bvandeusenandClaude Opus 5.5
cbbf186f17
plugin_metrics_hourly gains value_p95 beside value_avg and value_max. A two-minute backup spike raises the hour's peak and leaves its p95 low; an hour spent at that level raises both. Learned normals (milestone 513) need that difference to call a recurring spike usual without calling the same level held at another hour usual too. Hours rolled up before this keep a NULL p95 and read as their average. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
85 lines
4.3 KiB
Python
85 lines
4.3 KiB
Python
from __future__ import annotations
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from datetime import datetime, timezone
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from sqlalchemy import DateTime, Float, Index, Integer, String, UniqueConstraint
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from sqlalchemy.orm import Mapped, mapped_column
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from .base import Base
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from steward.core.ids import time_ordered_id
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class PluginMetric(Base):
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__tablename__ = "plugin_metrics"
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id: Mapped[str] = mapped_column(String(36), primary_key=True, default=time_ordered_id)
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source_module: Mapped[str] = mapped_column(String(64), nullable=False)
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resource_name: Mapped[str] = mapped_column(String(255), nullable=False)
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metric_name: Mapped[str] = mapped_column(String(128), nullable=False)
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value: Mapped[float] = mapped_column(Float, nullable=False)
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recorded_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True), nullable=False, default=lambda: datetime.now(timezone.utc)
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)
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# This time-series table grows by (sources × resources × sample cadence); every
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# host-detail / full-metrics / dashboard-widget read filters by
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# (source_module, resource_name) over a recorded_at range. Without these it's a
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# full sequential scan on every load.
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__table_args__ = (
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Index("ix_plugin_metrics_module_resource_recorded",
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"source_module", "resource_name", "recorded_at"),
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# One series over a time range, read from the index alone: `value` is
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# carried in it. Built after boot by core/metric_index.py, not by a
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# migration, since a build over the live table takes minutes (#5490).
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Index("ix_plugin_metrics_series_value",
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"source_module", "resource_name", "metric_name", "recorded_at",
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postgresql_include=["value"]),
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)
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class PluginMetricLatest(Base):
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"""The newest sample of each (source, resource, metric), kept beside
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plugin_metrics by record_metrics so "what is it now" never scans history.
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Postgres has no skip scan, so a newest-per-key query over plugin_metrics
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reads every raw sample in the window: on a seven-day window that took a
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dashboard widget a minute (#5208). This table is one row per key. Retention
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drops a row once its sample has aged out of the raw window, so a resource
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that stopped reporting disappears when its raw history does.
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"""
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__tablename__ = "plugin_metric_latest"
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source_module: Mapped[str] = mapped_column(String(64), primary_key=True)
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resource_name: Mapped[str] = mapped_column(String(255), primary_key=True)
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metric_name: Mapped[str] = mapped_column(String(128), primary_key=True)
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value: Mapped[float] = mapped_column(Float, nullable=False)
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recorded_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
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class PluginMetricHourly(Base):
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"""Hourly rollup of plugin_metrics — the coarse series that retention rolls
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raw samples into before pruning them, so multi-day/week history stays cheap.
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One row per (source_module, resource_name, metric_name, hour bucket); the
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unique constraint is the conflict target for the idempotent rollup upsert.
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Charts read this for the part of a range older than the raw-retention window.
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"""
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__tablename__ = "plugin_metrics_hourly"
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id: Mapped[str] = mapped_column(String(36), primary_key=True, default=time_ordered_id)
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source_module: Mapped[str] = mapped_column(String(64), nullable=False)
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resource_name: Mapped[str] = mapped_column(String(255), nullable=False)
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metric_name: Mapped[str] = mapped_column(String(128), nullable=False)
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bucket: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
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value_avg: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
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value_max: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
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# The level the hour held for all but its briefest 5% (#5738): a spike of
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# a minute or two raises value_max and leaves this low. NULL on hours
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# rolled up before it was kept; read those as value_avg.
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value_p95: Mapped[float | None] = mapped_column(Float, nullable=True)
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sample_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
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__table_args__ = (
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UniqueConstraint("source_module", "resource_name", "metric_name", "bucket",
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name="uq_plugin_metrics_hourly_bucket"),
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Index("ix_plugin_metrics_hourly_lookup",
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"source_module", "resource_name", "metric_name", "bucket"),
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)
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