First Release of Akraino Edge Stack Defines Framework, Blueprints for IoT Edge Applications

June 6, 2019 Brandon Lewis

LF Edge has issued Release 1 of the Akraino Edge Stack, Akraino R1. The Akraino Edge Stack is an open-source cloud software stack optimized for edge systems. The first release includes a series of blueprints that define the stack for a diverse range of IoT edge use cases, but are still compatible with the single, common framework. R1 also provides a foundation for defining and standardizing APIs across different stacks.

Akraino blueprints are iterative configurations of the Akraino stack for different applications. Akraino currently includes more than 11 blueprint families and 19 specific prints. These blueprints are tested and validated on real hardware by users and community members.

10 blueprints that are already “ready and proven” include:

  • Kubernetes-Native Infrastructure (KNI) Provider Access Edge, which leverages Kubernetes concepts to manage edge computing stacks at scale
  • Edge Lightweight and IOT (ELIOT), which supports edge use cases for IoT gateways and universal customer premise equipment (uCPE) for software-defined WANs.
  • Radio Edge Cloud (REC), which supports a near real-time RAN Intelligent Controller used to control aspects of 5G radio networks
  • Integrated Edge Cloud (IEC) Type 1 (Small Edge) and Type 2 (Medium Edge), a platform that targets telco applications on Arm processors at the edge
  • The Network Cloud family of blueprints, which automate deployment of edge sites from a regional controller
  • The StarlingX Far Edge Distributed Cloud, which addresses high-density, far edge use cases for value-added services

Enhancements will be made to the baseline functionality of Akraino R1, and the community is planning new blueprints, tools, edge APIs, and community lab hardware in R2.

For more information on the Akraino Edge Stack visit

For more on LF Edge, visit

About the Author

Brandon Lewis

Brandon Lewis, Editor-in-Chief of Embedded Computing Design, is responsible for guiding the property's content strategy, editorial direction, and engineering community engagement, which includes IoT Design, Automotive Embedded Systems, the Power Page, Industrial AI & Machine Learning, and other publications. As an experienced technical journalist, editor, and reporter with an aptitude for identifying key technologies, products, and market trends in the embedded technology sector, he enjoys covering topics that range from development kits and tools to cyber security and technology business models. Brandon received a BA in English Literature from Arizona State University, where he graduated cum laude. He can be reached by email at

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