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LF Edge Member Spotlight: Edgenesis

By Blog, LF Edge, Member Spotlight

Author: Yongli Chen, founder & CEO at Edgenesis

About Edgenesis

Edgenesis is an open-source IoT interoperability and edge computing solution provider. 

Edgenesis is a technology company specializing in industrial edge solutions. We aim to drive standardization in device-driven IoT applications and offer flexible, efficient solutions to optimize production processes and reduce costs. Our team includes top talent from companies like Microsoft, McKinsey, Google, and Amazon, and we pride ourselves on our professionalism and efficiency. 

Using a Kubernetes-native development framework, we help clients deploy and manage devices and applications for various use cases. Our solutions provide critical data on devices and production processes, empowering clients to make data-driven decisions and stay competitive in the manufacturing industry. At Edgenesis, we are dedicated to innovation, constantly striving to improve our products and services to offer cutting-edge solutions. Our goal is to create a smarter, more connected world by leveraging our expertise in industrial edge solutions.

Why is your organization adopting an open source approach?

Mobile Internet was mostly about mobile phones connecting to the Internet to consume content. We’re now transitioning to the hyper-connected world era where digital intersects with every aspect of the physical world around us. Therefore digital solutions should mimic physical interactions. We believe in an ecosystem and the ability for solutions to interact across different vendors and providers. Now more than ever collaboration across the community is of importance. Therefore, we like to embrace an open-source model for any of our offerings.

Why did you join LF Edge and what sort of impact do you think LF Edge has on the edge, networking, and IoT industries?

We want to work with the LF Edge umbrella to facilitate the development of edge computing in a structured, collaborative way.

What do you see as the top benefits of being part of the LF Edge community?

One of the many benefits we see in being part of the LF Edge project community is the opportunity to collaborate with like-minded professionals across the globe. 

What sort of contributions has your team made (or plans to make) to the community, ecosystem through LF Edge participation?

Shifu, an open source Kubernetes-native industrial edge which enables IoT interoperability. Shifu virtualizes IoT devices into Kubernetes pods, and gives you the all-in-one Kubernetes cluster which orchestrates IoT devices and applications at the same time.

What sets LF Edge apart from other industry alliances?

It’s the only organization that focuses solely on all aspects of edge computing across verticals. 


Fledge’s Journey: Celebrating its Graduation to Impact Stage in LF Edge

By Blog, Fledge

Fledge was first introduced in 2017 as an open source project by the Linux Foundation. The Fledge project, an open source framework for Industrial Internet of Things (IIoT) applications, was initially created by Dianomic with the goal of developing a lightweight and scalable platform for collecting and analyzing data from industrial devices. Dianomic contributed the Fledge codebase to the Linux Foundation with the goal of establishing an open and collaborative community around the project, as a solution to the challenges faced by IIoT applications, such as the need for real-time data processing and analysis, the need for secure and reliable data transport, and the need for a scalable and extensible platform among others. 

Three Maturity Stages for LF Edge Projects

Since its initial contribution, the Fledge community has continued to support, develop and grow Fledge as an open source project under LF Edge. The LF Edge technical steering committee (TAC) defines three maturity stages for projects:

  • Stage 1: At Large Projects: projects the TAC believes are, or have the potential to be, important to the edge ecosystem as a whole. They are typically early-stage efforts looking to add capabilities to the LF Edge open edge platform as a whole in exchange for community support. 
  • Stage 2: Growth Stage: projects that are interested in reaching the Impact Stage, and have identified a growth plan for doing so. The Growth Stage is meant to harbor projects still working on their product or service and are working towards supporting adopters at scale using the product or service. Expectations of the project Growth Stage projects have well-formed and documented processes, procedures and practices for planning, designing, implementing and documenting their intended edge product or service. Growth Stage projects have the resources (leadership, people, tools, infrastructure) necessary to deliver their product or service.
  • Stage 3: Impact Stage: projects on a self-sustaining cycle of development, maintenance, and long-term support. Impact Stage projects are widely used in production environments with a significant number of public use cases. Moreover they have broad, well-established communities with a number of diverse contributors. Expectations of the project include publicly known end-user production deployments, active participation in TAC proceedings, and as such have a binding vote on TAC matters such as the election of a TAC Chair, have publicly documented release cycles, ability to attract a number of committers on the basis of its production usefulness.

