Загрузить файлы в «alert-processor/app»

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2026-08-06 18:34:18 +03:00
parent 5b05a91a15
commit 6454fdea56
5 changed files with 1502 additions and 0 deletions
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from __future__ import annotations
import mimetypes
import uuid
from dataclasses import dataclass
from pathlib import Path
from urllib.parse import quote
import httpx
from app.matrix_token_manager import MatrixTokenManager
@dataclass
class MatrixSendResult:
ok: bool
status_code: int | None
event_id: str | None
error: str | None
content_uri: str | None = None
@dataclass
class MatrixUploadResult:
ok: bool
status_code: int | None
content_uri: str | None
error: str | None
class MatrixNotifier:
def __init__(
self,
homeserver_url: str,
room_id: str,
token_manager: MatrixTokenManager,
message_type: str = "m.notice",
timeout_seconds: float = 10,
verify_tls: bool = True,
) -> None:
self.homeserver_url = homeserver_url.rstrip("/")
self.room_id = room_id
self.token_manager = token_manager
self.message_type = message_type
self.client = httpx.AsyncClient(
timeout=timeout_seconds,
verify=verify_tls,
)
async def close(self) -> None:
await self.client.aclose()
async def send_message(self, body: str) -> MatrixSendResult:
payload = {
"msgtype": self.message_type,
"body": body,
}
return await self._send_room_message(payload)
async def send_image(
self,
file_path: str,
body: str | None = None,
) -> MatrixSendResult:
path = Path(file_path)
if not path.exists() or not path.is_file():
return MatrixSendResult(
ok=False,
status_code=None,
event_id=None,
error=f"Image file not found: {file_path}",
content_uri=None,
)
mime_type, _ = mimetypes.guess_type(path.name)
mime_type = mime_type or "image/png"
data = path.read_bytes()
upload_result = await self._upload_bytes(
filename=path.name,
data=data,
content_type=mime_type,
)
if not upload_result.ok:
return MatrixSendResult(
ok=False,
status_code=upload_result.status_code,
event_id=None,
error=upload_result.error,
content_uri=None,
)
payload = {
"msgtype": "m.image",
"body": body or path.name,
"url": upload_result.content_uri,
"info": {
"mimetype": mime_type,
"size": len(data),
},
}
send_result = await self._send_room_message(payload)
send_result.content_uri = upload_result.content_uri
return send_result
async def _send_room_message(self, payload: dict) -> MatrixSendResult:
txn_id = str(uuid.uuid4())
room_id_encoded = quote(self.room_id, safe="")
url = (
f"{self.homeserver_url}"
f"/_matrix/client/v3/rooms/{room_id_encoded}"
f"/send/m.room.message/{txn_id}"
)
try:
response = await self._request_with_refresh(
method="PUT",
url=url,
json=payload,
headers={"Content-Type": "application/json"},
)
data = response.json() if response.content else {}
if response.is_success:
return MatrixSendResult(
ok=True,
status_code=response.status_code,
event_id=data.get("event_id"),
error=None,
content_uri=None,
)
return MatrixSendResult(
ok=False,
status_code=response.status_code,
event_id=None,
error=str(data),
content_uri=None,
)
except Exception as exc:
return MatrixSendResult(
ok=False,
status_code=None,
event_id=None,
error=str(exc),
content_uri=None,
)
async def _upload_bytes(
self,
filename: str,
data: bytes,
content_type: str,
) -> MatrixUploadResult:
url = f"{self.homeserver_url}/_matrix/media/v3/upload"
try:
response = await self._request_with_refresh(
method="POST",
url=url,
params={"filename": filename},
content=data,
headers={"Content-Type": content_type},
)
payload = response.json() if response.content else {}
if response.is_success:
return MatrixUploadResult(
ok=True,
status_code=response.status_code,
content_uri=payload.get("content_uri"),
error=None,
)
return MatrixUploadResult(
ok=False,
status_code=response.status_code,
content_uri=None,
error=str(payload),
)
except Exception as exc:
return MatrixUploadResult(
ok=False,
status_code=None,
content_uri=None,
error=str(exc),
)
async def _request_with_refresh(
self,
method: str,
url: str,
**kwargs,
) -> httpx.Response:
response = await self._request_once(method, url, **kwargs)
if response.status_code == 401:
await self.token_manager.refresh_if_needed(force=True)
response = await self._request_once(method, url, **kwargs)
return response
async def _request_once(
self,
method: str,
url: str,
**kwargs,
) -> httpx.Response:
token = await self.token_manager.get_access_token()
headers = dict(kwargs.pop("headers", {}) or {})
headers["Authorization"] = f"Bearer {token}"
return await self.client.request(
method=method,
url=url,
headers=headers,
**kwargs,
)
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from __future__ import annotations
