BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Europe/Stockholm BEGIN:DAYLIGHT DTSTART:20270328T030000 TZOFFSETFROM:+0100 TZOFFSETTO:+0200 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:CEST END:DAYLIGHT BEGIN:STANDARD DTSTART:20261025T020000 TZOFFSETFROM:+0200 TZOFFSETTO:+0100 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:CET END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20261109T190358Z UID:8F97A135-D9E5-49A7-807D-4087C0B486A6 DTSTART;TZID=Europe/Stockholm:20261113T120000 DTEND;TZID=Europe/Stockholm:20261113T130000 DESCRIPTION:[Webinar] From Monitoring to Autonomous Operations: Observabili ty in the Age of AI\n\nAs software systems grow more distributed and AI-dr iven\, knowing what is happening inside them has shifted from a nice-to-ha ve to a necessity. This one-hour IEEE Region 8 Action for Industry (AfI) p anel discussion brings together experiences from leading industry professi onals and academic researchers to explore how observability has evolved an d where it is heading.\n\nWe start by unpacking what observability really means beyond traces\, logs\, and metrics\, and how it differs from traditi onal monitoring. Through live demos\, we follow Dynatrace’s journey from application performance monitoring to AIOps and autonomous operations\, a nd show how LLMs are making observability agentic. We then turn the lens a round to monitoring AI applications themselves\, which are “just” appl ications with less predictable outputs. The session closes with the regula tory landscape for AI and what organisations need to comply with.\n\nCo-sp onsored by: IEEE Region 8 Action for Industry (AfI)\n\nSpeaker(s): Adha Hu stro\, Nauman Bin Ali\, Magnus Bergman\, Anas Dakkak\n\nAgenda: \nIntroduc tion to Observability\, more than traces\, logs and metrics.\n\nDifference between “monitoring” and "observability"\n\nObservability has gone be yond “nice to have”\n\nIntroduction to Dynatrace\n\nstarted from APM - > Observability -> AiOps -> Autonomous Operations\n\nObservability is goin g Agentic\n\nLeverage LLM as part of the observability solution\n\nMonitor ing AI applications\n\nIt’s “just” and application\, with different output\n\nAI and compliance\n\nWhat regulation do we have to comply with?\ n\n(a) An open discussion about why observability matters\, including the need for observability in an all-connected world and a brief reflection on the difference between monitoring and observability. (10 min)\n\n(b) Chal lenges of observing AI applications. (10 min)\n\n(c) Demo of Dynatrace cap abilities (two items in green). (20-25 min).\n\n(d) Reflection on regulati ons and the evolving regulatory landscape (5 -10 min) (optional if we get time).\n\n(e) Questions and answers.\n\nVirtual: https://events.vtools.iee e.org/m/590261 LOCATION:Virtual: https://events.vtools.ieee.org/m/590261 ORGANIZER:dakkak@ieee.org SEQUENCE:20 SUMMARY:[Webinar] From Monitoring to Autonomous Operations: Observability i n the Age of AI URL;VALUE=URI:https://events.vtools.ieee.org/m/590261 X-ALT-DESC:Description: <br /><p><strong><span style="color: rgb(52\, 73\, 94)\;">[Webinar] From Monitoring to Autonomous Operations: Observability i n the Age of AI</span></strong></p>\n<p>As software systems grow more dist ributed and AI-driven\, knowing what is happening inside them has shifted from a nice-to-have to a necessity. This one-hour IEEE Region 8 Action for Industry (AfI) panel discussion brings together experiences from leading industry professionals and academic researchers to explore how observabili ty has evolved and where it is heading.</p>\n<p>We start by unpacking what observability really means beyond traces\, logs\, and metrics\, and how i t differs from traditional monitoring. Through live demos\, we follow Dyna trace&rsquo\;s journey from application performance monitoring to AIOps an d autonomous operations\, and show how LLMs are making observability agent ic. We then turn the lens around to monitoring AI applications themselves\ , which are &ldquo\;just&rdquo\; applications with less predictable output s. The session closes with the regulatory landscape for AI and what organi sations need to comply with.</p><br /><br />Agenda: <br /><p class="x_MsoN ormal"><strong>Introduction to Observability\, more than traces\, logs and metrics.&nbsp\;</strong></p>\n<p class="x_MsoNormal">Difference between & ldquo\;monitoring&rdquo\; and "observability"</p>\n<p class="x_MsoNormal"> Observability has gone beyond &ldquo\;nice to have&rdquo\;</p>\n<p class=" x_MsoNormal"><strong>Introduction to Dynatrace&nbsp\;</strong></p>\n<p cla ss="x_MsoNormal">started from APM -&gt\; Observability -&gt\; AiOps -&gt\; Autonomous Operations</p>\n<p class="x_MsoNormal"><strong>Observability i s going Agentic&nbsp\;</strong></p>\n<p class="x_MsoNormal">Leverage LLM a s part of the observability solution</p>\n<p class="x_MsoNormal"><strong>M onitoring AI applications&nbsp\;</strong></p>\n<p class="x_MsoNormal">It&r squo\;s &ldquo\;just&rdquo\; and application\, with different output</p>\n <p class="x_MsoNormal"><strong>AI and compliance&nbsp\;</strong></p>\n<p c lass="x_MsoNormal">What regulation do we have to comply with?</p>\n<p clas s="x_MsoNormal">&nbsp\;</p>\n<p class="x_MsoNormal">(a) An open discussion about&nbsp\;why observability matters\, including the need for observabil ity in an all-connected world&nbsp\;and a brief reflection on the differen ce between monitoring and observability. (10 min)</p>\n<p class="x_MsoNorm al">(b) Challenges of observing AI applications. (10 min)</p>\n<p class="x _MsoNormal">(c) Demo of Dynatrace capabilities (two items in green). (20-2 5 min).&nbsp\;</p>\n<p class="x_MsoNormal">(d) Reflection on regulations a nd the evolving regulatory landscape (5 -10 min) (optional if we get time) .&nbsp\;</p>\n<p class="x_MsoNormal">(e) Questions and answers.&nbsp\;</p> \n<p>&nbsp\;</p> END:VEVENT END:VCALENDAR