Fledge is the first and only project to graduate all the way to Impact Stage from At Large Stage under the LF Edge.

Today, Fledge is widely used in IIoT applications across a variety of industries and continues to evolve and grow with contributions from a thriving community of developers and adopters. The Fledge project and community focuses on industrial data pipelines to and from industrial assets and systems, edge applications and edge machine learning. Our community, users and contributors are suppliers and integrators to industrial markets as well as industrial companies including:  AVEVA, Schneider Electric, OSIsoft, RTE, JEA, Google, Neuman-Aluminum, FLIR and Dianomic.   The Fledge project has expanded into LF Energy’s Project FledgePower with 67 energy companies and suppliers and OSDU (an Open Group Project)  with 167 Oil and Gas companies and suppliers.   Fledge is deployed in both process and discrete manufacturing helping produce: drone military aircraft, engines, aluminum car parts, food processing, chemical polymers, energy, oil and gas, paper products, premium wines, professional auto racing digital twins and more.

While Fledge is open source and freely available for use, there are companies that offer commercial support and services for Fledge. For example, Dianomic, one of the original contributors to the project, provides commercial support, training, and consulting services for Fledge. 

FLIR Systems, Inc. a company that specializes in the development and production of thermal imaging cameras and systems has contributed to the development of Fledge by integrating its thermal imaging technology with the Fledge platform. The integration of FLIR’s technology with Fledge enables industrial customers to analyze thermal data in real-time, allowing for early detection of potential issues and proactive maintenance. The integration of FLIR’s technology with Fledge has resulted in the creation of several use cases for the platform, including monitoring the temperature of equipment in manufacturing plants, detecting anomalies in electrical systems, and monitoring the thermal performance of buildings and infrastructure. Overall, FLIR’s involvement in the development of Fledge highlights the potential of combining edge computing and industrial IoT technologies with advanced imaging and sensing capabilities to enable early detection of potential issues, increased operational efficiency, and improved safety.

AVEVA, a leading provider of industrial automation and software solutions, announced a strategic partnership to enable the integration of FogLAMP with AVEVA’s industrial software solutions. As part of this partnership, AVEVA became a reseller of FogLAMP software, providing its customers with access to the open-source platform for use in their industrial applications. The integration of FogLAMP with AVEVA’s industrial software solutions enables customers to collect, process, and analyze data from industrial assets in real-time, providing insights into performance and enabling predictive maintenance. The partnership also provides customers with access to a broad range of industrial automation and software solutions, combined with the flexibility and customization of the open-source Fledge platform. Overall, the partnership between AVEVA and Dianomic aims to provide customers with a comprehensive solution for their industrial automation and IIoT needs, leveraging the strengths of both companies in the industrial software market.

Fledge is Not a General Purpose Edge Platform  

Fledge was developed by and for industrial suppliers and companies to address the specific needs of industrial markets.   Developers adopting Fledge get all the time to market, licensing and community advantages of Linux Foundation projects.  They get a community with deep industrial, data processing and machine learning understanding.  And, most importantly, they get a final product or service that meets the exacting requirements of industrial users.

AccuKnox joins mimik Technologies, IBM as Open Horizon project partner

By Blog, Open Horizon

The Open Horizon project, contributed by IBM to the Linux Foundation, developed a solution to automate complex edge computing workload and analytics placement decisions. Open Horizon also provides end-to-end security for the deployment process using security best practices. As a result of its rigorous adherence to recommended procedures, the Open Horizon project recently earned the OpenSSF Best Practices badge.

While Open Horizon provides secure container deployment, it cannot guarantee that a container is free of flawed code or other vulnerabilities that could put the system at risk, nor that a container is inherently safe from someone else’s malicious workloads running on the same host. That’s where a dynamic runtime security solution like KubeArmor comes in.

