Observability in Large Language Models: A Framework for Real-Time Applications

Author(s)	Syed Arham Akheel
Country	United States
Abstract	Large Language Models (LLMs) are revolutionizing the way artificial intelligence interacts with the world. However, as they become more integrated into real-time systems, ensur- ing their performance, safety, and robustness presents critical challenges. This paper explores the importance of observability in LLMs, outlining metrics, frameworks, and techniques for monitoring and optimization. Drawing on diverse observability studies, we discuss the practical implementations, case studies, and the future of this emerging field.
Keywords	Large Language Models, Observ- ability, Real-Time Systems, Performance Monitoring, Opti- mization, Hallucinations, Reinforcement Learning from Hu- man Feedback, Metrics, Frameworks
Field	Engineering
Published In	Volume 5, Issue 12, December 2024
Published On	2024-12-08
Cite This	Observability in Large Language Models: A Framework for Real-Time Applications - Syed Arham Akheel - IJLRP Volume 5, Issue 12, December 2024. DOI 10.5281/zenodo.14995714
DOI	https://doi.org/10.5281/zenodo.14995714
Short DOI	https://doi.org/g87h3b

About IJLRP Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijlrp.com

International Journal of Leading Research Publication