bvandeusenandClaude Opus 5.5
3cb2a95054
A bundled prometheus plugin, on by default like the other protocol plugins. Targets are rows edited on its page: address, bearer token (encrypted), interval, keep/leave-out name patterns and a series cap. Steward does the filtering; the endpoint serves everything (Archives' ruling). - A 5 s tick scrapes due targets at once, each within a 30 s deadline, and writes the outcome to its row and its series through record_metrics, so alert rules can watch any of them. - Gauges are stored as they are; counters (and a histogram's or summary's _sum/_count) as <name>_per_sec rates from the second scrape. Buckets and quantiles are skipped. A labelled series is stored under "<target>:k=v,…". Each target also records is_up, scrape_ms, series_kept and series_capped. - Pages: targets not answering first, with why; a target's series grouped by metric with their newest values; a chart per series; the editor with Test, which scrapes once and says what would be stored. - The counter-to-rate keeper moves to steward/core/counter_rates.py; SNMP's RateKeeper now scales its rate on top of it. - metric_value reads Prometheus's _seconds as a span and _per_sec as a rate. - The catalog guard treats an empty list as a dynamic source (snmp, prometheus), as the rule form does. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
35 lines
1.2 KiB
Python
35 lines
1.2 KiB
Python
"""A counter's previous sample, to turn the next one into a per-second rate.
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Scrapers that read monotonic counters (SNMP octets, Prometheus *_total)
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store the rate, not the running total. Keys are tuples whose first element
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is the owner (a device, a target), so forgetting an owner drops all of its
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counters at once.
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"""
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from __future__ import annotations
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from datetime import datetime
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class CounterRates:
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"""In memory: after a restart the first sample of each counter gives no
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rate and the second does. A sample lower than the one before (the source
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restarted, or a 32-bit counter wrapped) gives no rate rather than a huge
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negative or wrapped one."""
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def __init__(self) -> None:
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self._last: dict[tuple, tuple[float, datetime]] = {}
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def rate(self, key: tuple, value: float, at: datetime) -> float | None:
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prev = self._last.get(key)
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self._last[key] = (value, at)
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if prev is None:
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return None
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seconds = (at - prev[1]).total_seconds()
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if seconds <= 0 or value < prev[0]:
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return None
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return (value - prev[0]) / seconds
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def forget(self, owner) -> None:
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for key in [k for k in self._last if k[0] == owner]:
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del self._last[key]
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