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Track: Living on the Edge: The World of Edge Compute From Device to Infrastructure Edge

Location: Bayview AB

Day of week: Wednesday

How do you define edge computing? ...and, more importantly, what does it mean for your architecture?

Ask three people what edge computing is and you’ll likely get three different answers. The last mile is a phrase used by telecommunication networks to indicate the last point where a telco delivers services to a customer. On one side of that last mile is the Device Edge (think things like IoT/IIoT, phones, & devices). On the other, is the Infrastructure Edge (think cellular towers, regional data centers, and CDN running application logic from Node, to K8s, to serverless functions).

This track explores architectures leveraging the device and infrastructure edges in modern application architecture. This is a track that explores pushing code closer to the user than ever before to handle new and innovative use case. Look for talks exploring federated learning through training localized machine learning models on device, k8s clusters being deployed to hundreds if not thousands of on-prim locations, Web Assembly (WASM/WASI) implementations in caching tiers, and application architectures for application gateways, content delivery, streaming, and more.

While the modern edge may not be the easiest thing to define, the edge is a place to deliver value to your customers and is altering what we think is possible for application architecture.

Track Host: Wes Reisz

QCon San Francisco Lead Chair, Host of the InfoQ Podcast, & Former VP of Technology @SectionIO

Wesley Reisz is the former VP of Technology at Section (an Edge Compute Platform focused on rethinking how the edge is used in DevOps-focused application development). Wes also chairs the LFEdge Landscape Working Group and the San Francisco edition of QCon.

Before joining Section, Wes served as the product owner for all of the English speaking QCon conferences worldwide, was a principal architect with HP Enterprise Systems, and, for over 13 years, taught as an adjunct professor for the University of Louisville (Go Cards!).

At HPE, Wes’ primary roles supported the US Army’s Human Resources (HRC), Recruiting, and Cadet Support Commands based at Fort Knox, Kentucky. Wes was the Principal Architect for US Army Cadet Command and was known for championing, building, and deploying enterprise portal and identity solutions used by Army Recruiting.

In addition to Wes’ current roles, he co-hosts a weekly podcast called The InfoQ Podcast. The InfoQ Podcast serves senior early adopter/early majority developers and architects with interviews from some of software’s most important thought leaders. The podcast has been downloaded over 1.5 million times and has a weekly listener base of around 14K.

10:35am - 11:25am

Self-Driving Cars as Edge Computing Devices

Every Uber self-driving car runs advanced software, often for hours on end, which requires a powerful compute stack. In this talk, we’ll explain the architecture of Uber ATG’s self-driving cars and have a look at how the software is developed, tested, and deployed.

Matt Ranney, Sr. Staff Engineer @UberATG

11:50am - 12:40pm

Linux Foundation's Project EVE: A Cloud-Native Edge Computing Platform

Connecting IoT devices to the Internet is nothing new. Deploying and running real-time cloud-native applications at hyperscale on the mesh fabric of these devices is. Edge Computing evolves Cloud Computing by keeping what's great about the Cloud model (developer friendly APIs and Software-defined everything) yet applying it to the harsh physical and security environments of IoT and IIoT deployments. While IoT is making the world cyber-physical, Edge Computing promises to make it manageable and truly software-defined, thus making familiar cloud-native applications live life on the edge forever unshackled from the confines of a datacenter.  

At the same time, Edge is not yet another datacenter. Its unique requirements make it virtually impossible to take existing software projects that are powering cloud-native infrastructures and apply them to the Edge as-is.  

In this talk we will cover design and implementation of a novel Edge Computing platform created at ZEDEDA Inc. and later used as a founding project for the Linux Foundation's LF Edge initiative. We will focus on this new, special purpose, open source operating environment that aims to run securely on billions of ARM and x86 devices. The name of the project is EVE (Edge Virtualization Engine) and its ambition in life is to become to Edge Computing what Android has become to Mobile computing. We will walk you through the unique challenges that EVE has to tackle and will provide hands-on advice on how it enables the same DevOps-driven, high velocity developer culture that is now ubiquitous in the cloud environments.

Roman Shaposhnik, Co-founder, VP Product and Strategy @ZededaEdge & Member Board Of Directors for LF Edge @linuxfoundation

1:40pm - 2:30pm

Machine Learning on Mobile and Edge Devices With TensorFlow Lite

Machine learning enables some incredible applications, from human-centric user interfaces to generative art. But the traditional machine learning architecture is server-based, with data being sent from users' devices to the cloud, and users are rightly concerned about privacy, safety, and control over their data.  

In this talk, we'll learn how developers can use TensorFlow Lite to build amazing machine learning applications that run entirely on-device. We'll see how running models on-device leads to lower latency, improved privacy, and robustness against connectivity issues. And we'll get familiar with the workflows, tools, and platforms that make on-device inference possible.  

You'll leave this session ready to deploy machine learning models to a wide range of devices, from mobile phones to ultra-low power microcontrollers. You'll learn where to find pre-trained models that can solve a wide range of problems, and how to optimize your own models so they work well on devices.

Daniel Situnayake, Developer Advocate for TensorFlow Lite @Google and Co-Author of TinyML

2:55pm - 3:45pm

Pick Your Region: Earth; Cloudflare Workers

In September of 2008, Google’s Chromium Project released V8, a JavaScript engine, as part of a browser optimization wave that heralded the era of JavaScript browser applications that we both love, and love to hate. Less than a year later, in 2009, Ryan Dahl announced a way to run the V8 browser environment outside of the browser- Node.js, a platform that held the promise of unifying web application development, where both client and server-side development could happen in the same language - JavaScript.

A decade later, V8, JavaScript, and its new buddy WebAssembly, have found themselves in territory neither server nor client- the “Edge”. More specifically, Cloudflare's network of 194 data centers all over the globe.

In this talk, we’ll introduce what the “Edge” is and why we are excited for it to revolutionize computation on the web. We’ll dig into why the V8 JavaScript engine is so well suited to tasks previously limited to Virtual Machines, Containers, or Operating Systems. We'll explore why Workers, Cloudflare's Serverless Edge Compute platform, is unique, from both a programming model and architecture point of view, and why we think it heralds a new paradigm shift in JavaScript and web development. 

Ashley Williams, Core Rust Team @RustLang

4:10pm - 5:00pm

Evolution of Edge @Netflix

Being the gatekeepers for the company is a very exciting and enlightening experience - we are trusted to build and operate bridges between the Internet and the data centers. With such a centralized location in the ecosystem comes great power and great responsibility - we have a unique insight into the company’s traffic and access patterns and often can adjust them in order to provide better user experience, reduce cost or improve on some other parameter.   

In this talk we’ll review Netflix’s edge gateway ecosystem - multiple traffic gateways performing different functions deployed around the world. We’ll touch upon the motivation behind such topology and highlight challenges it introduces. We’ll see where and how the value is added, what is the operational footprint of it and what happens when things go wrong. 
 

Vasily Vlasov, Engineering Leader @Netflix

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