cluster: summarize node load by hardware
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ef2ede2443
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3d21506ff0
@ -66,6 +66,53 @@ _LOAD_TOP_COUNT = 5
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_NAMESPACE_TOP_COUNT = 5
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def _node_usage_by_hardware(node_load: list[dict[str, Any]], node_details: list[dict[str, Any]]) -> list[dict[str, Any]]:
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if not node_load or not node_details:
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return []
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hardware_by_node = _hardware_map(node_details)
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buckets: dict[str, dict[str, list[float]]] = {}
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for entry in node_load:
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if not isinstance(entry, dict):
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continue
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node = entry.get("node")
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if not isinstance(node, str) or not node:
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continue
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hardware = hardware_by_node.get(node, "unknown")
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_append_hardware_usage(buckets, str(hardware), entry)
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return _finalize_hardware_usage(buckets)
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def _hardware_map(node_details: list[dict[str, Any]]) -> dict[str, str]:
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mapping: dict[str, str] = {}
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for node in node_details:
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if not isinstance(node, dict):
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continue
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name = node.get("name")
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if isinstance(name, str) and name:
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mapping[name] = str(node.get("hardware") or "unknown")
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return mapping
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def _append_hardware_usage(buckets: dict[str, dict[str, list[float]]], hardware: str, entry: dict[str, Any]) -> None:
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bucket = buckets.setdefault(hardware, {"load_index": [], "cpu": [], "ram": [], "net": [], "io": []})
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for key in ("load_index", "cpu", "ram", "net", "io"):
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value = entry.get(key)
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if isinstance(value, (int, float)):
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bucket[key].append(float(value))
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def _finalize_hardware_usage(buckets: dict[str, dict[str, list[float]]]) -> list[dict[str, Any]]:
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output: list[dict[str, Any]] = []
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for hardware, metrics in buckets.items():
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row: dict[str, Any] = {"hardware": hardware}
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for key, values in metrics.items():
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if values:
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row[key] = sum(values) / len(values)
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output.append(row)
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output.sort(key=lambda item: (-(item.get("load_index") or 0), item.get("hardware") or ""))
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return output
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@dataclass(frozen=True)
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class ClusterStateSummary:
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nodes_total: int | None
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@ -1771,6 +1818,7 @@ def collect_cluster_state() -> tuple[dict[str, Any], ClusterStateSummary]:
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node_pods,
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)
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metrics["node_load_summary"] = _node_load_summary(metrics.get("node_load", []))
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metrics["node_load_by_hardware"] = _node_usage_by_hardware(metrics.get("node_load", []), node_details)
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snapshot = {
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"collected_at": collected_at.isoformat(),
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