Kubernetes on Edge Day Europe 2022

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Modern applications deployed at the edge are revolutionizing industries, turning “Kubernetes at the edge” one of the most compelling use cases for the ecosystem. While edge can be challenging to deploy and manage, the significant progress across many community projects is providing the building blocks of a brand new redefined edge that will unlock its true potential. This short keynote will cover the “now” for edge now, what’s required and the future ahead.

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Edge computing is the next evolution of cloud. Over the last decade, we’ve learned a lot about running applications on elastic clouds. Infrastructure Operators and Developers can apply much of what we’ve learned to Edge deployments, so that you can be confident that the same app is up to date and secure at many locations simultaneously. The two concepts we’ll cover in this quick talk are disposable infrastructure and using abstractions to enable t-shirt sizing at the Edge.

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Anyone who’s ever deployed on the edge has had this hope before: “It ran perfectly on my cloud environment, it’ll surely work when I deploy it across these other different environments”. Unfortunately, much of the time, this hope falls flat. This is frustratingly true for those deploying machine learning models on the edge. These models are often painstakingly trained and fine-tuned over months and days to achieve those extra few percentage points of accuracy… Only to see performance drop by over 10% once deployed to an edge device. This session will cover common problems encountered when deploying machine learning models on the edge, and how MLExray, an open-source observability framework created at Stanford, can be used to help debug these issues when they inevitably occur. *MLExray has been accepted into MLSys 2022: https://arxiv.org/pdf/2111.04779.pdf

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Edge computing can require connecting hundreds of clusters across disparate locations and infrastructures. Without a networking solution to manage this scale and complexity, you will just have a bunch of computers talking to themselves rather than each other and your customers. Cilium is the next generation, eBPF powered open-source Cloud Native Networking solution, providing security, observability, scalability, and superior performance. Cilium has joined the CNCF as incubating project. In this session, you’ll learn how you can leverage Cilium Cluster Mesh for providing connectivity for load-balancing, observability, and security between nodes across multiple clusters, enabling simple, high-performance cross-cluster connectivity at the edge. We’ll explore how Cluster Mesh allows endpoints in connected clusters to communicate while providing full security policy enforcement. The audience will walk away with an appreciation for how eBPF can help solve their networking challenges at the edge.

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The network edge presents new challenges in optimizing application deployments, as the deeper an application is pushed into the Internet, the greater the associated costs to run those workloads. This talk will cover a set of optimization considerations and strategies that allow workloads to be as close to users as possible, bounded by a business value construct. At the same time, we will discuss the importance of maintaining simplicity in the usability of the system, so that developers can specify how deeply they want their application to run without overallocation of resources. Using CNCF core technologies, including Kubernetes and Prometheus as a base, this talk establishes a framework for evaluating projects within the CNCF landscape and their suitability for edge use cases. We will examine Kubernetes Federation techniques, Multi-cluster orchestrator systems, and Traffic Direction and Service Discovery strategies against a selection criteria to assist architects in making “good-fit” decisions.

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As edge devices consume the world, the ability to deploy AI models on these devices becomes increasingly vital. Challenges surrounding the management of numerous models across a multitude of edge hosts can be tricky. Not only that, the limited compute power that edge hosts provide makes it necessary to eliminate as much overhead as possible. These are common pain points holding users back from large scale adoption. However, with the combination of ModelMesh with technologies like K3s and MicroShift, the practicality of employing such a system has increased dramatically. As the multi-model serving backend of KServe, ModelMesh offers a small-footprint control-plane for managing model deployments on Kubernetes. Using multi-model runtimes with intelligent model loading/unloading, ModelMesh is able to make the most out of a limited set of resources while still providing the capability to serve many models for inference. Come to this talk to get the edge on edge model serving!

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Edge computing and K8s have the potential to transform every industry, by bringing apps, data and outcomes closer to end-users, but it can be a significant paradigm shift for most enterprises when it comes to operationalization. For the healthcare industry, requirements such as security, availability and performance across thousands of locations are demanding for a new type of architecture and efficient tooling. Join this talk, if you're interested in learning about the requirements and gotchas of running and delivering K8s applications across thousands of edge locations, with 0 tolerance for mistakes. GE Healthcare's Senior Staff Software Architect, Ben Beeman and Spectro Cloud’s CTO, Saad Malik will discuss the lessons and how we need a next generation of edge architecture for the cloud native world. Beyond the theory, we will demo live the open source building blocks of managing the complete lifecycle at the edge, such as Cluster API, Libvirt, Docker and others.

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Developers can leverage container tools such as Kubernetes, Docker and CRI-O to deploy, manage, and run lightweight WebAssembly applications. In this talk, there will be a demonstration of how Kubernetes ecosystem tools work with WasmEdge WebAssembly applications. Compared with Linux containers, WebAssembly could be 100x faster at startup, have a much smaller memory and disk footprint, and have a better-defined safety sandbox. However, the trade-off is that WebAssembly requires its own language SDKs, and compiler toolchains, making it a more constrained developer environment than Linux containers. WebAssembly is increasingly used in Edge Computing scenarios where it is difficult to deploy Linux containers or when the application performance is vital. One of the great advantages of Linux application containers is the rich ecosystem of tools. The good news is that you can use the exact same tools to manage WebAssembly applications, enabling Linux containers and WebAssembly apps to run side-by-side in the same system.

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