Merge origin/main into running Command Center
Keep the deployed tree on conflict; integrate the remote Dockhand/CDC tip.
This commit is contained in:
+112
-43
@@ -18,7 +18,7 @@ import json
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import os
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import re
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import uuid
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from collections import deque
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from collections import defaultdict, deque
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from datetime import datetime, timezone
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from typing import Any
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@@ -28,7 +28,8 @@ from fastapi.responses import JSONResponse
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router = APIRouter(prefix="/api/changes", tags=["changes"])
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KAFKA_BOOTSTRAP = os.getenv("KAFKA_BOOTSTRAP", "10.0.21.36:9092")
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RING_SIZE = int(os.getenv("CDC_RING_SIZE", "1000"))
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RING_SIZE = int(os.getenv("CDC_RING_SIZE", "5000"))
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METRICS_RETENTION_MIN = int(os.getenv("CDC_METRICS_RETENTION_MIN", str(24 * 60)))
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# Active CDC topic prefixes -> logical source. Matches Debezium topic.prefix.
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PREFIX_SOURCE = {
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@@ -45,6 +46,8 @@ TOPIC_PATTERN = re.compile(
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OP_MAP = {"c": "insert", "u": "update", "d": "delete", "r": "snapshot"}
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_ring: deque[dict[str, Any]] = deque(maxlen=RING_SIZE)
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# Minute-level rollups — accurate counts beyond the display ring buffer cap.
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_minute_rollups: dict[int, dict[str, Any]] = {}
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_state: dict[str, Any] = {
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"started": False,
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"connected": False,
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@@ -127,6 +130,83 @@ def _parse(topic: str, value: bytes | None) -> dict[str, Any] | None:
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}
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def _record_metrics(entry: dict[str, Any]) -> None:
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"""Track per-minute aggregates for accurate window stats (not ring-limited)."""
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try:
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ts = datetime.fromisoformat(entry["ts"].replace("Z", "+00:00"))
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except Exception:
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ts = datetime.now(timezone.utc)
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minute_key = int(ts.timestamp()) // 60
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bucket = _minute_rollups.setdefault(
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minute_key,
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{"total": 0, "by_source": defaultdict(int), "by_op": defaultdict(int), "by_table": defaultdict(int)},
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)
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bucket["total"] += 1
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bucket["by_source"][entry["source"]] += 1
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bucket["by_op"][entry["op"]] += 1
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bucket["by_table"][entry["table"]] += 1
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cutoff = minute_key - METRICS_RETENTION_MIN
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for old_key in list(_minute_rollups.keys()):
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if old_key < cutoff:
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del _minute_rollups[old_key]
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def _aggregate_window(minutes: int) -> dict[str, Any]:
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"""Aggregate rollup buckets for the requested time window."""
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now = datetime.now(timezone.utc)
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cutoff_minute = int((now.timestamp() - minutes * 60) // 60)
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use_hour_buckets = minutes >= 120
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by_source: dict[str, int] = defaultdict(int)
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by_op: dict[str, int] = defaultdict(int)
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by_table: dict[str, int] = defaultdict(int)
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buckets: dict[str, int] = defaultdict(int)
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total = 0
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for minute_key, bucket in _minute_rollups.items():
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if minute_key < cutoff_minute:
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continue
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total += bucket["total"]
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for k, v in bucket["by_source"].items():
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by_source[k] += v
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for k, v in bucket["by_op"].items():
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by_op[k] += v
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for k, v in bucket["by_table"].items():
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by_table[k] += v
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ts = datetime.fromtimestamp(minute_key * 60, timezone.utc)
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label = ts.strftime("%H:00") if use_hour_buckets else ts.strftime("%H:%M")
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buckets[label] += bucket["total"]
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# Fill chart timeline with zero buckets so the window span is visible.
