Spaces:
Runtime error
Runtime error
| """ | |
| Core service layer for incident and alert management | |
| """ | |
| import logging | |
| from typing import List, Dict, Any, Optional | |
| from uuid import UUID | |
| from datetime import datetime, timedelta | |
| from sqlalchemy.orm import Session | |
| from sqlalchemy import desc | |
| logger = logging.getLogger(__name__) | |
| class AlertService: | |
| """Service for alert operations""" | |
| def __init__(self, db: Session): | |
| self.db = db | |
| async def create_alert(self, alert_data: Dict[str, Any]) -> Dict[str, Any]: | |
| """Create a new alert""" | |
| try: | |
| logger.info(f"Creating alert from source: {alert_data.get('source')}") | |
| # Implementation would interact with database models | |
| # This is a placeholder for the actual implementation | |
| return { | |
| "status": "created", | |
| "alert_id": "placeholder" | |
| } | |
| except Exception as e: | |
| logger.error(f"Error creating alert: {e}") | |
| raise | |
| async def get_alert(self, alert_id: UUID) -> Optional[Dict[str, Any]]: | |
| """Retrieve an alert by ID""" | |
| try: | |
| logger.info(f"Retrieving alert: {alert_id}") | |
| return None # Placeholder | |
| except Exception as e: | |
| logger.error(f"Error retrieving alert: {e}") | |
| raise | |
| async def list_alerts( | |
| self, | |
| severity: Optional[str] = None, | |
| status: Optional[str] = None, | |
| source: Optional[str] = None, | |
| limit: int = 100, | |
| offset: int = 0 | |
| ) -> Dict[str, Any]: | |
| """List alerts with filters""" | |
| try: | |
| logger.info(f"Listing alerts with filters") | |
| return { | |
| "items": [], | |
| "total": 0, | |
| "limit": limit, | |
| "offset": offset | |
| } | |
| except Exception as e: | |
| logger.error(f"Error listing alerts: {e}") | |
| raise | |
| async def update_alert(self, alert_id: UUID, update_data: Dict[str, Any]) -> Dict[str, Any]: | |
| """Update an alert""" | |
| try: | |
| logger.info(f"Updating alert: {alert_id}") | |
| return {"status": "updated"} | |
| except Exception as e: | |
| logger.error(f"Error updating alert: {e}") | |
| raise | |
| async def deduplicate_alert(self, fingerprint: str) -> Optional[UUID]: | |
| """Check if alert with same fingerprint already exists""" | |
| try: | |
| logger.debug(f"Checking for duplicate alert with fingerprint: {fingerprint}") | |
| return None # Placeholder | |
| except Exception as e: | |
| logger.error(f"Error deduplicating alert: {e}") | |
| raise | |
| class IncidentService: | |
| """Service for incident operations""" | |
| def __init__(self, db: Session): | |
| self.db = db | |
| async def create_incident(self, incident_data: Dict[str, Any]) -> Dict[str, Any]: | |
| """Create a new incident""" | |
| try: | |
| logger.info(f"Creating incident: {incident_data.get('title')}") | |
| return { | |
| "status": "created", | |
| "incident_id": "placeholder" | |
| } | |
| except Exception as e: | |
| logger.error(f"Error creating incident: {e}") | |
| raise | |
| async def get_incident(self, incident_id: UUID) -> Optional[Dict[str, Any]]: | |
| """Retrieve an incident by ID""" | |
| try: | |
| logger.info(f"Retrieving incident: {incident_id}") | |
| return None # Placeholder | |
| except Exception as e: | |
| logger.error(f"Error retrieving incident: {e}") | |
| raise | |
| async def list_incidents( | |
| self, | |
| severity: Optional[str] = None, | |
| status: Optional[str] = None, | |
| limit: int = 100, | |
| offset: int = 0 | |
| ) -> Dict[str, Any]: | |
| """List incidents with filters""" | |
| try: | |
| logger.info(f"Listing incidents") | |
| return { | |
| "items": [], | |
| "total": 0, | |
| "limit": limit, | |
| "offset": offset | |
| } | |
| except Exception as e: | |
| logger.error(f"Error listing incidents: {e}") | |
| raise | |
| async def update_incident(self, incident_id: UUID, update_data: Dict[str, Any]) -> Dict[str, Any]: | |
| """Update an incident""" | |
| try: | |
| logger.info(f"Updating incident: {incident_id}") | |
| return {"status": "updated"} | |
| except Exception as e: | |
| logger.error(f"Error updating incident: {e}") | |
| raise | |
| async def acknowledge_incident(self, incident_id: UUID, user: str) -> Dict[str, Any]: | |
| """Acknowledge an incident""" | |
| try: | |
| logger.info(f"Acknowledging incident {incident_id} by {user}") | |
| return {"status": "acknowledged"} | |
| except Exception as e: | |
| logger.error(f"Error acknowledging incident: {e}") | |
| raise | |
| async def resolve_incident(self, incident_id: UUID, user: str, resolution: str) -> Dict[str, Any]: | |
| """Resolve an incident""" | |
| try: | |
| logger.info(f"Resolving incident {incident_id} by {user}") | |