KubeArmor is an open-source project at CNCF (Cloud Native Computing Foundation) foundation that secures containerized workloads.  But until recently it only did so within Kubernetes clusters. AccuKnox, in conjunction with KubeArmor and Open Horizon, added additional coverage to KubeArmor to ensure the security of deployed workloads on both Kubernetes clusters and bare Linux hosts running a container engine like Docker or podman.

KubeArmor provides deep visibility into the behavior of the deployed workload, including network, process, and file operations. This information is vital when making policy decisions related to workload security. In the context of Open Horizon, it was interesting to observe the runtime behavior of the anax agent and the containerized edge workloads that it deployed.

After thorough evaluation and approval by IBM developers, AccuKnox contributed the integration code to the Open Horizon project. The contribution was significant enough to qualify AccuKnox for membership in the Open Horizon project as a partner and voting member. The Technical Steering Committee then voted to invite AccuKnox to join based on the value of their work and the strength of their contribution.

To learn more about the Open Horizon project and how anax automates workload placement, consider attending the project’s Agent Working Group meetings.  The KubeArmor integration code is available in the GitHub repository.

Leaders in LF Edge: Interview with Michael Maxey

By Blog, LF Edge

Gartner predicts that by 2025, more than 50% of enterprise-managed data will be created and processed outside the data center or cloud, with an over $500 billion increase in the edge computing market by 2030. As edge computing becomes a significant revenue opportunity for the technology and telecom industries, it’s even more important to have effective leaders to advance the future of edge computing industry.

Today we sat down with Michael Maxey, Vice President of Business Development at Zededa. Maxey tells us how he got involved in the edge computing industry and why leaders must plan for the growth of IoT and edge.

How did you get involved in the LF Edge community and what is your role now?

I joined ZEDEDA in 2022 as the Vice President for Business Development, to drive the company’s efforts in building out a rich ecosystem of partners, and ultimately to enable customers an easy way to compile the disparate solutions their projects required. Getting involved with LF Edge was a natural extension of these efforts. Today I sit on the LF Edge Governing Board.

What is your vision for the edge computing industry? Tell us briefly how you see the edge market developing over the next few years.

What we’re seeing today within the edge computing industry is just scratching the surface of what is possible. Edge deployments are largely bespoke, with each enterprise building a unique stack to solve specific business needs. We’re going to see this change as the industry develops. Deployment patterns will lead to standardization of the lower levels of the technology stack, providing a common set of services to help build and deploy applications, much like the LAMP stack in the early days of computing. This standardization of services will unlock massive developer communities, who have been building in the cloud for the past 10 years, and as a result, will drive a massive transformation of computing outside of the data center.

What impact do you see open source playing in the evolution of the edge market? And how has it shaped where we are today?

Open source brings a lot of benefits but the biggest one I see within the edge market is that of standardization. It’s hard to get your head around scale at the edge – it’s not just the sheer number of deployed devices and sites, but it’s that number split across many different types of hardware, running many different applications, and all in service to an endless number of use cases.  Standardization is key to enabling interoperability across all of this heterogeneity and provides an open foundation that ensures organizations can build something without falling into the silo trap that hinders the growth of so many projects.

Why is LF Edge important to advance the future of edge computing?

LF Edge is important for a number of reasons. First, the organization is driving the standardization that the heterogeneity and scale of the edge requires. Second, it has taken the fragmented edge landscape and given people a common taxonomy and framework to discuss, define, and understand it. Third, it has brought together existing efforts to address different parts of the edge landscape under a common umbrella, not only enabling interoperability between those projects but illustrating how the complexity of the edge requires an ecosystem of solutions in order to solve individual problems.

What is ZEDEDA’s role in edge computing and LF Edge?

ZEDEDA delivers a distributed, cloud-native edge management and orchestration solution, simplifying the security and remote management of edge infrastructure and applications at scale. Through ZEDEDA’s ecosystem of partners, customers can easily deploy any application at the edge via a Marketplace, enabling customers ease of use as they use different solutions for their edge projects. ZEDEDA leverages EVE, an LF Edge project, to provide an open, flexible and secure foundation while abstracting the complexity of the diverse hardware, connectivity and software at the distributed edge and eliminating any vendor lock-in. ZEDEDA customers include Fortune 500 companies from industries like energy, automotive, and manufacturing with thousands of edge nodes in production today across the globe.

