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DTSTAMP:20250513T202500Z
DESCRIPTION:The complexity of modern cloud platforms and the highly distrib
 uted nature of today’s software systems present significant challenges for
  debugging\, anomaly detection\, and root cause analysis. Traditional meth
 ods for software debugging\, monitoring\, and performance analysis are oft
 en limited\, as they focus primarily on known issues. The rise of large la
 nguage models (LLMs) has further transformed software development by autom
 ating tasks\, often reducing developers’ direct engagement with code and d
 ecreasing system awareness. This lack of awareness introduces new challeng
 es\, particularly in maintaining security\, performance\, and reliability.
  This talk will explore the concept of software observability and discuss 
 mechanisms that support debugging\, fault diagnosis\, anomaly detection\, 
 and AIOps. It will highlight examples from ongoing research in the telecom
  domain and examine how observability can address the gaps in system under
 standing created by LLM-assisted coding. The discussion will conclude with
  an analysis of broader challenges and research opportunities in advancing
  observability for the modern era.\n\nRegister\n\nSpeaker\n\nNaser Ezzati-
 Jivan\, PhD\, is an Associate Professor in the Department of Computer Scie
 nce at Brock University\, Ontario\, Canada. His research focuses on Softwa
 re Performance Engineering and Software Analysis\, supported by over 16 ye
 ars of experience as a professor\, software engineer\, and team leader. He
  has collaborated on several research projects with major industrial partn
 ers\, including Google Montreal\, Ericsson\, and Ciena. An active member o
 f the academic community\, Nazer has served as a reviewer and program comm
 ittee member for major journals and conferences. He completed his PhD at P
 olytechnique Montréal\, where his thesis was recognized with a special men
 tion award.\n\n\n
DTSTART:20250331T150000Z
DTEND:20250331T160000Z
LOCATION:Online<br><b>Language of Delivery</b>: English
SUMMARY:Software Observability in the Era of Large Language Models – Challe
 nges and Opportunities
URL:/continuingstudies/channels/event/software-observa
 bility-era-large-language-models-challenges-and-opportunities-363875
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