| return {"status": "resolved"} | |
| except Exception as e: | |
| logger.error(f"Error resolving incident: {e}") | |
| raise | |
| async def get_incident_timeline(self, incident_id: UUID) -> List[Dict[str, Any]]: | |
| """Get timeline of incident events""" | |
| try: | |
| logger.info(f"Retrieving timeline for incident: {incident_id}") | |
| return [] # Placeholder | |
| except Exception as e: | |
| logger.error(f"Error retrieving timeline: {e}") | |
| raise | |
| async def add_incident_event( | |
| self, | |
| incident_id: UUID, | |
| event_type: str, | |
| message: str, | |
| actor: str, | |
| details: Optional[Dict[str, Any]] = None | |
| ) -> Dict[str, Any]: | |
| """Add an event to incident timeline""" | |
| try: | |
| logger.info(f"Adding event to incident {incident_id}: {event_type}") | |
| return {"status": "added"} | |
| except Exception as e: | |
| logger.error(f"Error adding incident event: {e}") | |
| raise | |
| async def correlate_alerts(self, alert_ids: List[UUID]) -> UUID: | |
| """Correlate multiple alerts into an incident""" | |
| try: | |
| logger.info(f"Correlating {len(alert_ids)} alerts") | |
| return UUID("00000000-0000-0000-0000-000000000000") # Placeholder | |
| except Exception as e: | |
| logger.error(f"Error correlating alerts: {e}") | |
| raise | |
| class AnalysisService: | |
| """Service for LLM-based analysis""" | |
| def __init__(self, db: Session, llm_client): | |
| self.db = db | |
| self.llm_client = llm_client | |
| async def analyze_incident_classification(self, incident_id: UUID) -> Dict[str, Any]: | |
| """Analyze incident and classify it""" | |
| try: | |
| logger.info(f"Classifying incident: {incident_id}") | |
| return {"status": "classified"} | |
| except Exception as e: | |
| logger.error(f"Error classifying incident: {e}") | |
| raise | |
| async def analyze_root_cause(self, incident_id: UUID) -> Dict[str, Any]: | |
| """Perform root cause analysis on incident""" | |
| try: | |
| logger.info(f"Analyzing root cause for incident: {incident_id}") | |
| return {"status": "analyzed"} | |
| except Exception as e: | |
| logger.error(f"Error analyzing root cause: {e}") | |
| raise | |
| async def generate_recommendations(self, incident_id: UUID) -> List[Dict[str, Any]]: | |
| """Generate recommendations for incident resolution""" | |
| try: | |
| logger.info(f"Generating recommendations for incident: {incident_id}") | |
| return [] # Placeholder | |
| except Exception as e: | |
| logger.error(f"Error generating recommendations: {e}") | |
| raise | |
| async def normalize_alert(self, raw_alert: Dict[str, Any], source: str) -> Dict[str, Any]: | |
| """Normalize an alert using LLM""" | |
| try: | |
| logger.info(f"Normalizing alert from source: {source}") | |
| return {} # Placeholder | |
| except Exception as e: | |
| logger.error(f"Error normalizing alert: {e}") | |
| raise | |
| class CorrelationService: | |
| """Service for alert correlation""" | |
| def __init__(self, db: Session, llm_client): | |
| self.db = db | |
| self.llm_client = llm_client | |
| async def correlate_alerts(self, alerts: List[Dict[str, Any]]) -> Dict[str, Any]: | |
| """Correlate multiple alerts into incidents""" | |
| try: | |
| logger.info(f"Correlating {len(alerts)} alerts") | |
| return {"correlations": []} # Placeholder | |
| except Exception as e: | |
| logger.error(f"Error correlating alerts: {e}") | |
| raise | |
| async def check_correlation_window(self, time_window_minutes: int = 5) -> List[Dict[str, Any]]: | |
| """Check for alerts within correlation window to process""" | |
| try: | |
| logger.info(f"Checking for alerts within {time_window_minutes} minute window") | |
| return [] # Placeholder | |
| except Exception as e: | |
| logger.error(f"Error checking correlation window: {e}") | |
| raise | |
| class MetricsService: | |
| """Service for system metrics and statistics""" | |
| def __init__(self, db: Session): | |
| self.db = db | |
| async def get_system_stats(self) -> Dict[str, Any]: | |
| """Get system statistics""" | |
| try: | |
| logger.info("Retrieving system statistics") | |
| return { | |
| "total_incidents": 0, | |
| "open_incidents": 0, | |
| "total_alerts": 0, | |
| "avg_mttr_minutes": None | |
| } | |
| except Exception as e: | |
| logger.error(f"Error retrieving system stats: {e}") | |
| raise | |
| async def get_incident_stats(self) -> Dict[str, Any]: | |
| """Get detailed incident statistics""" | |
| try: | |
| logger.info("Retrieving incident statistics") | |
| return { | |
| "by_severity": {}, | |
| "by_status": {}, | |
| "by_category": {} | |
| } | |
| except Exception as e: | |
| logger.error(f"Error retrieving incident stats: {e}") | |
| raise | |