Monthly Archives

July 2020

LF Edge Member Spotlight: Mocana

By Blog, EdgeX Foundry, LF Edge, Member Spotlight

The LF Edge community comprises a diverse set of member companies and people that represent the IoT, Enterprise, Cloud and Telco Edge. The Member Spotlight blog series highlights these members and how they are contributing to and leveraging open source edge solutions. Today, we sat down with Dave Smith, President of Mocanato discuss the importance of open source, collaborating with industry leaders in edge computing, security, how they leverage the EdgeX Foundry framework and the impact of being a part of the LF Edge ecosystem.

Can you tell us a little about your organization?

Mocana revolutionizes OT and IoT with cyber protection as a service for trustworthy systems. The company helps device operators bridge the adoption challenge between vendors and service providers, and delivers key cybersecurity benefits to the emerging 5G network, edge computing applications, and SD-WAN enterprise networks. Mocana protects the content delivery supply chain and device lifecycle for tamper-resistance from manufacture to end of life, with root-of-trust and chain-of-trust anchors. Mocana measures devices for sustained integrity and the trustworthiness of operations and data to power artificial intelligence/machine learning analytics. The Mocana team of security professionals works with semiconductor vendors and certificate authorities to integrate with emerging technologies to comply with data privacy and protection standards. The goal of cyber protection as a service is to eliminate the initial cost of modernization for device vendors and empower service providers to offer subscription-based services for the effective and efficient expansion of corporate and industrial digital transformation strategies.

Mocana’s core technology protects more than 100 million devices today, and is trusted by more than 200 of the largest energy, government, healthcare, manufacturing, IoT, telecommunications & networking, and transportation companies globally.

Why is your organization adopting an open-source approach?

Mocana is eager to support the global body of customers adopting the EdgeX Foundry open source solution. OpenSSL is by far the most broadly integrated and implemented open source security stack. It comes freely available and is distributed as part of the LF Edge distributions. However, in recent years OpenSSL has come under scrutiny because of critical security vulnerabilities and the resulting issuance of CVEs. The Heartbleed vulnerability from 2014 was a notable exploit, and there are several other recent CVEs that have generated concern in the information security community. The strategy of taking a defensive position through ongoing patching of vulnerabilities continues to challenge efforts to protect mission-critical OT environments.

Since the founding of the LF Edge projects, the goal has been to pull together a body of code to standardize the microservices delivery and orchestration for edge computing systems and devices. The projects continues to advance commercial third-party solutions to address key functional areas, especially for mission-critical and vertical industry applications. Mocana’s solution is based upon a commercially supported, NIST FIPS 140-2 certified, cryptographic module. Many of the company’s Fortune 500 customers have realized significant benefits from the ability to quickly migrate from default products integrated with OpenSSL to Mocana’s offering, leveraging its OpenSSL connector.

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

Developing, deploying, operating, and managing IoT and edge computing requires a community of key, forward-looking technology innovators. The IoT-edge ecosystem spans a wide supply chain from first silicon to the cloud, and includes system integrators, end-user operators and asset owners. Mocana was one of the first 50 founding members of EdgeX Foundry in 2017. Early on, the company took an industry leadership position by driving industry adoption through off-the-shelf solutions developed through stakeholder collaboration. This approach addressed a variety of common use cases delivered by new edge computing technologies and applications, and required much more than a reference architecture. Mocana recognized the need for the user community and developing ecosystem to leverage community-developed code (e.g. Github) to reduce feature and software code duplication and enable the broadest possible market adoption. The customer benefit reduces the implementation risk for such new technologies and accelerates community stakeholder time to market.

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

Mocana values LF Edge’s ecosystem breadth and depth of community members and stakeholders, which includes chip companies, device ODMs, OEMs, carrier service providers, and asset owner/operators. Each contributes key use case challenges that have been invaluable for ensuring that LF Edge can support key technology developments and marketplace challenges.

What sort of contributions has your team made to the community, ecosystem through LF Edge participation?

As key contributor to the community, Mocana worked with the EdgeX Foundry Security Working Group and offered insights and guidance on vital security use cases. The company ensured there was always a path to address developing cybersecurity mandates and best practices from NIST Cybersecurity Framework and ISA/IEC 62443. As a result, the community has delivered a number of key security functions. They added a reverse proxy, provided a method to secure the key store with the ability to manage it, and has integrated access to session-based security to the microservices.

