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aiopslisted

Generic AIOps (AI for IT Operations) patterns and best practices for 2025. Provides comprehensive implementation strategies for intelligent monitoring, automation, incident response, and observability across any infrastructure. Framework-agnostic approach supporting multiple monitoring platforms, cloud providers, and automation tools.
aiskillstore/marketplace · ★ 329 · DevOps & Infrastructure · score 82
Install: claude install-skill aiskillstore/marketplace
# 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 ```python # 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" LOW = "low" INFO = "info" class IncidentStatus(str, Enum): """Incident status""" OPEN = "open" INVESTIGATING = "investigating"