AIOps - AI for IT Operations

AIOps - AI for IT Operations

This skill provides comprehensive patterns for implementing AIOps strategies in 2025, including intelligent monitoring, automated incident response, predictive analytics, and observability best practices. The patterns are designed to be framework-agnostic and applicable across different infrastructure platforms.

When to Use This Skill

Use this skill when you need to:

• Implement AIOps strategies for modern infrastructure
• Build intelligent monitoring and alerting systems
• Create automated incident response workflows
• Deploy predictive maintenance solutions
• Implement self-healing capabilities
• Build observability platforms with AI/ML
• Optimize multi-cloud operations
• Create chaos engineering practices
• Implement generative AI for operations
• Build digital twins for infrastructure

1. AIOps Architecture Patterns

Core AIOps Platform Architecture

# aiops/core/architecture.py
from abc import ABC, abstractmethod
from typing import Dict, List, Optional, Any, Union
from dataclasses import dataclass, field
from datetime import datetime, timedelta
from enum import Enum
import asyncio
import json
import logging

logger = logging.getLogger(__name__)

class AlertSeverity(str, Enum):
    """Alert severity levels"""
    CRITICAL = "critical"
    HIGH = "high"
    MEDIUM = "medium"