import asyncio
import json
import logging
import time
from dataclasses import asdict, dataclass
from pathlib import Path
import httpx
logger = logging.getLogger(__name__)
@dataclass
class MatrixTokenState:
access_token: str
refresh_token: str
expires_at: float | None = None
class MatrixTokenManager:
def __init__(
self,
token_endpoint: str,
client_id: str,
client_secret: str | None,
initial_access_token: str,
initial_refresh_token: str,
initial_expires_in_seconds: int | None,
refresh_margin_seconds: int,
state_file: str,
timeout_seconds: float = 10,
verify_tls: bool = True,
) -> None:
self.token_endpoint = token_endpoint
self.client_id = client_id
self.client_secret = client_secret or None
self.refresh_margin_seconds = refresh_margin_seconds
self.state_path = Path(state_file)
self._lock = asyncio.Lock()
self._stop_event = asyncio.Event()
self._refresh_task: asyncio.Task | None = None
self._refresh_failures = 0
self.client = httpx.AsyncClient(
timeout=timeout_seconds,
verify=verify_tls,
)
state = self._load_state()
if state is None:
expires_at = None
if initial_expires_in_seconds and initial_expires_in_seconds > 0:
expires_at = time.time() + initial_expires_in_seconds
state = MatrixTokenState(
access_token=initial_access_token,
refresh_token=initial_refresh_token,
expires_at=expires_at,
)
self._save_state(state)
self._state = state
def _load_state(self) -> MatrixTokenState | None:
if not self.state_path.exists():
return None
raw = json.loads(self.state_path.read_text(encoding="utf-8"))
return MatrixTokenState(
access_token=raw["access_token"],
refresh_token=raw["refresh_token"],
expires_at=raw.get("expires_at"),
)
def _save_state(self, state: MatrixTokenState) -> None:
self.state_path.write_text(
json.dumps(asdict(state), ensure_ascii=False, indent=2),
encoding="utf-8",
)
def _needs_refresh(self) -> bool:
if not self._state.refresh_token:
return False
if self._state.expires_at is None:
return False
return time.time() >= (self._state.expires_at - self.refresh_margin_seconds)
async def get_access_token(self) -> str:
await self.refresh_if_needed()
return self._state.access_token
async def refresh_if_needed(self, force: bool = False) -> MatrixTokenState:
async with self._lock:
if not force and not self._needs_refresh():
return self._state
data = {
"grant_type": "refresh_token",
"refresh_token": self._state.refresh_token,
"client_id": self.client_id,
}
if self.client_secret:
data["client_secret"] = self.client_secret
response = await self.client.post(
self.token_endpoint,
data=data,
headers={"Content-Type": "application/x-www-form-urlencoded"},
)
response.raise_for_status()
payload = response.json()
access_token = payload["access_token"]
refresh_token = payload.get("refresh_token", self._state.refresh_token)
expires_in = payload.get("expires_in")
expires_at = None
if expires_in is not None:
expires_at = time.time() + int(expires_in)
self._state = MatrixTokenState(
access_token=access_token,
refresh_token=refresh_token,
expires_at=expires_at,
)
self._save_state(self._state)
self._refresh_failures = 0
logger.info("Matrix OAuth token refreshed successfully")
return self._state
def start_background_refresh(self) -> None:
if self._refresh_task is None:
self._refresh_task = asyncio.create_task(self._refresh_loop())
async def _refresh_loop(self) -> None:
while not self._stop_event.is_set():
try:
await self.refresh_if_needed()
except Exception as exc:
self._refresh_failures += 1
logger.exception("Matrix token background refresh failed: %s", exc)
if self._refresh_failures > 0:
sleep_for = min(300, 30 * self._refresh_failures)
else:
sleep_for = 30
if self._state.expires_at is not None:
remaining = int(self._state.expires_at - time.time() - self.refresh_margin_seconds)
sleep_for = max(5, min(60, remaining if remaining > 0 else 5))
try:
await asyncio.wait_for(self._stop_event.wait(), timeout=sleep_for)
except asyncio.TimeoutError:
pass
async def close(self) -> None:
self._stop_event.set()
if self._refresh_task is not None:
self._refresh_task.cancel()
try:
await self._refresh_task
except asyncio.CancelledError:
pass
await self.client.aclose()
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from __future__ import annotations
from datetime import datetime
from typing import Any
from pydantic import BaseModel, Field
class NormalizedEvent(BaseModel):
source: str = "zabbix"
correlation_id: str
received_at: datetime
remote_addr: str | None = None
event_id: str | None = None
problem_id: str | None = None
event_type: str = "problem"
timestamp: datetime | None = None
severity: str | None = None
severity_code: int | None = None
