Intelligent Logging & AI Fault Analysis

This page provides an overview of the AiEventing library and how it integrates with .NET applications for advanced event logging and AI-powered diagnostics.

About AiEventing:
AiEventing leverages Microsoft’s extensible logging infrastructure and advanced AI to deliver actionable insights and rapid diagnostics for your .NET solutions.

The Problem:
Modern applications generate a large volume of logs and exception events, making it difficult for developers to quickly identify, analyze, and resolve faults. AiEventing addresses this by capturing, structuring, and analyzing exception events in real time, leveraging AI to provide deeper understanding and recommendations for remediation.

How AiEventing Works

1. Seamless Microsoft Integration:
   • Logging is initialized using Dependency Injection and ILogger patterns.
   • The EventSourcePublisher is registered as a singleton, ensuring efficient, thread-safe event publishing.
2. Structured, Contextual Logging:
   • ApplicationLogger captures log level, category, scopes, correlation IDs, and exception details for every event.
   • Scopes are managed using Microsoft’s IExternalScopeProvider for logical grouping and distributed tracing.
3. AI-Powered Fault Analysis with ChatGPT:
   • When an exception is logged, the logger automatically invokes a ChatGPT-powered analysis service.
   • The exception’s stack trace and context are securely sent to the AI, which analyzes the fault and suggests likely causes and fixes.
4. Smart Caching for Efficiency:
   • Each unique exception is hashed and results are cached in a thread-safe dictionary.
   • If the same exception occurs again, the cached analysis is instantly retrieved and published—no redundant AI calls.
5. Enterprise-Ready Event Publishing:
   • All log events, including AI-generated analyses, are published via EventSourcePublisher for integration with Windows Event Tracing, Azure Monitor, and other Microsoft observability tools.