fix(metrics): time-series rows get time-ordered ids, so an insert stops costing a disk read (#5149)
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Measured on dev (385a579), agent posts cut to five samples still dropped:
flush=8.8s for 990 rows, 6.6s for 680, 8.4s for 1000 — about 110 rows/s,
~9 ms a row, with rules and evaluation near zero. One random read per
row fits a random uuid4 primary key whose index no longer fits in memory:
every new row lands on a random page of it. (Inferred from the rate; the
table and index sizes have not been read.)

- steward.core.ids.time_ordered_id: a UUIDv7-layout string (48-bit ms
  timestamp, then random), same 36-char shape as the stored uuid4 ids, so
  no migration. Python's uuid7() arrives in 3.14; the image runs 3.13.
- Used for plugin_metrics and its hourly rollup, monitor_results,
  audit_events, the docker metrics/hourly/events/logs tables, and the
  traefik and unifi time series.
- MAX_SAMPLES_PER_INGEST 5 → 2 (~400 rows) for now: it fits the agent's
  10 s even at the old rate, so hosts land data whichever way the new rate
  comes out. Raise it once the new rate is measured.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This commit is contained in:
2026-10-06 18:58:41 -04:00
co-authored by Claude Opus 5.5
parent ade078cabf
commit ad4f7d9232
9 changed files with 83 additions and 21 deletions
+5 -5
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@@ -1,6 +1,5 @@
# plugins/docker/models.py
from __future__ import annotations
import uuid
from datetime import datetime, timezone
from sqlalchemy import (
BigInteger, Boolean, DateTime, Float, ForeignKey, Index, Integer, String, Text,
@@ -8,6 +7,7 @@ from sqlalchemy import (
)
from sqlalchemy.orm import Mapped, mapped_column
from steward.models.base import Base
from steward.core.ids import time_ordered_id
class DockerContainer(Base):
@@ -67,7 +67,7 @@ class DockerMetric(Base):
__tablename__ = "docker_metrics"
id: Mapped[str] = mapped_column(
String(36), primary_key=True, default=lambda: str(uuid.uuid4())
String(36), primary_key=True, default=time_ordered_id
)
host_id: Mapped[str] = mapped_column(
String(36), ForeignKey("hosts.id", ondelete="CASCADE"), nullable=False, index=True
@@ -103,7 +103,7 @@ class DockerMetricHourly(Base):
__tablename__ = "docker_metrics_hourly"
id: Mapped[str] = mapped_column(
String(36), primary_key=True, default=lambda: str(uuid.uuid4())
String(36), primary_key=True, default=time_ordered_id
)
host_id: Mapped[str] = mapped_column(
String(36), ForeignKey("hosts.id", ondelete="CASCADE"), nullable=False
@@ -139,7 +139,7 @@ class DockerEvent(Base):
__tablename__ = "docker_events"
id: Mapped[str] = mapped_column(
String(36), primary_key=True, default=lambda: str(uuid.uuid4())
String(36), primary_key=True, default=time_ordered_id
)
host_id: Mapped[str] = mapped_column(
String(36), ForeignKey("hosts.id", ondelete="CASCADE"), nullable=False
@@ -176,7 +176,7 @@ class DockerLog(Base):
__tablename__ = "docker_logs"
id: Mapped[str] = mapped_column(
String(36), primary_key=True, default=lambda: str(uuid.uuid4())
String(36), primary_key=True, default=time_ordered_id
)
host_id: Mapped[str] = mapped_column(
String(36), ForeignKey("hosts.id", ondelete="CASCADE"), nullable=False, index=True
+3 -1
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@@ -343,7 +343,9 @@ SLOW_INGEST_SECONDS = 2.0
# instance that did not finish inside the agent's 10 s, the rollback left the
# buffer full, and every later post failed the same way. The newest samples
# are kept: the older ones would be lost to the agent's ring buffer anyway.
MAX_SAMPLES_PER_INGEST = 5
# Two (~400 rows) fits 10 s even at the ~110 rows/s measured before
# plugin_metrics got time-ordered ids; raise it once the new rate is known.
MAX_SAMPLES_PER_INGEST = 2
def newest_samples(samples: list, limit: int) -> tuple[list, int]:
+4 -4
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@@ -1,16 +1,16 @@
# plugins/traefik/models.py
from __future__ import annotations
import uuid
from datetime import datetime, timezone
from sqlalchemy import DateTime, Float, Integer, String, Text
from sqlalchemy.orm import Mapped, mapped_column
from steward.models.base import Base
from steward.core.ids import time_ordered_id
class TraefikMetric(Base):
__tablename__ = "traefik_metrics"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=time_ordered_id)
router_name: Mapped[str] = mapped_column(String(255), nullable=False)
scraped_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), nullable=False, default=lambda: datetime.now(timezone.utc)
@@ -41,7 +41,7 @@ class TraefikAccessSummary(Base):
"""Aggregated traffic-origin summary — one row per scheduler tick."""
__tablename__ = "traefik_access_summaries"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=time_ordered_id)
period_start: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
period_end: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
total_requests: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
@@ -57,7 +57,7 @@ class TraefikGlobalStat(Base):
"""One row per scrape — process-level and config stats."""
__tablename__ = "traefik_global_stats"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=time_ordered_id)
scraped_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), nullable=False, default=lambda: datetime.now(timezone.utc)
)
+5 -5
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@@ -1,10 +1,10 @@
# plugins/unifi/models.py
from __future__ import annotations
import uuid
from datetime import datetime, timezone
from sqlalchemy import Boolean, DateTime, Float, Integer, String, Text
from sqlalchemy.orm import Mapped, mapped_column
from steward.models.base import Base
from steward.core.ids import time_ordered_id
# ── Time-series (one row per scrape) ──────────────────────────────────────────
@@ -13,7 +13,7 @@ class UnifiWanStat(Base):
"""WAN interface health — one row per scrape."""
__tablename__ = "unifi_wan_stats"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=time_ordered_id)
scraped_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(timezone.utc))
is_up: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
wan_ip: Mapped[str | None] = mapped_column(String(64), nullable=True)
@@ -27,7 +27,7 @@ class UnifiClientSnapshot(Base):
"""Aggregated client counts + top talkers — one row per scrape."""
__tablename__ = "unifi_client_snapshots"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=time_ordered_id)
scraped_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(timezone.utc))
total_clients: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
wireless_clients: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
@@ -41,7 +41,7 @@ class UnifiWlanStat(Base):
"""Per-SSID/radio stats — one row per scrape per SSID+radio combination."""
__tablename__ = "unifi_wlan_stats"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=time_ordered_id)
scraped_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(timezone.utc))
ssid: Mapped[str] = mapped_column(String(255), nullable=False)
radio: Mapped[str | None] = mapped_column(String(8), nullable=True) # ng=2.4GHz, na=5GHz, 6e=6GHz
@@ -56,7 +56,7 @@ class UnifiDpiSnapshot(Base):
"""DPI application/category traffic snapshot — one row per scrape (JSON blob)."""
__tablename__ = "unifi_dpi_snapshots"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=time_ordered_id)
scraped_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(timezone.utc))
# JSON: [{"cat_id", "cat_name", "rx_bytes", "tx_bytes"}] aggregated across all clients
by_category_json: Mapped[str] = mapped_column(Text, nullable=False, default="[]")