Amy Simonson
Marketing Manager of Swedish edge computing company Avassa
Stockholm, Sweden
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Amy is an experienced marketing professional who thrives right in the intersection between deep tech and marketing. She is currently the marketing manager of Swedish Edge Platform provider Avassa, who are set out to make the distributed on-site edge delightfully easy to manage.
Area of Expertise
Topics
Where MLOps Ends, and Edge Container Lifecycle Management Begins
MLOps helps teams design and develop their Machine Learning (ML) models and applications systematically, enabling them to future-proof their AI initiatives. AI models are typically developed and trained in a centralized development environment. However, once ready for production, they often run closer to telemetry data sources, at the edge.
A gap frequently arises at this point.
Most leading MLOps tools cover all essential functions for developing and packaging trained models and applications, but they rarely support the complete lifecycle management of the distributed container applications themselves.
In this session, we delve into the intersection of MLOps and edge container management and operations. We'll discuss where one ends, and the other begins. Moreover, we'll explore how you as an ML developer can efficiently and securely align the lifecycles of the central and distributed components of your edge AI model and application containers.
We'll outline the path toward container application and model management and operations for the future.
A developer self-service experience for edge and IoT come true
Enough manual actions. Enough slow handovers. And enough K8mplexity.
For many innovative enterprises today, the journey to the centralized cloud has shaped the way of working when it comes to container orchestration and observability. Now, developers and IT teams are increasingly also managing containers at the distributed on-site edge and in IoT environments, which risk becoming a mind-boggling task due to the resource-constrained, distant nature of IoT and edge.
In this session, we address the challenges related to deploying, monitoring, observing, and securing container applications at the edge. We also present hands-on examples of what a self-service developer experience can look like for the container applications at the distributed edge and IoT infrastructure. It's automated, it's application-centric and it's astonishingly easy.
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