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chore: import upstream snapshot with attribution
2026-07-13 13:10:45 +08:00

95 lines
3.3 KiB
Python

"""Parse-rate tracking for streaming JSON / NDJSON clients.
Vendors occasionally emit a flaky line in an NDJSON stream, so dropping the
odd malformed frame is expected. The risk is when the drop ratio crosses a
threshold (content-type drift, schema break, vendor migration) and we keep
returning empty results to the agent.
``StreamingParseStats`` accumulates per-response parse outcomes;
``report_if_unhealthy`` emits a single Sentry event (with the failure
histogram in extras) when the skip ratio exceeds the threshold, so we do
not spam one event per dropped line.
"""
from __future__ import annotations
import logging
from collections import Counter
from dataclasses import dataclass, field
from platform.observability.errors.boundary import report_exception
#: Default fraction of skipped lines tolerated before a stream is flagged.
DEFAULT_SKIP_THRESHOLD: float = 0.10
#: Decimal places for ``skip_ratio`` in Sentry extras.
_SKIP_RATIO_DECIMAL_PLACES = 3
@dataclass
class StreamingParseStats:
"""Counters for one streaming-parse pass over a vendor response."""
parsed: int = 0
skipped: int = 0
errors: Counter[str] = field(default_factory=Counter)
def record_parsed(self) -> None:
self.parsed += 1
def record_error(self, exc: BaseException) -> None:
self.skipped += 1
self.errors[type(exc).__name__] += 1
@property
def total(self) -> int:
return self.parsed + self.skipped
@property
def skip_ratio(self) -> float:
return self.skipped / self.total if self.total else 0.0
def report_if_unhealthy(
self,
*,
logger: logging.Logger,
integration: str,
source: str,
threshold: float = DEFAULT_SKIP_THRESHOLD,
) -> None:
"""Capture a single Sentry event when the skip ratio exceeds ``threshold``.
No-op for empty streams or healthy ratios. ``integration`` is the vendor
name (``splunk``, ``coralogix``, ...); ``source`` identifies the
endpoint or parse site so dashboards can group by both.
"""
if self.total == 0 or self.skip_ratio <= threshold:
return
# Synthesize an exception so report_exception (which routes through
# Sentry's capture_exception) has something to attach the histogram to.
# Keep the message static per integration so Sentry groups every
# unhealthy response into a single issue; dynamic counts live in
# extras where the dashboard can break them down.
synthetic = RuntimeError(f"{integration}: streaming parse rate unhealthy")
report_exception(
synthetic,
logger=logger,
message="streaming parse-rate unhealthy",
severity="warning",
tags={
"surface": "service_client",
"integration": integration,
"source": source,
"event": "streaming_parse_unhealthy",
},
extras={
"parsed": self.parsed,
"skipped": self.skipped,
"skip_ratio": round(self.skip_ratio, _SKIP_RATIO_DECIMAL_PLACES),
"errors": dict(self.errors),
"threshold": threshold,
},
)
__all__ = ["DEFAULT_SKIP_THRESHOLD", "StreamingParseStats"]