#6718 "A swarm container's metrics, normal and anomalies are keyed by its task name, so they start over whenever the task moves". The operator: "the metrics should be keys to the service name not the task name... as that's what's consistent between updates." CPU, memory, restart count and health now go under "swarm/<service>", so a normal, its anomalies and an alert rule carry across a redeploy or a move between nodes. Network rates stay "<host>/<service>", the task id gone, as they answer who on a host is sending. Tasks of a multi-task service share the key, so its level reads as an average across them (of 51 live services, only authentik-worker and portainer_agent run more than one task). History under task names moves in a background task, 5000 raw samples every 15 s, not a migration: the raw table holds about 2M such rows and the app would wait on it at boot. Hourly rows combine where two tasks share an hour, and rows still to review merge to one per metric. A service's anomalies no longer reach a host's page, as it has no one host; get_anomaly reads what happened around one from the service's own events. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
114 lines
5.6 KiB
Python
114 lines
5.6 KiB
Python
"""Who sends a host's network traffic (#6115): its containers and NFS mounts,
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ranked against the host's own total over a window.
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A host's net_tx_bps (net_rx_bps) is what its physical interfaces carried; each
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container's comes from Docker ingest (resource "<host>/<service or container>") and each
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NFS mount's from the agent (resource "<host>:<mount>"). All three are read in
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the same time buckets, so the busiest bucket of the host's total can be put
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down to who was sending in it. What no container or mount accounts for is the
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host itself (an apt download, a backup run from the host, a swarm ingress
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hand-off) or a container's traffic that never left the host.
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Imports only the core metric model, like metrics_query, so the docker plugin
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being off leaves just the NFS mounts and the host.
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"""
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from __future__ import annotations
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import re
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from datetime import datetime, timedelta, timezone
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from sqlalchemy import func, select
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from steward.models.metrics import PluginMetric, PluginMetricLatest
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SOURCE_MODULE = "host_agent"
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DIRECTIONS = ("tx", "rx")
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# Buckets a window is cut into: a 1 h window reads per 60 s sample, 24 h per
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# 12 minutes. Narrow the window to see a spike sharper.
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BUCKETS = 120
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# A swarm task's container, "<service>.<slot or node id>.<task id>", is shown
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# by its service, so its tasks over the window add up to one sender.
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_TASK = re.compile(r"^(?P<svc>.+?)\.(?:\d+|[a-z0-9]{25})\.[a-z0-9]{25}$")
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def sender_name(container: str) -> str:
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m = _TASK.match(container)
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return m["svc"] if m else container
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def rank(host: dict, senders: dict, limit: int = 10) -> dict:
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"""`host` is {bucket: bytes a second}; `senders` is {(kind, name):
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{bucket: bytes a second}}. The host's average, its peak and when, and each
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sender's average over the host's buckets (a bucket it is missing from
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counts as 0), its own peak and what it sent in the host's peak bucket,
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biggest at the host's peak first. `unaccounted_*` is what the host carried
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beyond them all, never below 0."""
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if not host:
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return {"host": None, "senders": [], "more": 0, "unaccounted_avg_bps": None,
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"unaccounted_at_peak_bps": None}
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n = len(host)
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peak_at = max(host, key=lambda b: host[b])
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rows = []
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for (kind, name), series in senders.items():
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top = max(series, key=lambda b: series[b])
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rows.append({"kind": kind, "name": name,
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"avg_bps": sum(v for b, v in series.items() if b in host) / n,
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"peak_bps": series[top], "peak_at": top,
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"at_host_peak_bps": series.get(peak_at, 0.0)})
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rows.sort(key=lambda r: (r["at_host_peak_bps"], r["avg_bps"]), reverse=True)
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host_avg = sum(host.values()) / n
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return {
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"host": {"avg_bps": host_avg, "peak_bps": host[peak_at], "peak_at": peak_at},
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"senders": rows[:limit],
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"more": max(0, len(rows) - limit),
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"unaccounted_avg_bps": max(0.0, host_avg - sum(r["avg_bps"] for r in rows)),
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"unaccounted_at_peak_bps": max(0.0, host[peak_at] - sum(r["at_host_peak_bps"] for r in rows)),
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}
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async def senders(session, host_name: str, since: datetime, direction: str = "tx",
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limit: int = 10, raw_days: int = 7) -> dict:
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"""rank() over the raw samples since `since` (no earlier than the raw
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window: the hourly rollup keeps no per-bucket sender to rank). Adds the
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window actually read and its bucket width."""
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if direction not in DIRECTIONS:
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raise ValueError(f"direction is one of {', '.join(DIRECTIONS)}")
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now = datetime.now(timezone.utc)
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since = max(since, now - timedelta(days=raw_days))
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width = max(60, int((now - since).total_seconds() / BUCKETS))
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bucket = func.date_bin(func.make_interval(0, 0, 0, 0, 0, 0, width), PluginMetric.recorded_at,
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func.to_timestamp(0)).label("bucket")
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metric = f"net_{direction}_bps"
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async def named(source, metric_name, prefix):
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# The resources under the host, from the small latest-value table: a
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# prefix LIKE on plugin_metrics itself can't use its index (the
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# column's collation isn't C) and reads the whole table.
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return list((await session.execute(
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select(PluginMetricLatest.resource_name).where(
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PluginMetricLatest.source_module == source, PluginMetricLatest.metric_name == metric_name,
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PluginMetricLatest.resource_name.startswith(prefix, autoescape=True),
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PluginMetricLatest.recorded_at >= since))).scalars())
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async def series(source, metric_name, resources):
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if not resources:
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return []
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return (await session.execute(
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select(PluginMetric.resource_name, bucket, func.avg(PluginMetric.value))
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.where(PluginMetric.source_module == source, PluginMetric.resource_name.in_(resources),
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PluginMetric.metric_name == metric_name, PluginMetric.recorded_at >= since)
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.group_by(PluginMetric.resource_name, bucket))).all()
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host: dict = {}
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for _, b, v in await series(SOURCE_MODULE, metric, [host_name]):
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host[b] = float(v)
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out: dict = {}
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for res, b, v in await series("docker", metric, await named("docker", metric, host_name + "/")):
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key = ("container", sender_name(res[len(host_name) + 1:]))
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out.setdefault(key, {})
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out[key][b] = out[key].get(b, 0.0) + float(v) # a service's tasks add up
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nfs = f"nfs_{direction}_bps"
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for res, b, v in await series(SOURCE_MODULE, nfs, await named(SOURCE_MODULE, nfs, host_name + ":/")):
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out.setdefault(("nfs", res[len(host_name) + 1:]), {})[b] = float(v)
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return {"since": since, "bucket_s": width, "direction": direction, **rank(host, out, limit)}
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