ZEDEDA was a founding member of LF Edge and in May of 2019 donated the original code for what became EVE to LF Edge. Today ZEDEDA is active within LF Edge at multiple levels: within EVE from an ongoing code development perspective to sitting on the LF Edge Governing Board, as well as the Technical Advisory Council and Outreach Committee to continually evangelizing LF Edge to analysts, the media, customers, and more.

What advice do you give to organizations who want to get involved in the LF Edge community?

Now is the time to get involved! There’s a real need across the industry to develop architectural blueprints, build solutions, and in general demonstrate the transformative value that can be gained by making sense of all of the data that organizations generate across their distributed environments. By getting involved now, organizations are able to have real impact driving standardization, developing recommendations, and helping to create solutions applicable across industries and use cases.


Efficiently Collect, Transform and Transit Your Data With eKuiper 1.9 Release

By Blog, eKuiper, Project Release

eKuiper—a lightweight IoT data analytics and streaming software—is now available in its 1.9.0 release. eKuiper, an LF Edge project, migrates real-time cloud streaming analytics frameworks such as Apache Spark, Apache Storm and Apache Flink to the edge. eKuiper references these cloud streaming frameworks, incorporates any special requirements of edge analytics and introduces rule engine, which is based on Source, SQL (business logic) and Sink; rule engine is used for developing streaming applications at the edge.

eKuiper 1.9 release continues to enhance the source/sink connectors to make it easier to connect and transmit data with lower bandwidth. The community has also enhanced the data transformation ability to flexibly encode and compress any part of your data. The 1.9 release adds a number of significant new features, among them are

  • Multiple neuron connection to analyze collected data from multiple IOT gateways together
  • MQTT sink/source compression/decompression support, save bandwidth for edge cloud communication
  • HTTPPull source & REST sink support dynamic token based authentication, connect to more services out of box
  • More transformation and compression functions added, handle your data flexibly
  • Partial data export/import, migrate only interested rules and the dependencies
  • Run python plugin in conda virtual environment, separate the python runtime env

Learn more about these and other features of eKuiper’s 1.9 release in the release notes.

What’s next

In the next release, the community will adapt to the EdgeX Foundry‘s Minnesota version, while exploring the use of external states such as Redis states to achieve persistent states.

Akraino and CAMARA Communities Join Forces to Boost API Integration in Edge Computing

By Akraino, Blog

At the Hefei High-tech Integrated Circuit Incubation Center in Anhui Province, a panel discussion moderated by Guanyu Zhu from Huawei’s Cloud Network OSDT team brought together experts from the Akraino and CAMARA communities, along with industry professionals, to explore the significance of APIs in edge computing and the potential for collaboration between the two communities. Prominent panelists included Tina Tsou, LF Edge Board Chair, Leo Li from Akraino TSC, Gao Chen, the senior engineer from China Unicom, and Shuting Qing, the open-source ecology expert from Huawei’s Cloud Network OSDT.

Shuting Qing provided insights into the origins of the CAMARA project, explaining that “Capability exposure aims to encapsulate these capabilities into a simple interface and expose it to developers for everyone to use.” CAMARA is a vital initiative designed to generate new revenue streams for European operators that have made substantial investments in 4G/5G networks. Qing emphasized the need to clarify the value scenarios and focus on monetization.

Leo Li discussed Akraino’s eagerness to collaborate with emerging communities like CAMARA, emphasizing the need for standardized edge computing hardware modules and the adoption of novel hardware interface technologies such as Ethernet, PCIe, and UCIe. Li highlighted the importance of integrating standardized hardware with an API-based business development model, stating, “We hope to further enhance the business flexibility of operators while promoting hardware standardization, and reduce costs and power consumption through standardization in conjunction with the trend of service APIization.”

The panelists also shared their views on the commercial realization of telecom edge cloud. Gao Chen emphasized the standardization of east-west interfaces, highlighting the importance of providing a unified and user-friendly API to access network capabilities, while Tina Tsou pointed out the potential benefits for various stakeholders, noting that “Edge computing can provide better performance and services, thereby increasing customer loyalty and revenue.”

