still far short of the 250,000 the | |
| # committed report was produced from. Model skill is therefore not a | |
| # meaningful signal here -- see docs/forecast-report.md's small-sample | |
| # caveat, and note that the model does not beat its baseline at full scale | |
| # either, so a skill gate would be permanently red. `make forecast` | |
| # already only fails when the pipeline produced no predictions at all, not | |
| # on model comparison, and the same rule holds here: this workflow must | |
| # never fail because the model "didn't win". | |
| on: | |
| schedule: | |
| - cron: "0 6 * * 1" # weekly, Mondays at 06:00 UTC | |
| workflow_dispatch: | |
| jobs: | |
| run-monitors: | |
| runs-on: ubuntu-latest | |
| steps: | |
| - uses: actions/checkout@v4 | |
| - uses: astral-sh/setup-uv@v3 | |
| - run: uv sync | |
| - name: Build the lakehouse | |
| run: N_TRANSACTIONS=20000 uv run make all | |
| - name: Data quality monitors | |
| run: uv run make monitor | |
| - name: Data arrival SLAs | |
| run: uv run make arrival | |
| - name: Ops agent (dry-run) | |
| run: uv run make agent |