Open Source Akraino Edge Computing Project Leaps Into Action
The ubiquitous topic of edge computing has so far primarily focused on IoT and machine learning. A new Linux Foundation project called Akraino Edge Stack intends to standardize similar concepts for use on edge telecom and networking systems in addition to IoT gateways. The goal to build an “open source software stack that supports high-availability cloud services optimized for edge computing systems and applications,” says the project.
“The Akraino Edge Stack project is focused on anything related to the edge, including both telco and enterprise use cases,” said Akraino evangelist Kandan Kathirvel, Director of Cloud Strategy & Architecture at AT&T, in an interview with Linux.com.
The project announced it has “moved from formation into execution,” and revealed a slate of new members including Arm, Dell, Juniper, and Qualcomm. New member Ericsson is joining AT&T Labs to host the first developer conference on Aug. 23-24.
Akraino Edge Stack was announced in February based on code contributions from AT&T for carrier-scale edge computing. In March, Intel announced it was joining the project and open sourcing parts of its Wind River Titanium Cloud and Network Edge Virtualization SDK for the emerging Akraino stack. Intel was joined by a dozen, mostly China-based members including China Mobile, China Telecom, China Unicom, Docker, Huawei, Tencent, and ZTE.
The Akraino Edge Stack project has now announced broader based support with new members Arm, Dell EMC, Ericsson, inwinSTACK, Juniper Networks, Nokia, Qualcomm, Radisys, Red Hat, and Wind River. The project says it has begun to develop “blueprints that will consist of validated hardware and software configurations against defined use case and performance specifications.” The initial blueprints and seed code will be opened to the public at the end of the week following the Akraino Edge Stack Developer Summit at AT&T Labs in Middletown, New Jersey.
The project announced a lightweight governance framework with a Technical Steering Committee (TSC), composed of “active committers within the community.” There is “no prerequisite of financial contribution,” says the project.
Edge computing meets edge networking
Like most edge computing projects and products, such as AWS Greengrass, the Linux Foundation’s EdgeX Foundry, and Google’s upcoming Cloud IoT Edge, the technology aims to bring cloud technologies and analytics to smaller-scale computers that sit closer to the edge of the network. The goal is to reduce the latency of cloud/device interactions, while also reducing costly bandwidth delivery and improving reliability via a distributed network.
Akraino will offer blueprints for IoT, but it is more focused more on bringing edge services to telecom and networking systems such as cellular base stations, smaller networking servers, customer premises equipment, and virtualized central offices (VCOs). The project will supply standardized blueprints for implementing virtual network functions (VNFs) in these systems for applications ranging from threat detection to augmented reality to specialized services required to interconnect cars and drones. Virtualization avoids the cost and complexity of integrating specialized hardware with edge networking systems.
“One key difference from other communities is that we offer blueprints,” said AT&T’s Kathirvel. “Blueprints are declarative configurations of everything including the hardware, software, operational and security tools, security tools -- everything you need to run production in large scale.”
When asked for further clarification between Akraino’s stack and the EdgeX Foundry’s middleware for industrial IoT, Kathirvel said that EdgeX is more focused on the intricacies of IIoT gateway/sensor communications whereas Akraino has a broader focus and is more concerned with cloud connections.
“Akraino Edge Stack is not limited to IoT -- we’re bringing everything together in respect to the edge,” said Kathirvel. “It’s complementary with EdgeX Foundry in that you could take EdgeX code and create a blueprint and maintain that within the Akraino Edge Stack as an end to end stack. In addition, the community is working on additional use cases to support different classes of edge hardware.”
Meeting new demands for sub-20ms latency
Initially, Akraino Edge Stack use cases will be “focused on provider deployment,” said Kathirvel, referring to telecom applications. These will include emerging, 5G-enabled applications such as “AR/VR and connected cars” in which sub 20 millisecond or lower latency is required. In addition, edge computing can reduce the extent to which network bandwidth must be boosted to accommodate demanding multimedia-rich and cloud-intensive end-user applications.
Akraino Edge Stack borrows virtualization and container technologies from open source networking projects such as OpenStack. The goal is to create a common API stack for deploying applications using VNFs running within containers. A VNF is a software-based implementation of the networked virtual machines implemented via closely related NFV (network functions virtualization) initiatives.
In a May 23 presentation (YouTube video) at the OpenStack Summit Vancouver, Kathirvel and fellow Akraino contributor Melissa Evers-Hood of Intel, listed several other projects and technologies that the stack will accommodate with blueprints, including Ceph (distributed cloud storage), Kata Containers, Kubernetes, and the Intel/Wind River backed StarlingX for open cloud infrastructure. Aside from EdgeX and OpenStack, other Linux Foundation hosted projects on the list include DANOS (Disaggregated Network Operating System) and the LF’s new Acumos AI project for developing a federated platform to manage and share models for AI and machine learning.
Akraino aligns closely with OpenStack edge computing initiatives, as well as the Linux Foundation’s ONAP (Open Network Automation Platform). ONAP, which was founded in Feb. 2017 from the merger of the earlier ECOMP and OPEN-O projects, is developing a framework for real-time, policy-driven software automation of VNFs.
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