host: str | None = None
host_id: str | None = None
service: str | None = None
trigger_name: str | None = None
trigger_id: str | None = None
item_id: str | None = None
value: str | None = None
opdata: str | None = None
zabbix_url: str | None = None
event_url: str | None = None
graph_url: str | None = None
graph_image_path: str | None = None
zabbix_context: dict[str, Any] = Field(default_factory=dict)
tags: dict[str, str] = Field(default_factory=dict)
raw_payload: dict[str, Any]
class ProcessorForwardEnvelope(BaseModel):
event: NormalizedEvent
class NotificationDecision(BaseModel):
notify: bool
severity: str | None = None
channels: list[str] = Field(default_factory=list)
reason: str
routing_class: str
fingerprint: str | None = None
repeat_count: int = 1
suppressed: bool = False
suppress_reason: str | None = None
event_phase: str = "problem"
open_incident_found: bool = False
recovered_from_severity: str | None = None
flap_detected: bool = False
flap_event_count: int = 0
flap_reason: str | None = None
triage_applied: bool = False
triage_source: str | None = None
triage_verdict: str | None = None
triage_reason: str | None = None
triage_classification: str | None = None
correlation_applied: bool = False
correlation_role: str | None = None
correlation_group_id: str | None = None
correlation_kind: str | None = None
correlation_reason: str | None = None
correlation_source: str | None = None
correlation_confidence: str | None = None
parent_event_id: str | None = None
parent_correlation_id: str | None = None
root_cause_candidate: bool = False
correlated_event_count: int = 0
llm_enriched: bool = False
remediation_summary: str | None = None
remediation_steps: list[str] = Field(default_factory=list)
remediation_commands: list[str] = Field(default_factory=list)
class ProcessorAck(BaseModel):
accepted: bool
correlation_id: str
decision: NotificationDecision
message: str
class IngestAck(BaseModel):
accepted: bool
correlation_id: str
queued: bool
job_id: str
message: str
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from __future__ import annotations
from app.models import NormalizedEvent, NotificationDecision
HIGH_SEVERITIES = {"high", "disaster"}
AVERAGE_SEVERITIES = {"average"}
LOW_SEVERITIES = {"warning", "information", "not classified", "not_classified", "info"}
RECOVERY_EVENT_TYPES = {"recovery", "resolved", "resolve", "ok", "clear", "closed"}
def normalize_severity(value: str | None) -> str | None:
if value is None:
return None
return value.strip().lower()
def normalize_event_phase(event_type: str | None, value: str | None = None) -> str:
raw = (event_type or "").strip().lower()
if raw in RECOVERY_EVENT_TYPES:
return "recovery"
if not raw and str(value or "").strip() == "0":
return "recovery"
return "problem"
def evaluate_event(
event: NormalizedEvent,
fingerprint: str,
repeat_count: int,
) -> NotificationDecision:
severity = normalize_severity(event.severity)
if severity in HIGH_SEVERITIES:
return NotificationDecision(
notify=True,
severity=event.severity,
channels=["matrix", "mail"],
reason="Severity is High/Disaster: mandatory notification",
routing_class="high_priority",
fingerprint=fingerprint,
repeat_count=repeat_count,
event_phase="problem",
)
if severity in AVERAGE_SEVERITIES:
return NotificationDecision(
notify=True,
severity=event.severity,
channels=["matrix"],
reason="Severity is Average: notify by deterministic baseline policy",
routing_class="average_priority",
fingerprint=fingerprint,
repeat_count=repeat_count,
event_phase="problem",
)
if severity in LOW_SEVERITIES:
return NotificationDecision(
notify=False,
severity=event.severity,
channels=[],
reason="Severity is Warning or lower: held for triage/suppress pipeline",
routing_class="low_priority",
fingerprint=fingerprint,
repeat_count=repeat_count,
event_phase="problem",
)
return NotificationDecision(
notify=False,
severity=event.severity,
channels=[],
reason="Unknown severity: conservative hold until policy is expanded",
routing_class="unknown_priority",
fingerprint=fingerprint,
repeat_count=repeat_count,
event_phase="problem",
)
def build_recovery_decision(
fingerprint: str,
repeat_count: int,
open_incident_found: bool,
previous_severity: str | None,
previous_channels: list[str] | None,
previous_routing_class: str | None,
) -> NotificationDecision:
severity_norm = normalize_severity(previous_severity)
if not open_incident_found:
return NotificationDecision(
notify=False,
severity=previous_severity,
channels=[],
reason="Recovery received but no matching open incident was found",
routing_class="recovery_ignored",
fingerprint=fingerprint,