Perhaps most important, Mocana has enabled the community to incorporate a scalable, robust, and commercially supported cybersecurity offering for EdgeX Foundry production development and deployments.

Mocana developed its OpenSSL connector to ease migration from default project configurations with OpenSSL to Mocana’s TrustCenter and TrustPoint offerings. This solution aligns well with the project’s objectives to accelerate adoption and deployments of standardized implementations addressing key edge computing use cases with microservices.

What do you think sets LF Edge apart from other industry alliances?

Delivering actual code that organizations can download, compile, run, and then operate is a tremendous benefit compared to most other industry alliances. It is a major differential in comparison to groups that only suggest frameworks and prescriptions of possible features, implementations, and suggested “best practices.”

How will LF Edge help your business?

Demand is growing for edge computing solutions. Hitting 5 million downloads of the EdgeX Foundry SDK in May are proof of that. Mocana also is beginning to see initial commercial success and adoption in the innovation and R&D centers by key community members. The company’s ability to enable its fully integrated TrustCenter and TrustPoint solutions leveraging an OpenSSL connector provides a clear and rapid path to EdgeX device security lifecycle management and supply chain provenance. Plus, it will increase adoption of Mocana’s latest edge device offerings from the community.

What advice would you give to someone considering joining LF Edge?

Find your niche in one of LF Edge’s nine collaborative projects where your offering can deliver the most value and contribute. There has never been a better time to participate in this open source community, which is looking for complementary solutions and ways to deepen the ecosystem.

To learn more about EdgeX Foundry, click here. To find out more about our members or how to join LF Edge, click here.

Additionally, if you have questions or comments, visit the  LF Edge Slack or the EdgeX Foundry Slack to share your thoughts and engage with community members.

Fledge, an LF Edge Project, Enters Growth Stage as Release 1.8 Enables Open Industrial Edge Software with AI/ML, and Public Cloud Integration

By Announcement, Fledge
  • Expanded community includes integrations and contributions from Google, Nokia, Flir, OSIsoft, Nexcom, RoviSys, Advantech, Wago, Zededa and Dianomic
  • Supports complementary products and services from a global open ecosystem, with commercial support, developer support, training, ML/AI applications and scale-up and out management
  • Use cases include Gradient Racing, which uses Fledge and Google Cloud to optimize complex machine configurations and operations using ML/AI, car and driver simulators and race track digital twins  

SAN FRANCISCO – July 30, 2020 LF Edge, an umbrella organization within the Linux Foundation that aims to establish an open, interoperable framework for edge computing independent of hardware, silicon, cloud, or operating system, today announced maturing of its Fledge project, which has issued it’s 1.8  release and moved to the Growth Stage within the LF Edge umbrella. Fledge is an open source framework for the Industrial Internet of Things (IIoT), used to implement predictive maintenance, situational awareness, safety and other critical operations.  Deployed in industrial use cases since early 2018, Fledge integrates IIoT, sensors, machines, ML/AI tools-processes-workloads, and cloud/s with the current industrial production systems and levels, as per ISA-95.  

Fledge v1.8 is the first release since moving to the Linux Foundation. However, this is the ninth release of the  project code that has over 60,000 commits, averaging 8,500 commits/month. Concurrently, Fledge has matured into a Stage 2 or “Growth Stage” project within LF Edge. This maturity level is for projects interested in reaching the Impact Stage, and have identified a growth plan for doing so. Growth Stage projects receive mentorship from the Technical Advisory Committee (TAC) and are expected to actively develop their community of contributors, governance, project documentation, and other variables identified in the growth plan that factor in to broad success and adoption.

“Fledge, initially seeded by OSISoft and Dianomic and now a diverse project within LF Edge, is a great example of open source integration. By working closely with Google and other ecosystem partners on new and emerging use cases, we are bringing the power of LF Edge to a broader market,” said  Arpit Joshipura, general manager, Networking, Edge and IoT, the Linux Foundation. “We look forward to building an open community of industrial users, suppliers and integrators.”  

Utilizing Fledge to gather and analyze machine, process, environment and operator data in context, improved efficiency, quality and safety is achieved.  Gradient Racing used Fledge, Google Cloud, and Motorsports.AI to build IIoT based digital twins of each track, a machine simulator and an operator simulator to optimize car configurations and driving strategy before each race.  Using Fledge, TensorFlow and Kubernetes, two all-time track records were broken in the GT3 2019 season. See the full story here.  

