When it comes to deploying applications at the IoT edge, containers are all the rage and Kubernetes is making its way out of the data center but we also can’t overlook traditional virtual machines for accommodating existing applications. The IoT edge is inherently heterogenous and ultimately we need to tame the complexity by enabling a variety of deployment models in a more standardized way.  More importantly, the ultimate business opportunity with digital transformation is through interconnected ecosystems and this simply isn’t possible without an open, trusted edge.

 As explained in the new LF Edge taxonomy, the edge is a continuum that necessitates different considerations and toolset based on inherent technical tradeoffs as deployments span from the cloud to the physical world.  In the taxonomy, the Smart Device Edge is a category characterized by compute assets deployed outside of physically-secured data centers but have enough system memory (~256MB) to support application abstraction through virtualization and/or containerization.  This includes both end-user centric devices such as smartphones and PCs, and headless compute resources spanning gateways, hubs, servers and routers

 Android has scaled a massive open ecosystem at the Smart Device Edge but the IoT component remains largely fragmented due to a diverse mix of hardware and tools.  Project EVE aims to be the “Android for the IoT edge” by creating an open abstraction engine that simplifies the development, orchestration and security of cloud-native applications on distributed edge hardware. Supporting containers, VMs and unikernels, EVE provides a flexible foundation for Industrial and Enterprise IoT edge deployments with choice of hardware, applications and clouds.

In this session we will highlight the key challenges of deploying applications at the edge, why LF Edge is important, and specifically why an open, standardized abstraction engine for edge hardware is critical for IoT edge scale.  The session will close with a hands-on demo based on the community’s Raspberry Pi dev kit.