perf: bound lake scans and add platform Grafana dashboard

Explorer and exporter were scanning the full Parquet lake every 1–5s
(~2000 files, 200MB+), driving ~2.2 CPU cores. Limit metrics to the
last N flights, cache DuckDB views and the partition tree, slow live
polls to 2s, and keep drones alive after seal to stop restart churn.

Add node-exporter, scan-duration metrics, and a Swarm Platform Grafana
dashboard for node CPU/memory and scan health.

simulator/monitoring/lake.py

@@ -0,0 +1,43 @@
+"""Scan the Hive-partitioned lake without re-reading every historical flight."""
+
+from __future__ import annotations
+
+import os
+from pathlib import Path
+
+
+def flight_window() -> int:
+    return max(1, int(os.environ.get("METRIC_FLIGHT_WINDOW", "5")))
+
+
+def recent_flights(data_dir: Path, dataset: str, limit: int | None = None) -> list[Path]:
+    """Most recently modified flight= partitions for a dataset."""
+    limit = limit or flight_window()
+    base = data_dir / f"dataset={dataset}"
+    if not base.is_dir():
+        return []
+    flights = [p for p in base.iterdir() if p.is_dir() and p.name.startswith("flight=")]
+    flights.sort(key=lambda p: p.stat().st_mtime, reverse=True)
+    return flights[:limit]
+
+
+def parquet_reader(data_dir: Path, dataset: str, *, limit: int | None = None) -> str:
+    """DuckDB read_parquet() source limited to recent flights."""
+    flights = recent_flights(data_dir, dataset, limit)
+    if not flights:
+        path = data_dir / f"dataset={dataset}" / "**" / "*.parquet"
+        return f"'{path}', hive_partitioning=true, union_by_name=true"
+    if len(flights) == 1:
+        return f"'{flights[0]}/**/*.parquet', hive_partitioning=true, union_by_name=true"
+    inner = ", ".join(f"'{f}/**/*.parquet'" for f in flights)
+    return f"[{inner}], hive_partitioning=true, union_by_name=true"
+
+
+def iter_parquet_files(data_dir: Path, *, flight_limit: int | None = None) -> list[Path]:
+    """Parquet paths under recent flights only — avoids full-lake rglob."""
+    limit = flight_limit or flight_window()
+    out: list[Path] = []
+    for ds in ("telemetry", "detections", "state"):
+        for flight in recent_flights(data_dir, ds, limit):
+            out.extend(flight.rglob("*.parquet"))
+    return out