“Google Cloud helps customers deliver artificial intelligence to applications from the edge to the cloud,”  said Craig Wiley, director of Product Management for Google Cloud AI.  “Fledge’s ability to collect, process, transform and send machine data as well as run TensorFlow Lite on the edge makes it an excellent complement to Google’s AI platform. As an active member of the Linux Foundation, Google is proud to support this open source community through contributions to the Fledge project, empowering next generation industrial processes and machines.”

Fledge has rapidly become one of the most active open source IIoT projects. Adding to the momentum are new contributors, contributions and integrations. Highlights include:  

  • Google’s contribution of its IoT Core North Plugin, enables secure, reliable transfer of data to Google cloud services like machine learning.   
  • OSIsoft’s contribution of  the Web API North Plugin, enables Fledge secure, reliable transfer of telemetry and metadata to existing ISA95 systems like PI, OCS and EDS.   
  • Nexcom’s contribution of CAN bus 2.0, J1708 and J1939 south plugins provide real-time monitoring for fleet management of cars and heavy duty trucks.   
  • Dianomic’s contribution of new core services, alert services and orchestration services enable advanced vibration-based applications, more security and scalable management.   
  • Nokia integrated Fledge with the Nokia Digital Automation Cloud (NDAC), Nokia’s industrial-grade private wireless network.  
  • Google and Nexcom completed integration of Fledge within Google’s Coral line of ML processors and Nexcom’s industrial gateways.  
  • Flir and Dianomic completed a south plugin integration with Flir’s line of industrial infrared cameras.  

Industrial Operational Technology (OT) markets are new to the Linux Foundation, and open source projects are new to OT use cases. Like the LAMP stack enabled web application development, the Fledge project’s mission is to enable IIoT application development.  Together we can solve the diversity and complexity issues when collecting and processing data beyond  current control networks and eliminate silos of data by integrating with mission-critical ISA95 systems, ML systems, and the cloud.  

Learn more about Fledge in an upcoming On the Edge with LF Edge webinar, entitled “How Google, OSIsoft, FLIR and Dianomic use Fledge to implement Industrial 4.0,” August 13 at 9 am PT. Details and registration here:https://zoom.us/webinar/register/9215960636525/WN_1jGqjfJoT4-Iv2y6YDGgYg 

Join Fledge and other LF Edge projects at the Open Networking & Edge Summit (ONES), a virtual experience happening September 28-30. ONES is the industry’s premier open networking event now expanded to comprehensively cover Edge Computing, Edge Cloud & IoT. Open Networking & Edge Summit (ONES) enables collaborative development and innovation across enterprises, service providers/telcos and cloud providers to shape the future of networking and edge computing. Learn more and register today: https://events.linuxfoundation.org/open-networking-edge-summit-north-america/

Industry Support for Flege

Advantech
“Advantech is pleased to be part of the Linux Foundation Fledge 1.8 project along with our solution partner, Dianomic,” said David Liu, director of IoT solutions and strategic alliances at Advantech. “Our company vision is to ‘Enable an Intelligent Planet.’ Open source application stacks for an industrial transformation, along with our rugged hardware, help complete that vision. As a leader in IoT intelligent systems and embedded platforms, we strive every day to better assist partners and customers in connecting their industrial chains through IoT hardware and software solutions with edge intelligence. The field-tested Fledge solution will play a key part in our continued efforts to co-create advanced solutions for a wide range of industries in the Industrial IoT.”

Dianomic 
“Dianomic and OSIsoft were pleased to contribute the FogLAMP code to seed the Linux Foundation’s Fledge project for the Industrial IoT Edge.”  said Tom Arthur, CEO Dianomic.  “This first release of Fledge 1.8 is a mature, field-tested solution already operating in power generation, power transmission & distribution, water & wastewater processing, discrete manufacturing, mining and professional auto racing. We invite manufacturers, equipment suppliers, system integrators and partners to join our community as we grow THE open source application stack for industrial transformations.”  

FLIR 
“For more than 40 years, FLIR thermal imaging has provided technologies for industrial users to improve their capabilities and safety on the job,”  said Chris Bainter, Director Global Business Development.  “Partnering with Dianomic we deployed our Ax8 and 300 series cameras using Fledge in energy substations and wastewater plants. Fledge easily and successfully integrated our sensor’s video, IR video and temperature reading outputs into our client’s existing operational, maintenance and safety systems. Fledge proved to Flir the future of open source for industrial 4.0 applications has arrived.”   

