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  <div class="vevent h-event"> <h1 class="summary p-name">Running Machine Learning workloads on Azure Kubernetes Service (AKS)</h1> <div class='date'><time class="dtstart dt-start" title="2018-10-29T17:30:00" datetime="2018-10-29T17:30:00">Monday, October 29, 2018 from 5:30</time>–<time class="dtend dt-end" title="2018-10-29T20:00:00" datetime="2018-10-29T20:00:00">8pm</time></div> <div class="location vcard p-location h-card"> <a class="url" href='http://calagator.org/venues/202395977'><span class='fn org p-name'>SoftSource Consulting</span></a> <div class="adr p-adr h-adr"> <div class="street-address p-street-address">6855 SW Baylor Street</div> <span class="locality p-locality">Portland</span> , <span class="region p-region">or</span> <span class="postal-code p-postal-code">97223</span> <div class="country-name p-country-name">us</div> (<a href='https://maps.google.com/maps?q=6855%20SW%20Baylor%20Street,%20Portland%20or%2097223%20us'>map</a>) </div> </div> <div class="description p-description"> <p>Please RSVP on our meetup page!</p> <p>Kubernetes simplifies building and operating coordinated distributed systems. Often, this means scaling stateless web applications across nodes and cloud providers.</p> <p>In this talk, we will discuss how to take advantage of the distributed primitives provided by Kubernetes to build a massively scalable online machine learning service on Azure.</p> <p>Topics covered: - Fundamental Kubernetes constructs - Scheduling of scarce compute resources (GPUs) - Autoscaling based on application metrics - Implications of Kubernetes on service availability</p> <p>Jordan Olshevski works on Azure Kubernetes Service at Microsoft, and has years of experience in the field of distributed systems and containers. Before coming to Microsoft, he helped build an enterprise-scale application runtime platform at Nike.</p> </div> <h3>Links</h3> <ul> <li><a class="url u-url" href="https://www.meetup.com/Portland-Azure-User-Group/events/255802959/">Website</a></li> </ul> </div>