Addressing potential challenges in implementing commercialization ideas, Leo Li indicated that “We believe that cost will be a crucial factor in the monetization process of edge cloud.” He advocated for standardizing hardware specifications and implementation methods and adopting an API-based business development model to minimize costs.

Tina Tsou expressed her expectations for the CAMARA community, emphasizing the need for more flexible and customizable edge computing capabilities, stronger equipment and data management capabilities, and enhanced security and credibility guarantees. She also called for increased cooperation with other open-source projects.

Shuting Qing and Tina Tsou shared their thoughts on how Akraino and CAMARA could work together to create a more open, collaborative, and innovative edge computing ecosystem. Qing considered that since CAMARA is discussing capability exposure, it would be worth exploring the integration of edge computing open capabilities, such as ETSI MP1, into the CAMARA. Meanwhile, Tsou proposed combining edge computing framework, openness, security and privacy protection, and application scenario expansion.

The panel discussion offered valuable insights into the role of APIs in edge computing and the potential collaboration between Akraino and CAMARA. As the industry continues to develop, the joint efforts of these two communities could result in a more open, collaborative, and innovative edge computing ecosystem that benefits all stakeholders.

Baetyl New Release Integrates With eKuiper and Delivers Edge to More Devices

By Baetyl, Blog, eKuiper, Project Release

Baetyl—an LF Edge project that extends cloud computing, data and service seamlessly to edge devices— has released v2.4.3 release. With the efforts of many active contributors, new functions have been added, and some existing functions have been continuously optimized since the previous v2.3.0 release. These new features continue to follow the cloud-native philosophy and build an open, secure, scalable, and controllable intelligent edge computing platform.

Compared to the previous Baetyl v2.3.0 releases, the new features and optimizations in v2.4.3 include:

  • Device management functionality has been refactored with the addition of a device template interface, support for calculating OT data collection values, support for IEC-104 protocol, updated OPC-UA and Modbus drivers, and updated driver-node binding logic;
  • Support for Windows platform has been added with the ability to generate Windows – platform images for the Baetyl edge main module;
  • Remote invocation has been implemented, allowing for remote access to specified edge services with results returned from the cloud;
  • New container mode with eKuiper as an optional system application;
  • New baetyl-rule module supports HTTP Target;
  • Adaptation to the highest K3s 1.24.4 version;
  • Fix workload type creation failure bug;

These new features are available and now you can view the release note here. Other features can be further explored by the developers, and Baetyl will continue to improve and optimize its functionality.

Integration with eKuiper

Baetyl uses eKuiper as a system optional application on the edge-side for stream processing and data analytics. The collaboration and integration with eKuiper increase the linkage between LF Edge projects and promote innovation. Platform and version adaptation enables Baetyl to run on more devices. The optimization of device management and new driver support prepare for the access of more devices with different protocols. From the point of eKuiper, this means you can deploy eKuiper more quickly and conveniently.

In the new version, the integration between Baetyl and eKuiper makes the following changes, including:

  • set mqtt client as Baetyl broker; 
  • mount eKuiper’s data file to the host to ensure no configuration loss; 
  • add k8s service to the eKuiper application to enable calling eKuiper’s open API from the host as well as from within the cluster to enable edge configuration changes; 
  • built-in eKuiper as an optional application in the Baetyl framework, so that eKuiper can be installed directly through Baetyl, eliminating the need for separate installation; 

After the integration, the Baetyl framework enhances the ability of edge message processing, while users can use Baetyl’s ability to use eKuiper more easily and quickly.

What’s next?

For future releases, the project is working on strengthening the management of non-intelligent devices at the edge, including providing

  • more comprehensive management functions for device models, devices, and drivers on the cloud management platform, 
  • a software gateway management module on the edge to support the ability of devices to connect through various industrial drivers,
  • a unified northbound connection protocol blink for access implementation.

