Year: 2025
Type: article
Abstract: This article presents a comprehensive framework for implementing observability in AI-driven pipelines, addressing the challenges of monitoring and maintaining complex distributed systems.The framework encompasses multiple layers including data collection, processing and analysis, and visualization, providing organizations with Mouna Reddy Mekala https://iaeme.com/Home/journal/IJRCAIT687 [email protected] insights into their AI operations.Through detailed case studies of e-commerce and manufacturing implementations, the article demonstrates how advanced observability techniques can significantly improve system reliability, reduce incident resolution times, and enhance overall operational efficiency.The framework incorporates best practices for data collection strategies, monitoring approaches, and operational excellence, enabling organizations to achieve robust observability across their AI infrastructure while maintaining optimal performance and reliability.
Author: Mouna Reddy Mekala
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4406937375