repeat_count=repeat_count,
event_phase="recovery",
open_incident_found=False,
recovered_from_severity=previous_severity,
)
if previous_routing_class == "triage_low_priority_notify":
return NotificationDecision(
notify=True,
severity=previous_severity,
channels=previous_channels or ["matrix"],
reason="Recovery matched a triaged low-severity incident",
routing_class="recovery_triage_low_priority",
fingerprint=fingerprint,
repeat_count=repeat_count,
event_phase="recovery",
open_incident_found=True,
recovered_from_severity=previous_severity,
)
if severity_norm in HIGH_SEVERITIES:
return NotificationDecision(
notify=True,
severity=previous_severity,
channels=previous_channels or ["matrix", "mail"],
reason="Recovery matched an open High/Disaster incident",
routing_class="recovery_high_priority",
fingerprint=fingerprint,
repeat_count=repeat_count,
event_phase="recovery",
open_incident_found=True,
recovered_from_severity=previous_severity,
)
if severity_norm in AVERAGE_SEVERITIES:
return NotificationDecision(
notify=True,
severity=previous_severity,
channels=previous_channels or ["matrix"],
reason="Recovery matched an open Average incident",
routing_class="recovery_average_priority",
fingerprint=fingerprint,
repeat_count=repeat_count,
event_phase="recovery",
open_incident_found=True,
recovered_from_severity=previous_severity,
)
return NotificationDecision(
notify=False,
severity=previous_severity,
channels=[],
reason="Recovery matched a low-priority incident: no notification by baseline policy",
routing_class="recovery_low_priority",
fingerprint=fingerprint,
repeat_count=repeat_count,
event_phase="recovery",
open_incident_found=True,
recovered_from_severity=previous_severity,
)
def decision_supports_suppress(decision: NotificationDecision) -> bool:
return decision.routing_class == "average_priority" and decision.notify
def decision_supports_flap_suppress(decision: NotificationDecision) -> bool:
return decision.routing_class in {
"average_priority",
"recovery_average_priority",
} and decision.notify
def is_low_severity_problem_candidate(
decision: NotificationDecision,
) -> bool:
return decision.event_phase == "problem" and decision.routing_class == "low_priority"
def apply_suppress_window(
decision: NotificationDecision,
ttl_seconds: int,
) -> NotificationDecision:
return decision.model_copy(
update={
"notify": False,
"channels": [],
"suppressed": True,
"suppress_reason": f"Suppress window active, {ttl_seconds}s remaining",
"reason": "Duplicate Average event suppressed by re-notify window",
}
)
def apply_flap_suppress(
decision: NotificationDecision,
event_count: int,
window_seconds: int,
) -> NotificationDecision:
return decision.model_copy(
update={
"notify": False,
"channels": [],
"suppressed": True,
"flap_detected": True,
"flap_event_count": event_count,
"flap_reason": f"Flapping detected: {event_count} phase changes within {window_seconds}s",
"reason": "Average event suppressed because the series is flapping",
}
)
def apply_low_severity_triage(
decision: NotificationDecision,
verdict: str,
classification: str | None,
reason: str | None,
source: str,
) -> NotificationDecision:
verdict_norm = (verdict or "hold").strip().lower()
classification_norm = (classification or "unknown").strip().lower()
reason_text = (reason or "").strip() or "LLM triage applied"
common = {
"triage_applied": True,
"triage_source": source,
"triage_verdict": verdict_norm,
"triage_reason": reason_text,
"triage_classification": classification_norm,
}
if verdict_norm == "notify":
return decision.model_copy(
update={
**common,
"notify": True,
"suppressed": False,
"suppress_reason": None,
"channels": ["matrix"],
"routing_class": "triage_low_priority_notify",
"reason": f"LLM triage marked low-severity event as actionable: {reason_text}",
}
)
if verdict_norm == "suppress":
return decision.model_copy(
update={
**common,
"notify": False,
"suppressed": True,
"channels": [],
"routing_class": "triage_low_priority_suppressed",
"reason": "LLM triage suppressed low-severity event",
"suppress_reason": reason_text,
}
)
return decision.model_copy(
update={
**common,
"notify": False,
"suppressed": False,
"channels": [],
"routing_class": "triage_low_priority_hold",
"reason": f"LLM triage kept low-severity event on hold: {reason_text}",
}
)
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from __future__ import annotations
import logging
from app.audit_logger import AuditLogger
from app.config import settings
from app.correlation import (
CorrelationAssessment,
CorrelationRegistry,
apply_correlation_to_decision,
assess_correlation,
)
from app.fingerprint import build_fingerprint
