chore: remove Airflow completely from the stack

Drop all four Airflow containers (db, init, webserver, scheduler) from the
mlops compose profile, leaving MLflow as the sole mlops service. Remove
AIRFLOW_* env vars, config fields, health-check entries, DAG trigger code
in admin/bench routes, the airflow_dag_run_id schema column, Airflow nav
links and DAG-run links in the admin UI, the two Airflow DAG files
(bench_dag.py, sim_dag.py), and all related docs/ADR references.
Simulations now run exclusively via the subprocess path.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

ml/README.md

@@ -6,7 +6,7 @@ Python. Owns models, features, training, online scoring.
 |---|---|---|
 | `serving/` | FastAPI online scorer (`/score`, `/generate`) + LiteLLM gateway + prompt registry (`prompts.py`) + JetStream consumers for `signals.>` / `feedback.>`, called by `recommender` | 1–2 |
 | `features/` | context assembler (`context.py`): signals → `PromptContext`; profile-feature schema mirror (`profile_schema.py`); Feast adapter later | 2 |
-| `pipelines/` | batch feature + training DAGs (Prefect/Airflow) | 4 |
+| `pipelines/` | batch feature + training scripts | 4 |
 | `registry/` | MLflow-backed model registry integration | 4 |
 | `experiments/` | A/B assignment + multi-armed bandit policies | 4 |
 | `notebooks/` | research; never imported by production code | — |