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if use_hour_buckets:
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span = max(1, (minutes + 59) // 60)
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filled: dict[str, int] = {}
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for i in range(span):
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t = datetime.fromtimestamp(now.timestamp() - (span - 1 - i) * 3600, timezone.utc)
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filled[t.strftime("%H:00")] = buckets.get(t.strftime("%H:00"), 0)
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buckets = filled
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else:
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span = max(1, minutes)
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filled = {}
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for i in range(span):
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t = datetime.fromtimestamp(now.timestamp() - (span - 1 - i) * 60, timezone.utc)
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filled[t.strftime("%H:%M")] = buckets.get(t.strftime("%H:%M"), 0)
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buckets = filled
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return {
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"total": total,
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"by_source": dict(by_source),
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"by_op": dict(by_op),
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"by_table": dict(by_table),
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"buckets": [{"t": k, "n": v} for k, v in sorted(buckets.items())],
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"inserts": by_op.get("insert", 0),
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"updates": by_op.get("update", 0),
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"deletes": by_op.get("delete", 0),
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"rate_per_min": round(total / max(1, minutes), 1),
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}
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async def cdc_consumer_loop() -> None:
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"""Background loop: consume CDC topics and publish each change live."""
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_state["started"] = True
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@@ -158,6 +238,7 @@ async def cdc_consumer_loop() -> None:
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if not entry:
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continue
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_ring.append(entry)
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_record_metrics(entry)
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_state["consumed"] += 1
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_state["last_ts"] = entry["ts"]
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try:
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@@ -182,30 +263,36 @@ async def cdc_consumer_loop() -> None:
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def snapshot(minutes: int = 15) -> dict[str, Any]:
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"""Lightweight CDC snapshot for other modules (Data Flow graph)."""
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cutoff = datetime.now(timezone.utc).timestamp() - minutes * 60
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by_source: dict[str, int] = {}
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total = 0
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for c in _ring:
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try:
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if datetime.fromisoformat(c["ts"]).timestamp() < cutoff:
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continue
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except Exception:
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continue
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total += 1
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by_source[c["source"]] = by_source.get(c["source"], 0) + 1
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return {"connected": _state["connected"], "consumed": _state["consumed"],
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"buffered": len(_ring), "window_total": total, "by_source": by_source}
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agg = _aggregate_window(minutes)
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return {
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"connected": _state["connected"],
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"consumed": _state["consumed"],
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"buffered": len(_ring),
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"window_total": agg["total"],
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"by_source": agg["by_source"],
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}
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# ── Endpoints ────────────────────────────────────────────────────────────────
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@router.get("")
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async def list_changes(
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limit: int = Query(100, le=500),
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limit: int = Query(200, le=1000),
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source: str | None = None,
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op: str | None = None,
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table: str | None = None,
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minutes: int | None = Query(None, le=1440),
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) -> JSONResponse:
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items = list(_ring)
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if minutes is not None:
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cutoff = datetime.now(timezone.utc).timestamp() - minutes * 60
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filtered_by_time: list[dict[str, Any]] = []
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for c in items:
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try:
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if datetime.fromisoformat(c["ts"].replace("Z", "+00:00")).timestamp() >= cutoff:
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filtered_by_time.append(c)
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except Exception:
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continue
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items = filtered_by_time
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if source:
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items = [c for c in items if c["source"] == source]
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if op:
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@@ -217,47 +304,29 @@ async def list_changes(
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"ok": True,
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"changes": items,
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"buffered": len(_ring),
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"buffer_cap": RING_SIZE,
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"connected": _state["connected"],
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"consumed": _state["consumed"],
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"last_error": _state["last_error"],
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"last_ts": _state["last_ts"],
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})