from app.llm_correlation import LLMCorrelationAdapter, LLMCorrelationResult
from app.llm_remediation import LLMRemediationAdapter
from app.llm_triage import LLMTriageAdapter
from app.models import NotificationDecision, ProcessorForwardEnvelope
from app.notifications.dispatcher import NotificationDispatcher
from app.policy import (
apply_flap_suppress,
apply_low_severity_triage,
apply_suppress_window,
build_recovery_decision,
decision_supports_flap_suppress,
decision_supports_suppress,
evaluate_event,
is_low_severity_problem_candidate,
normalize_event_phase,
)
from app.redis_repo import FlapState, OpenIncidentState, RedisStateRepository
from app.zabbix_enricher import ZabbixEnricher
logger = logging.getLogger(__name__)
def _confidence_rank(value: str | None) -> int:
normalized = (value or "").strip().lower()
if normalized == "high":
return 3
if normalized == "medium":
return 2
if normalized == "low":
return 1
return 0
def _is_high_or_disaster(severity: str | None) -> bool:
value = (severity or "").strip().lower()
return value in {"high", "disaster"}
class ProcessorService:
def __init__(
self,
redis_repo: RedisStateRepository,
notification_dispatcher: NotificationDispatcher,
zabbix_enricher: ZabbixEnricher | None = None,
llm_remediation_adapter: LLMRemediationAdapter | None = None,
llm_triage_adapter: LLMTriageAdapter | None = None,
correlation_registry: CorrelationRegistry | None = None,
audit_logger: AuditLogger | None = None,
llm_correlation_adapter: LLMCorrelationAdapter | None = None,
) -> None:
self.redis_repo = redis_repo
self.notification_dispatcher = notification_dispatcher
self.zabbix_enricher = zabbix_enricher
self.llm_remediation_adapter = llm_remediation_adapter
self.llm_triage_adapter = llm_triage_adapter
self.correlation_registry = correlation_registry
self.audit_logger = audit_logger
self.llm_correlation_adapter = llm_correlation_adapter
async def process(self, envelope: ProcessorForwardEnvelope) -> NotificationDecision:
event = envelope.event
fingerprint = build_fingerprint(event)
repeat_count = 1
event_phase = normalize_event_phase(event.event_type, event.value)
async def audit(stage: str, status: str = "ok", details: dict | None = None) -> None:
if self.audit_logger is not None:
await self.audit_logger.log_stage(
correlation_id=event.correlation_id,
event_id=event.event_id,
stage=stage,
status=status,
details=details,
)
flap_state = FlapState(
active=False,
event_count=0,
phases=[],
window_seconds=settings.flap_window_seconds,
)
fp_state = await self.redis_repo.update_fingerprint_state(
fingerprint=fingerprint,
event=event,
)
repeat_count = fp_state.count
await self.redis_repo.save_event_snapshot(
event=event,
fingerprint=fingerprint,
repeat_count=repeat_count,
)
await audit(
"state_updated",
details={
"fingerprint": fingerprint,
"repeat_count": repeat_count,
"event_phase": event_phase,
},
)
if settings.flap_enabled:
flap_state = await self.redis_repo.record_phase_transition(
fingerprint=fingerprint,
event_phase=event_phase,
correlation_id=event.correlation_id,
event_id=event.event_id,
)
await audit(
"flap_evaluated",
details={
"flap_active": flap_state.active,
"flap_event_count": flap_state.event_count,
"window_seconds": flap_state.window_seconds,
},
)
baseline_low_severity_candidate = False
if event_phase == "recovery":
open_incident: OpenIncidentState | None = await self.redis_repo.get_open_incident(
fingerprint
)
decision = build_recovery_decision(
fingerprint=fingerprint,
repeat_count=repeat_count,
open_incident_found=open_incident is not None,
previous_severity=open_incident.severity if open_incident else None,
previous_channels=open_incident.channels if open_incident else None,
previous_routing_class=open_incident.routing_class if open_incident else None,
)
if (
flap_state.active
and settings.flap_enabled
and settings.flap_apply_to_average
and decision_supports_flap_suppress(decision)
):
decision = apply_flap_suppress(
decision=decision,
event_count=flap_state.event_count,
window_seconds=flap_state.window_seconds,
)
await self.redis_repo.clear_suppress_window(fingerprint)
await self.redis_repo.clear_open_incident(fingerprint)
else:
decision = evaluate_event(
event=event,
fingerprint=fingerprint,
repeat_count=repeat_count,
)
if (
flap_state.active
and settings.flap_enabled
and settings.flap_apply_to_average
and decision_supports_flap_suppress(decision)
):
decision = apply_flap_suppress(
decision=decision,
event_count=flap_state.event_count,
window_seconds=flap_state.window_seconds,
)
elif (
settings.suppress_enabled
and settings.suppress_apply_to_average
and decision_supports_suppress(decision)
):