Nexcom 
“NEXCOM is proud to support FLEDGE from the Linux Foundation, establishing a growing line of preloaded and edge-enabled industrial gateways.” said Alexander Su, “The pre-configured products include the NIFE 105 for fixed assets, and the VTC 1910 targeted at transportation related use cases. In addition, NEXCOM has contributed code to the Linux Foundation supporting FLEDGE southbound plugins for CAN 2.0,  J1708 and J1939, to provide real-time monitoring for fleet management. The MVS2623 with Coral intelligence, provides a powerful purpose-built gateway combining the flexibility of FLEDGE with the strength of Google’s Edge TPU, better enabling edge use cases like real-time object detection from IP or USB cameras.”

Nokia 
Janne Parantainen, head of technology, Nokia Digital Automation said: “We run Fledge 1.8 on our edge platform bringing the benefits of optimized wireless communication to the industrial protocol domain and enabling new use cases across multiple industries. Deployed as part of our Nokia Digital Automation Cloud, it offers a way to transfer legacy industrial protocol data to new solutions. Nokia Digital Automation Cloud provides 5G-ready, reliable wireless connectivity, industrial applications and industrial ruggedized devices for addressing Industry 4.0 needs” www.dac.nokia.com

OSIsoft 
“OSIsoft’s  PI System is the most trusted source of real-time operational data. We enable the collection, standardization, contextualization and federation of large volumes of industrial, operational data.“  said Richard Beeson, CTO OSIsoft. “Fledge solves the diversity and complexity issues when collecting and processing data beyond the process control network.  OSIsoft recommends all our industrial customers and partners begin their IIoT journey by integrating Fledge into their industrial 4.0 deployments and asks them to join our growing community.”  

Rovisys  
“As an Operation Technology (OT) solution provider that is actively venturing into the world of Industrial AI, RoviSys sees value in using Fledge to collect manufacturing and IIoT data from the plant floor, including connecting to historians and cloud-based advanced data analytic platforms.”  said Bryan DeBlois, Director of Industrial AI RoviSys.  “Furthermore, commercially supported FogLAMP enables us to implement vibration analysis, apply machine learning models and detect anomalies to predict quality, improve maintenance, and monitor setpoints.  This helps our customers minimize downtime and maximize production efficiencies across their entire operation.”

TQS Integration
“With Fledge, industrial manufacturing now gets the technology needed to acquire datasets from sources that had previously not been able to cross the threshold of traditional cost-benefit analyses. Fledge is uniquely placed to solve data collection on the edge, and within existing process control networks, providing customers the flexibility to apply Industry 4.0 technologies with their entire infrastructure,” said Tom Quilty, director of Technology for TQS Integration. “With Fledge, we can advance our customer’s ability to maximize their current investments, maximize the value gained from IIoT devices and accelerate time-to-value for Industry 4.0 applications.”

WAGO 
“WAGO, a technology leader of industrial control and interconnect products, strives to be the backbone of a smart connected world.  This backbone is created  through constant innovation and empowered connections with our customers and industry partners.  Technologies like the Linux Foundation’s Fledge 1.8, and partners like Dianomic help our customers realize their true potential and expand on what is possible in an industrial control system.   The WAGO 750 Series has millions of units installed globally and supports applications with over 300 IO modules and more than 16 industrial fieldbus protocols offered.  Leveraging WAGO with Linux & Docker capabilities  provides the means to  add IIoT platforms like Fledge and benefit from all that Fledge offers to simplify cloud integration, management, and orchestration. Employing WAGO for ease of field wiring, data collection and/or control tasks while using the IEC 61131-3 PLC runtime and integrating it with the possibilities of Fledge creates a powerful platform for a smart connected world.”

ZEDEDA
“The most successful organizations going forward will have a model strongly rooted in an open philosophy that facilitates interoperability and agility, and the industrial market is no exception,” said Jason Shepherd, VP Ecosystem, ZEDEDA. “Dianomic’s FogLAMP offer is tailored to the unique needs of industrial customers and their open source foundation hosted in LF Edge helps customers mitigate lock-in and focus on value creation rather than reinvention. We look forward to working with Dianomic within our growing ecosystem to address critical business needs for industrial customers.”

About the Linux Foundation
Founded in 2000, the Linux Foundation is supported by more than 1,000 members and is the world’s leading home for collaboration on open source software, open standards, open data, and open hardware. Linux Foundation’s projects are critical to the world’s infrastructure including Linux, Kubernetes, Node.js, and more.  The Linux Foundation’s methodology focuses on leveraging best practices and addressing the needs of contributors, users and solution providers to create sustainable models for open collaboration. For more information, please visit us at linuxfoundation.org.

