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DTSTART:20260308T030000
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DTSTAMP:20260615T001242Z
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DTSTART;TZID=America/New_York:20260817T190000
DTEND;TZID=America/New_York:20260817T200000
DESCRIPTION:Modern distributed systems rely on real-time streaming pipeline
 s to support business-critical applications across telecommunications\, e-
 commerce\, finance\, healthcare\, and cloud platforms. However\, maintaini
 ng reliable event delivery in these environments remains challenging due t
 o message loss\, duplicate events\, latency spikes\, consumer lag\, schema
  inconsistencies\, and node-level failures.\n\nThis talk presents an obser
 vability-driven streaming architecture that integrates logs\, metrics\, di
 stributed tracing\, telemetry correlation\, alerting\, and automated remed
 iation into the streaming lifecycle. The session explains how observabilit
 y can evolve beyond traditional monitoring into a reliability control laye
 r that improves fault detection\, root-cause analysis\, workload balancing
 \, and recovery speed.\n\nThe discussion will cover practical design patte
 rns using event-driven platforms\, distributed tracing\, dashboards\, and 
 self-healing mechanisms to improve message consistency\, reduce downtime\,
  and strengthen real-time data reliability in large-scale distributed syst
 ems.\n\nCo-sponsored by: IEEE Future Networks AI/ML Working Group\n\nSpeak
 er(s): Ravi\, \n\nVirtual: https://events.vtools.ieee.org/m/561661
LOCATION:Virtual: https://events.vtools.ieee.org/m/561661
ORGANIZER:anushanerella@ieee.org
SEQUENCE:55
SUMMARY:WIE Speaker Series: Enhancing Real-Time Data Reliability through Ob
 servability-Driven Streaming Architecture in Distributed Systems
URL;VALUE=URI:https://events.vtools.ieee.org/m/561661
X-ALT-DESC:Description: <br /><p>Modern distributed systems rely on real-ti
 me streaming pipelines to support business-critical applications across te
 lecommunications\, e-commerce\, finance\, healthcare\, and cloud platforms
 . However\, maintaining reliable event delivery in these environments rema
 ins challenging due to message loss\, duplicate events\, latency spikes\, 
 consumer lag\, schema inconsistencies\, and node-level failures.</p>\n<p>T
 his talk presents an observability-driven streaming architecture that inte
 grates logs\, metrics\, distributed tracing\, telemetry correlation\, aler
 ting\, and automated remediation into the streaming lifecycle. The session
  explains how observability can evolve beyond traditional monitoring into 
 a reliability control layer that improves fault detection\, root-cause ana
 lysis\, workload balancing\, and recovery speed.</p>\n<p>The discussion wi
 ll cover practical design patterns using event-driven platforms\, distribu
 ted tracing\, dashboards\, and self-healing mechanisms to improve message 
 consistency\, reduce downtime\, and strengthen real-time data reliability 
 in large-scale distributed systems.</p>
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