Monitoring compose profile: dependency-free Prometheus exporter that scans the Parquet output with DuckDB (rows, detections, pose frames, battery, RSSI, link distance, bytes on disk), Prometheus scrape config and a provisioned Grafana dashboard. Demonstrates the observability doctrine: fleet statistics derived from the data platform itself.
133 lines
4.9 KiB
Python
133 lines
4.9 KiB
Python
"""Prometheus exporter over the simulator's Parquet output.
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Periodically scans DATA_DIR with DuckDB and exposes fleet statistics as
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/metrics. Zero dependencies beyond duckdb: the exposition format is plain
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text, served with the standard library HTTP server.
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"""
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from __future__ import annotations
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import os
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import threading
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import time
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from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
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from pathlib import Path
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import duckdb
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DATA_DIR = Path(os.environ.get("DATA_DIR", "./data"))
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PORT = int(os.environ.get("EXPORTER_PORT", "9105"))
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SCAN_INTERVAL_S = float(os.environ.get("SCAN_INTERVAL_S", "5"))
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_lock = threading.Lock()
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_payload = "# swarm exporter starting\n"
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def _q(con: duckdb.DuckDBPyConnection, sql: str) -> list[tuple]:
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try:
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return con.sql(sql).fetchall()
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except duckdb.Error:
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return [] # partitions may not exist yet while the swarm warms up
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def collect() -> str:
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con = duckdb.connect()
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# union_by_name: sensors have different schemas under one dataset glob
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glob = lambda ds: ( # noqa: E731
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f"'{DATA_DIR}/dataset={ds}/**/*.parquet', hive_partitioning=true, union_by_name=true"
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)
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lines: list[str] = []
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def metric(name: str, help_text: str, mtype: str, rows: list[str]) -> None:
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lines.append(f"# HELP {name} {help_text}")
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lines.append(f"# TYPE {name} {mtype}")
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lines.extend(rows)
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metric(
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"swarm_rows_total", "Telemetry rows written per drone and sensor", "gauge",
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[f'swarm_rows_total{{drone="{d}",sensor="{s}"}} {n}'
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for d, s, n in _q(con, f"SELECT drone, sensor, count(*) FROM read_parquet({glob('telemetry')}) GROUP BY 1,2")],
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)
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metric(
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"swarm_detections_total", "Detection events per drone and class", "gauge",
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[f'swarm_detections_total{{drone="{d}",cls="{c}"}} {n}'
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for d, c, n in _q(con, f"SELECT drone, cls, count(*) FROM read_parquet({glob('detections')}) GROUP BY 1,2")],
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)
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metric(
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"swarm_state_frames_total", "Pose broadcast frames per drone and direction", "gauge",
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[f'swarm_state_frames_total{{drone="{d}",direction="{dr}"}} {n}'
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for d, dr, n in _q(con, f"SELECT drone, direction, count(*) FROM read_parquet({glob('state')}) GROUP BY 1,2")],
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)
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metric(
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"swarm_battery_pct", "Latest battery level per drone", "gauge",
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[f'swarm_battery_pct{{drone="{d}"}} {v}'
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for d, v in _q(con, f"""
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SELECT drone, arg_max(level_pct, ts_ns)
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FROM read_parquet({glob('telemetry')})
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WHERE sensor='battery' GROUP BY drone""")],
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)
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metric(
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"swarm_rssi_dbm", "Latest RSSI per drone-peer link", "gauge",
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[f'swarm_rssi_dbm{{drone="{d}",peer="{p}"}} {v}'
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for d, p, v in _q(con, f"""
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SELECT drone, peer_id, arg_max(rssi_dbm, ts_ns)
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FROM read_parquet({glob('telemetry')})
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WHERE sensor='rssi' GROUP BY drone, peer_id""")],
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)
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metric(
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"swarm_peer_distance_m", "Latest inter-drone distance estimate", "gauge",
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[f'swarm_peer_distance_m{{drone="{d}",peer="{p}"}} {v}'
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for d, p, v in _q(con, f"""
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SELECT drone, peer_id, arg_max(distance_m, ts_ns)
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FROM read_parquet({glob('telemetry')})
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WHERE sensor='rssi' GROUP BY drone, peer_id""")],
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)
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files = list(DATA_DIR.rglob("*.parquet"))
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metric(
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"swarm_parquet_bytes", "Bytes on disk per dataset", "gauge",
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[f'swarm_parquet_bytes{{dataset="{ds}"}} {sum(f.stat().st_size for f in files if f"dataset={ds}" in str(f))}'
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for ds in ("telemetry", "detections", "state")],
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)
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metric("swarm_parquet_files", "Parquet files on disk", "gauge",
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[f"swarm_parquet_files {len(files)}"])
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con.close()
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return "\n".join(lines) + "\n"
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def scanner() -> None:
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global _payload
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while True:
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started = time.monotonic()
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try:
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payload = collect()
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except Exception as exc: # keep serving stale metrics over dying
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payload = f"# collect error: {exc}\n"
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with _lock:
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_payload = payload
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time.sleep(max(0.5, SCAN_INTERVAL_S - (time.monotonic() - started)))
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class Handler(BaseHTTPRequestHandler):
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def do_GET(self) -> None: # noqa: N802 — http.server API
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if self.path != "/metrics":
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self.send_response(404)
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self.end_headers()
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return
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with _lock:
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body = _payload.encode()
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self.send_response(200)
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self.send_header("Content-Type", "text/plain; version=0.0.4")
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self.send_header("Content-Length", str(len(body)))
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self.end_headers()
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self.wfile.write(body)
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def log_message(self, *_args: object) -> None:
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pass # scrapes every few seconds; keep the log quiet
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if __name__ == "__main__":
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threading.Thread(target=scanner, daemon=True).start()
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print(f"swarm exporter on :{PORT}/metrics, scanning {DATA_DIR} every {SCAN_INTERVAL_S}s")
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ThreadingHTTPServer(("", PORT), Handler).serve_forever()
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