The Baetyl project is also further expanding and optimizing the implementation of cloud storage at the underlying level, providing support for database storage outside of k8s crds. It’ll also enhance the integration with K8s cloud-native, providing more edge cloud-native capabilities for access, such as providing the ability to view edge description information, and so on.

Webinar Recap: How LF Edge Projects Track CO2 Footprint with Secure Monitoring at the Edge

By Alvarium, Blog, Project EVE

With community members from over 50 organizations gathered on LinkedIn and Zoom last week, LF Edge kicked off its first webinar this year. This webinar is a continuation of the “On the Edge with LF Edge” webinar series where we invite community members and industry leaders to share production case studies, project demos, and the latest updates from the LF Edge project communities! 

For this webinar, we had distinguished speakers, Mathew Yarger, Advisor at IOTA and Co-Founder of DigitalMRV, Steve Todd, VP Data Innovation and Strategy at Dell Technologies, and Kathy Giori, Global Partnerships and Outreach at MicroBlocks, who shared their insights on the LF Edge use case of using Project Alvarium and EVE to monitor the carbon footprint in the world’s first BioGas Plant, which uses harvest waste as its only fuel.

To kick off the webinar, the speakers addressed the challenge of inaccurate emissions reporting in sustainability. In fact, “85% of organizations are concerned about reducing their emissions, but only 9% are able to measure their emissions comprehensively,” said Yarger. The VSPT Wine Group in Chile required a solution to process data from various sensors measuring water, solids, gases, and anaerobic digestion processes in real-time to provide reliable insights into their carbon footprint. This issue was tackled by leveraging the Data Confidence Fabric (DCF) framework of Project Alvarium and the cloud computing capabilities of Project EVE.

You can read the published use case on the LF Edge case studies page and watch the webinar recording below to learn more about how LF Edge projects enable organizations to take more informed and effective steps toward reducing their environmental impact.

Love this webinar? Make sure to subscribe to LF Edge on LinkedIn, so you won’t miss our next webinar and the opportunity to engage with the speakers live!

Get involved:

If you’re interested in getting involved in Project Alvarium and Project EVE, you can find the communities on the LF Edge Slack channels #eve and #alvarium (and related channels).

Project Alvarium:

You can learn more about Project Alvarium by visiting its wiki and GitHub. Have questions about the project? Subscribe to the project mailing list and Technical Steering Committee (TSC) mailing list and attend the TSC meetings every two weeks at 11 AM Eastern Time.

Project EVE:

You can learn more about Project EVE by visiting its wiki and GitHub documentation. Have questions about the project? Subscribe to the project mailing list and attend the TSC meetings that occur every four weeks on Thursday at 11:30 AM Eastern Time.

The developer program offered by ZEDEDA lets industry adopters run proof-of-concept (PoC) distributed edge orchestration programs at no cost. The Alvarium/IOTA teams have developed their applications and tools to be ready to deploy on EVE, so that you can remotely manage them no matter where your EVE edge node is located.

Akraino Displays Robotics Blueprint at ONE Summit 2022

By Akraino, Blog, Event

By Jeff Brower, CEO at Signalogic & LF Edge community member

At the ONE Summit (ONES) in Seattle in November, the Linux Foundation Edge community (LF Edge) presented state-of-the-art edge computing in areas of Telco, Oil & Gas, Manufacturing, and Retail. The Akraino blueprint “Robot Architecture Based on SSES” was selected by the LF Edge conference showcase committee to exhibit in the Manufacturing category. This blueprint is architected by Fujitsu and focuses on two key areas in robotics:

  • manipulating elastic and non-uniform objects with variable shapes and surfaces, under variable environmental conditions
  • safe and reliable robot-human interaction


Fujitsu and Signalogic personnel manned the Manufacturing kiosk and we’re happy to report the exhibit was well-attended and effective. While we didn’t see a pre-pandemic level of attendance (maybe half compared to 2019), that was made up for by enthusiasm and energy of attendees and exhibitors. It was a great feeling driving into Seattle on a cold but sunny day, negotiating the city’s notoriously gnarly freeway design and traffic, arriving at the Sheraton, and then focusing 100% on presenting LF Edge, Akraino, and robotics to technical
and business developers ! We can confidently report that in-person conferences are back and thriving.

