bvandeusenandClaude Opus 5.5
5569f9934e
#5740 "A metric that departs from its normal is recorded as an anomaly to review, and is findable after it ends", milestone 513. - Every minute each learned key's last 15 minutes is judged against its hour's normal: above the usual hold x1.25 and by the metric's floor opens an occurrence, which ends when the level comes back. - metric_anomalies holds one row per item to review; a repeat while it still waits joins it as an occurrence (metric_anomaly_spans). - An ended row nobody reviews within anomalies.review_days (14, Settings -> Thresholds) lapses; an ongoing one never does. - Learning skips every hour an occurrence covers unless its anomaly was marked normal: no normal is learned without review. - Alerts -> Anomalies lists those to review first, then the reviewed and lapsed under day dividers; marking is operator/admin and audited. - The Overview widget and get_overview warn of open ones and count those to review; the host page shows its own; the weekly report lists the week's and the lapsed; MCP list_anomalies and review_anomaly. - Reviewed and lapsed rows are pruned at data.retention_days, and kept in backups like alert history. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
56 lines
2.5 KiB
Python
56 lines
2.5 KiB
Python
"""Metrics that departed from their normal, to review (#5740).
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Revision ID: 0046_metric_anomalies
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Revises: 0045_metric_norms
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Create Date: 2026-10-14
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"""
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from typing import Sequence, Union
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from alembic import op
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import sqlalchemy as sa
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revision: str = "0046_metric_anomalies"
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down_revision: Union[str, None] = "0045_metric_norms"
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branch_labels: Union[str, Sequence[str], None] = None
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depends_on: Union[str, Sequence[str], None] = None
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def upgrade() -> None:
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op.create_table(
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"metric_anomalies",
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sa.Column("id", sa.String(36), primary_key=True),
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sa.Column("source_module", sa.String(64), nullable=False),
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sa.Column("resource_name", sa.String(255), nullable=False),
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sa.Column("metric_name", sa.String(128), nullable=False),
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sa.Column("started_at", sa.DateTime(timezone=True), nullable=False),
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sa.Column("last_started_at", sa.DateTime(timezone=True), nullable=False),
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sa.Column("ended_at", sa.DateTime(timezone=True), nullable=True),
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sa.Column("occurrences", sa.Integer, nullable=False),
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sa.Column("peak_level", sa.Float, nullable=False),
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sa.Column("peak_at", sa.DateTime(timezone=True), nullable=False),
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sa.Column("usual_hold", sa.Float, nullable=False),
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sa.Column("usual_peak", sa.Float, nullable=False),
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sa.Column("review", sa.String(12), nullable=False),
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sa.Column("reviewed_by", sa.String(64), nullable=True),
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sa.Column("reviewed_at", sa.DateTime(timezone=True), nullable=True),
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sa.Column("note", sa.Text, nullable=True),
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)
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op.create_index("ix_metric_anomalies_key", "metric_anomalies",
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["source_module", "resource_name", "metric_name"])
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op.create_index("ix_metric_anomalies_review_last", "metric_anomalies",
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["review", "last_started_at"])
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op.create_table(
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"metric_anomaly_spans",
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sa.Column("id", sa.String(36), primary_key=True),
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sa.Column("anomaly_id", sa.String(36),
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sa.ForeignKey("metric_anomalies.id", ondelete="CASCADE"), nullable=False),
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sa.Column("started_at", sa.DateTime(timezone=True), nullable=False),
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sa.Column("ended_at", sa.DateTime(timezone=True), nullable=True),
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sa.Column("peak_level", sa.Float, nullable=False),
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)
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op.create_index("ix_metric_anomaly_spans_anomaly_id", "metric_anomaly_spans", ["anomaly_id"])
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def downgrade() -> None:
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op.drop_table("metric_anomaly_spans")
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op.drop_table("metric_anomalies")
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