suppress_state = await self.redis_repo.get_suppress_state(fingerprint)
if suppress_state.active:
decision = apply_suppress_window(
decision=decision,
ttl_seconds=suppress_state.ttl_seconds,
)
elif decision.notify:
await self.redis_repo.activate_suppress_window(fingerprint)
baseline_low_severity_candidate = (
settings.llm_triage_enabled
and self.llm_triage_adapter is not None
and is_low_severity_problem_candidate(decision)
and not decision.suppressed
)
await audit(
"baseline_policy_applied",
details={
"notify": decision.notify,
"suppressed": decision.suppressed,
"routing_class": decision.routing_class,
"reason": decision.reason,
},
)
should_enrich = self.zabbix_enricher is not None
if settings.zabbix_enrich_only_notify:
should_enrich = should_enrich and (
(decision.notify and not decision.suppressed) or baseline_low_severity_candidate
)
if should_enrich and self.zabbix_enricher is not None:
try:
await self.zabbix_enricher.enrich_event(event)
await audit(
"zabbix_enrichment",
details={
"event_url": event.event_url,
"graph_url": event.graph_url,
"graph_image_path": event.graph_image_path,
"zabbix_context_keys": sorted(list((event.zabbix_context or {}).keys())),
},
)
except Exception as exc:
await audit(
"zabbix_enrichment",
status="error",
details={"error": str(exc)},
)
logger.exception(
"Zabbix enrichment failed: correlation_id=%s event_id=%s error=%s",
event.correlation_id,
event.event_id,
exc,
)
if baseline_low_severity_candidate and self.llm_triage_adapter is not None:
triage_applied = False
cached = await self.redis_repo.get_triage_cache(
fingerprint=fingerprint,
severity=decision.severity,
)
if cached is not None:
decision = apply_low_severity_triage(
decision=decision,
verdict=cached.verdict,
classification=cached.classification,
reason=cached.reason,
source="cache",
)
triage_applied = True
await audit(
"llm_triage",
details={
"source": "cache",
"verdict": cached.verdict,
"classification": cached.classification,
"reason": cached.reason,
},
)
logger.info(
"LLM triage reused from cache: correlation_id=%s event_id=%s verdict=%s classification=%s ttl=%s",
event.correlation_id,
event.event_id,
cached.verdict,
cached.classification,
cached.ttl_seconds,
)
if not triage_applied:
try:
triage = await self.llm_triage_adapter.generate(envelope, decision)
if triage.ok:
decision = apply_low_severity_triage(
decision=decision,
verdict=triage.verdict,
classification=triage.classification,
reason=triage.reason,
source="llm",
)
await self.redis_repo.save_triage_cache(
fingerprint=fingerprint,
severity=decision.severity,
verdict=triage.verdict,
classification=triage.classification,
reason=triage.reason,
source="llm",
)
await audit(
"llm_triage",
details={
"source": "llm",
"verdict": triage.verdict,
"classification": triage.classification,
"reason": triage.reason,
},
)
else:
await audit(
"llm_triage",
status="error",
details={"error": triage.error},
)
logger.warning(
"LLM triage returned no usable content: correlation_id=%s event_id=%s error=%s",
event.correlation_id,
event.event_id,
triage.error,
)
except Exception as exc:
await audit(
"llm_triage",
status="error",
details={"error": str(exc)},
)
logger.exception(
"LLM triage failed: correlation_id=%s event_id=%s error=%s",
event.correlation_id,
event.event_id,
exc,
)
if (
settings.correlation_enabled
and self.correlation_registry is not None
and decision.event_phase == "problem"
):
try:
zbx_context = event.zabbix_context or {}
scope_keys = list(zbx_context.get("correlation_scopes") or [])
recent = await self.redis_repo.get_recent_correlation_events(
host=event.host,
scope_keys=scope_keys,
window_seconds=settings.correlation_window_seconds,
)
deterministic_assessment = assess_correlation(
envelope=envelope,
decision=decision,
recent_events=recent,
registry=self.correlation_registry,
)
chosen_assessment: CorrelationAssessment | None = (
deterministic_assessment if deterministic_assessment.applied else None
)
strong_deterministic = (
deterministic_assessment.applied
and deterministic_assessment.role in {"root", "child"}
)
if (
self.llm_correlation_adapter is not None
and settings.llm_correlation_enabled
and not strong_deterministic
):
try:
llm_result = await self.llm_correlation_adapter.generate(
envelope=envelope,
decision=decision,
recent_events=recent,
)
llm_assessment = self._build_llm_correlation_assessment(
llm_result=llm_result,
decision=decision,
event=envelope.event,
)
if llm_assessment is not None:
chosen_assessment = llm_assessment
await audit(
"llm_correlation",
details={
"role": llm_assessment.role,
"kind": llm_assessment.kind,
"reason": llm_assessment.reason,
"confidence": llm_assessment.confidence,