As it turns out, the conference format was effective for promoting robotics as well as Akraino and LF Edge. As one example, our blueprint’s project team leader, Fukano Haruhisa-san from Fujitsu’s development labs, gave a technical presentation in the early afternoon of Day 1.
Then later in the day, while dinner was served near the exhibit area, attendees who had attended Fukano-san’s presentation zero’d in on our kiosk. They had been busy juggling their conference schedule, but now they had questions and were ready to dig deeper. That was also our chance to promote LF Edge and Akraino. Naturally we took full advantage 😀

Customer discussions at the kiosk were both wide ranging and in-depth. Of particular concern is how to merge requirements for compute intensive onboard processing (i.e. on the robot) with cloud processing. There is a mix of needs, including mapping, handling unusual and as-yet-unknown objects, failure prediction, real-time speech recognition, background noise removal, natural language processing, and more.  Some needs can be met in the cloud, and some demand “never down, never out” capability. The former can be met with containerization, Kubernetes, and other CICD and automation tools, while the latter requires intensive onboard computation. Of course, any onboard computation faces severe limitations in size (form-factor), weight, and available power. It’s a fascinating problem in edge computing and engineering tradeoffs.

Given the effectiveness of the ONE Summit format, I strongly urge the LF Edge board to organize and promote more combined technical + exhibit events. The exhibit component does two important things: (i) encourages effort and progress among blueprint participants, and (ii) provides feedback to shape and guide blueprints moving forward. A little pressure to meet conference schedule deadlines and get demos working is a good thing, and the payoff for LF Edge is increased industry exposure for its member projects.

2022 LF Edge Annual Report – Update from the General Manager

By Blog, LF Edge

Launched four years ago, LF Edge has become the center of gravity for some of the most impactful open source edge computing projects in the world, building an open, modular framework for edge computing. Check out the section below on the 2022 LF Edge Annual Report update from Arpit Joshipura, General Manager, Networking, Edge & IoT at the Linux Foundation.

LF Edge community members meet and collaborate in-person at ONE Summit 2022

Entering its fourth year as an umbrella project, LF Edge continues to grow and thrive, with more and more deployments and use cases across the globe and across verticals, from Telco, to Smart Home, to Industrial IoT, to AI, Robotics, and more. Check out the section below on the 2022 LF Edge Annual Report update from the LF Edge Board, written by Tina Tsou, Enterprise Architect, Arm and LF Edge Governing Board Chair.

As we enter into 2023, I wanted to take a moment to reflect on the great progress made as a community last year. Although we’re learning to live with a global pandemic, an uncertain economy, and more colorful geopolitical issues, all of these challenges didn’t slow down the growth of open source communities; with more innovation, and integration across verticals as the industry marches towards digital innovation.

One of the things that makes me most proud of LF Edge project is the fact that the community did not miss a beat in our work-from-home virtual world. In 2022, the number of LF Edge contributors increased by 138%, with an average of 1,120+ contributors per year. With 65+ members and 25%+ year-over-year membership growth, more and more organizations have joined LF Edge’s mission of unifying and providing edge computing projects, IoT frameworks and solutions/blueprints to serve the needs of Telecom Edge, Cloud Edge, IoT Edge, Industrial IoT Edge, Enterprise Edge markets, and more.

I wanted to also take a moment to look ahead to 2023, as well as recognize how the edge industry has shifted over the past year. 2022 was the tipping point for 5G, Edge & IoT deployments, all possible with Open Solutions, Open Collaboration and Open Communities. This year, the global collaboration in open source projects (including LF Edge) is better than ever. Our community has worked collaboratively across geopolitical and macroeconomic headwinds, which we intend to continue in 2023.

I’d like to close by thanking our entire community and ecosystem of members, developers, partners, and users. I hope to see more in-person or virtual collaboration happen in LF Edge this year. Here’s to a fantastic 2023 as we build the last cloud together — the edge!

Read the full 2022 LF Edge Annual Report, with community highlights from all LF Edge projects, TSC Chair, General Manager, Outreach Chair, and more.