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@router.get("/stats")
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async def change_stats(minutes: int = Query(15, le=240)) -> JSONResponse:
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now = datetime.now(timezone.utc)
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cutoff = now.timestamp() - minutes * 60
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by_source: dict[str, int] = {}
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by_op: dict[str, int] = {}
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by_table: dict[str, int] = {}
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buckets: dict[str, int] = {}
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total = 0
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for c in _ring:
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try:
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t = datetime.fromisoformat(c["ts"]).timestamp()
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except Exception:
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continue
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if t < cutoff:
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continue
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total += 1
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by_source[c["source"]] = by_source.get(c["source"], 0) + 1
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by_op[c["op"]] = by_op.get(c["op"], 0) + 1
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by_table[c["table"]] = by_table.get(c["table"], 0) + 1
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bucket = datetime.fromtimestamp(t, timezone.utc).strftime("%H:%M")
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buckets[bucket] = buckets.get(bucket, 0) + 1
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async def change_stats(minutes: int = Query(15, le=1440)) -> JSONResponse:
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agg = _aggregate_window(minutes)
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return JSONResponse({
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"ok": True,
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"window_minutes": minutes,
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"total": total,
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"by_source": by_source,
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"by_op": by_op,
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"by_table": by_table,
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"buckets": [{"t": k, "n": v} for k, v in sorted(buckets.items())],
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**agg,
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"connected": _state["connected"],
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"consumed": _state["consumed"],
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"buffered": len(_ring),
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"buffer_cap": RING_SIZE,
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"last_ts": _state["last_ts"],
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})
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@router.get("/status")
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async def changes_status() -> JSONResponse:
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return JSONResponse({"ok": True, "buffered": len(_ring), **_state})
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return JSONResponse({"ok": True, "buffered": len(_ring), "buffer_cap": RING_SIZE, **_state})
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+11
-1
@@ -808,11 +808,12 @@ async def collect_full_lab_context(
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if gpu_data is None:
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gpu_data = await collect_gpu_metrics(client, log)
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docker_raw, db_raw, lake_raw, cc_raw, hdfs, etl, objectscale = await asyncio.gather(
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docker_raw, db_raw, lake_raw, cc_raw, gpu_raw, hdfs, etl, objectscale = await asyncio.gather(
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dockhand_containers(client, DOCKHAND_ENVS["docker01"], log),
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dockhand_containers(client, DOCKHAND_ENVS["db02"], log),
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dockhand_containers(client, DOCKHAND_ENVS["lakehouse"], log),
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dockhand_containers(client, DOCKHAND_ENV_COMMAND_CENTER, log),
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dockhand_containers(client, DOCKHAND_ENVS["gpu_dev"], log),
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collect_hdfs(client, log),
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collect_etl(client, log),
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collect_objectscale(client, log),
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@@ -829,6 +830,15 @@ async def collect_full_lab_context(
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databases["inventory"] = {"error": str(exc)}
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lakehouse = await collect_lakehouse(client, lake_raw, log)
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command_center = await collect_command_center(client, cc_raw, log)
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if gpu_data is not None and gpu_raw:
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gpu_running = sum(1 for c in gpu_raw if c.get("state") == "running")
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gpu_data = {
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**gpu_data,
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"dockhand_env": DOCKHAND_ENVS["gpu_dev"],
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"dockhand_containers": _container_rows(gpu_raw, GPU_URL.replace("http://", "").split(":")[0]),
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"dockhand_running": gpu_running,
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"dockhand_total": len(gpu_raw),
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}
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try:
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governance = collect_governance(log)
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@@ -292,7 +292,15 @@ def build_workload_payload(snap: dict[str, Any]) -> dict[str, Any]:
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return {"id": eid, "from": src, "to": dst, "label": label, "kind": kind, "active": active}
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pipeline_ok = etl.get("airflow_healthy") and len(connectors) > 0 and etl.get("kafka_ui_ok")
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direct_pipeline_ok = (
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pipeline_ok
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and lakehouse.get("trino_ok")
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and objectscale_ok
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)
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s3_flow_ok = pipeline_ok and consumer_running and objectscale_ok
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if not s3_flow_ok and direct_pipeline_ok and not consumer_running:
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# Dockhand blind (auth/outage) but ETL + Trino + S3 probes healthy
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s3_flow_ok = True
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topology_edges = [
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_edge("e-seed", "airflow", "db", "seed data", "pipeline", bool(etl.get("airflow_healthy"))),
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