"parent_event_id": llm_assessment.parent_event_id,
"parent_correlation_id": llm_assessment.parent_correlation_id,
"suppress_child": llm_assessment.suppress_child,
"scope_keys": scope_keys,
},
)
else:
await audit(
"llm_correlation",
status="skipped",
details={
"reason": llm_result.reason,
"confidence": llm_result.confidence,
"error": llm_result.error,
"scope_keys": scope_keys,
},
)
except Exception as exc:
await audit(
"llm_correlation",
status="error",
details={"error": str(exc), "scope_keys": scope_keys},
)
logger.exception(
"LLM correlation fallback failed: correlation_id=%s event_id=%s error=%s",
event.correlation_id,
event.event_id,
exc,
)
if chosen_assessment is not None:
decision = apply_correlation_to_decision(
decision=decision,
assessment=chosen_assessment,
)
await self.redis_repo.save_correlation_event(
host=event.host or "",
event_id=event.event_id,
correlation_id=event.correlation_id,
kind=chosen_assessment.kind,
severity=decision.severity,
routing_class=decision.routing_class,
fingerprint=decision.fingerprint,
root_candidate=chosen_assessment.root_cause_candidate,
role=chosen_assessment.role,
group_id=chosen_assessment.group_id,
parent_event_id=chosen_assessment.parent_event_id,
parent_correlation_id=chosen_assessment.parent_correlation_id,
scope_keys=scope_keys,
tags=event.tags,
service=zbx_context.get("service") or event.service,
scope=zbx_context.get("scope"),
component=zbx_context.get("component"),
domain=zbx_context.get("domain"),
)
await audit(
"correlation",
details={
"applied": chosen_assessment.applied,
"role": chosen_assessment.role,
"kind": chosen_assessment.kind,
"group_id": chosen_assessment.group_id,
"parent_event_id": chosen_assessment.parent_event_id,
"parent_correlation_id": chosen_assessment.parent_correlation_id,
"root_cause_candidate": chosen_assessment.root_cause_candidate,
"correlated_event_count": chosen_assessment.correlated_event_count,
"reason": chosen_assessment.reason,
"suppress_child": chosen_assessment.suppress_child,
"source": chosen_assessment.source,
"confidence": chosen_assessment.confidence,
"scope_keys": scope_keys,
},
)
except Exception as exc:
await audit(
"correlation",
status="error",
details={"error": str(exc)},
)
logger.exception(
"Correlation baseline failed: correlation_id=%s event_id=%s error=%s",
event.correlation_id,
event.event_id,
exc,
)
if (
decision.event_phase == "problem"
and decision.notify
and not decision.suppressed
and decision.routing_class in {
"high_priority",
"average_priority",
"triage_low_priority_notify",
}
):
await self.redis_repo.upsert_open_incident(
fingerprint=fingerprint,
event=event,
decision=decision,
)
if (
self.llm_remediation_adapter is not None
and decision.event_phase == "problem"
and decision.notify
and not decision.suppressed
):
try:
remediation = await self.llm_remediation_adapter.generate(envelope, decision)
if remediation.ok:
decision = decision.model_copy(
update={
"llm_enriched": True,
"remediation_summary": remediation.summary,
"remediation_steps": remediation.steps,
"remediation_commands": remediation.commands,
}
)
await audit(
"llm_remediation",
details={
"summary": remediation.summary,
"steps_count": len(remediation.steps),
"commands_count": len(remediation.commands),
},
)
else:
await audit(
"llm_remediation",
status="error",
details={"error": remediation.error},
)
logger.warning(
"LLM remediation returned no usable content: correlation_id=%s event_id=%s error=%s",
event.correlation_id,
event.event_id,
remediation.error,
)
except Exception as exc:
await audit(
"llm_remediation",
status="error",
details={"error": str(exc)},
)
logger.exception(
"LLM remediation failed: correlation_id=%s event_id=%s error=%s",
event.correlation_id,
event.event_id,
exc,
)
if self.audit_logger is not None:
await self.audit_logger.log_decision(
envelope=envelope,
decision=decision,
)
logger.info(
"Processed event: correlation_id=%s event_id=%s event_phase=%s severity=%s "
"host=%s trigger=%s fingerprint=%s repeat_count=%s "
"open_incident_found=%s flap_detected=%s flap_event_count=%s "
"notify=%s suppressed=%s channels=%s reason=%s "
"triage_applied=%s triage_source=%s triage_verdict=%s triage_classification=%s triage_reason=%s "
"correlation_applied=%s correlation_role=%s correlation_kind=%s correlation_group_id=%s parent_event_id=%s root_cause_candidate=%s correlated_event_count=%s correlation_reason=%s correlation_source=%s correlation_confidence=%s "
"suppress_reason=%s flap_reason=%s recovered_from_severity=%s "
"event_url=%s graph_url=%s llm_enriched=%s",
event.correlation_id,
event.event_id,
decision.event_phase,
event.severity,
event.host,
event.trigger_name,
fingerprint,
repeat_count,
decision.open_incident_found,
decision.flap_detected,
decision.flap_event_count,
decision.notify,
decision.suppressed,
",".join(decision.channels),
decision.reason,
decision.triage_applied,
decision.triage_source,
decision.triage_verdict,
decision.triage_classification,
decision.triage_reason,
decision.correlation_applied,
decision.correlation_role,
decision.correlation_kind,
decision.correlation_group_id,
decision.parent_event_id,
decision.root_cause_candidate,
decision.correlated_event_count,
decision.correlation_reason,
decision.correlation_source,
decision.correlation_confidence,
decision.suppress_reason,
decision.flap_reason,
decision.recovered_from_severity,
event.event_url,
event.graph_url,
decision.llm_enriched,
)
dispatch_report = await self.notification_dispatcher.dispatch(
envelope=envelope,
decision=decision,
)
delivery_payload = {
"attempted": dispatch_report.attempted,
"matrix_attempted": dispatch_report.matrix_attempted,
"matrix_sent": dispatch_report.matrix_sent,
"matrix_event_id": dispatch_report.matrix_event_id,
"matrix_error": dispatch_report.matrix_error,
"matrix_image_attempted": dispatch_report.matrix_image_attempted,
"matrix_image_sent": dispatch_report.matrix_image_sent,
"matrix_image_event_id": dispatch_report.matrix_image_event_id,
"matrix_image_mxc_uri": dispatch_report.matrix_image_mxc_uri,
"matrix_image_error": dispatch_report.matrix_image_error,
"mail_attempted": dispatch_report.mail_attempted,
"mail_sent": dispatch_report.mail_sent,
"mail_error": dispatch_report.mail_error,
"errors": dispatch_report.errors,
}
if self.audit_logger is not None:
await self.audit_logger.log_delivery(
envelope=envelope,
delivery_payload=delivery_payload,
)
if dispatch_report.matrix_attempted:
if dispatch_report.matrix_sent:
logger.info(
"Matrix notification sent: correlation_id=%s event_id=%s matrix_event_id=%s",
event.correlation_id,
event.event_id,
dispatch_report.matrix_event_id,
)
else:
logger.error(
"Matrix notification failed: correlation_id=%s event_id=%s error=%s",
event.correlation_id,
event.event_id,
dispatch_report.matrix_error,
)
if dispatch_report.matrix_image_attempted:
if dispatch_report.matrix_image_sent:
logger.info(
"Matrix graph image sent: correlation_id=%s event_id=%s matrix_event_id=%s content_uri=%s",
event.correlation_id,
event.event_id,
dispatch_report.matrix_image_event_id,
dispatch_report.matrix_image_mxc_uri,
)
else:
logger.error(
"Matrix graph image failed: correlation_id=%s event_id=%s error=%s",
event.correlation_id,
event.event_id,
dispatch_report.matrix_image_error,
)
if dispatch_report.mail_attempted:
if dispatch_report.mail_sent:
logger.info(
"Mail notification sent: correlation_id=%s event_id=%s recipient=%s",
event.correlation_id,
event.event_id,
settings.mail_to,
)
else:
logger.error(
"Mail notification failed: correlation_id=%s event_id=%s error=%s",
event.correlation_id,
event.event_id,
dispatch_report.mail_error,
)
return decision
def _build_llm_correlation_assessment(
self,
llm_result: LLMCorrelationResult,
decision: NotificationDecision,
event,
) -> CorrelationAssessment | None:
if not llm_result.ok:
return None
min_confidence_rank = _confidence_rank(settings.llm_correlation_min_confidence)
actual_confidence_rank = _confidence_rank(llm_result.confidence)
role = llm_result.role
confidence = llm_result.confidence or "low"
if role in {"root", "child"} and actual_confidence_rank < min_confidence_rank:
return None
if role == "child" and not (llm_result.parent_event_id or llm_result.parent_correlation_id):
return None
suppress_child = False
if (
role == "child"
and llm_result.suppress_child
and actual_confidence_rank >= _confidence_rank("high")
and not _is_high_or_disaster(decision.severity)
):
suppress_child = True
if role == "root":
group_id = event.event_id or event.correlation_id
return CorrelationAssessment(
applied=True,
role="root",
kind=llm_result.kind,
group_id=group_id,
reason=llm_result.reason,
parent_event_id=None,
parent_correlation_id=None,
root_cause_candidate=True,
correlated_event_count=0,
suppress_child=False,
source="llm",
confidence=confidence,
)
if role == "child":
group_id = llm_result.parent_event_id or llm_result.parent_correlation_id
return CorrelationAssessment(
applied=True,
role="child",
kind=llm_result.kind,
group_id=group_id,
reason=llm_result.reason,
parent_event_id=llm_result.parent_event_id,
parent_correlation_id=llm_result.parent_correlation_id,
root_cause_candidate=False,
correlated_event_count=0,
suppress_child=suppress_child,
source="llm",
confidence=confidence,
)
return None