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The Linux Foundation has registered trademarks and uses trademarks. For a list of trademarks of The Linux Foundation, please see our trademark usage page: https://www.linuxfoundation.org/trademark-usage. Linux is a registered trademark of Linus Torvalds.

Exploration and Practices of Edge Computing: Cloud Managing Virtualized Devices

By Blog, EdgeX Foundry

Written by Gavin Lu, LF Edge member, EdgeX Foundry China Project Lead and R&D Director in the VMware Office of the CTO

As an industry leader with vast experience and knowledge, Gavin has been writing a series of articles focused on edge computing. These articles are posted on his personal blog and are posted here with his permission. To read more content from Gavin, visit his website

Introduction to the Architecture of Pallas

The previous article introduced how to build and install virtualized devices, but did not touch how to manage large-scale virtualized devices from the cloud. This article introduces the architecture of Pallas to achieve the above goal.

Pallas is the second milestone of the project Asteroid after Ceres. In this release, the basic problems of cloud managing virtualized devices are solved:

  • The device-cloud connection is narrow and unstable
  • Large scale of devices
  • Serious security concerns, often forbidding any open ports

The main functions of the Pallas architecture are implemented by the device manager and the agent virtual machine. Its design key points are:

  • Adopt MQTT protocol suitable for narrow-band, unstable network connections
  • The device manager in the cloud adopts the design concept of typical Internet architecture, with multiple layers, micro-services, multiple buffers, and read-write separation
  • The device is automatically registered to the device manager, and the device initiates all connections and response happens in the cloud
  • Close all ports on the device, run without VPN / SD-WAN, cross public networks
  • Each device has a randomly created, globally unique and permanent ID

Installation requirements

  • vSphere Hypervisor is installed on the device.
    • Device agent
      • CPU: 1 x86-64 vCore
      • Memory: 512MB
      • Storage: 5GB
  • Device manager
    • CPU: 2 vCores
    • Memory: 8GB
    • Storage: 100GB
    • Network: Open ports 443 and 1883, the device is visible

Note: In order for the agent to work properly, the device requires at least vSphere Essentials Kit license, or apply for the Enterprise Edition 60-day trial using the method described in the previous article. 

Download and Installation

Download Pallas

The Pallas installation package can be downloaded from the Flings website of the VMware CTO office. You need to register a VMware community account in advance. The download package contains the device manager OVA, agent VM OVA and user guide.

Note: The download package provided on the Flings website is a technical preview, which does not include commercial support. It is recommended that you carefully read its installation and user guide before initialize the installation.

Install device manager

The way to install device manager is the same as the typical way to install an OVA of virtual machines, which can be completed in sequence by referring to the steps in the Pallas installation guide.

Note: Although device manager is packaged in OVA mode, it does not depend on any specific virtualization infrastructure or cloud platform. In an alternative, it can be converted from OVA to other formats, or install on any cloud platform that supports OVA format.

Install device agent

In order to simplify the process of installing device agent, it is recommended to use the virtual machine OVA instead of the binary package.

 
You can use OVF Tools to install OVA remotely, or leverage ESXi UI to install directly as below.

ovftool –acceptAllEulas –name=pallas_agent –datastore=DATASTORENAME -dm=thin –X:injectOvfEnv –powerOn pallas_agent_ubuntu.ova ‘vi://USERNAME:PASSWORD@ESXIHOST’

Configuration and Use

Configuration

Before you start using it, it is critical to configure the device agent. In order to ensure communication security, remember to modify /etc/vmware/pallas_agent/pallas_agent.conf file before encrypt the file in the following manner.
python3 /root/agent/install/encrypte_password.py YOUR-PASSWORD

If the device is connected to the cloud via WiFi or a telco carreir mobile network, the corresponding PCIe or USB NIC needs to be passed through to the device agent virtual machine. In this way, the device agent virtual machine can be registered to the device manager.

Use

After the device is registered to the device manager, you can perform CRUD-like operations on users, devices, and virtual machines like other ordinary management tools.

 
 
 
It should be noted that because the communication protocol of metadata between the device manager and the device is based on MQTT, the status updates of the device and the virtual machine on top of it are completed asynchronously. If you don’t find a task completed in “real time”, you may need to wait for a while or refresh the status.
 
For tasks such as deploying a virtual machine or patching a device, large files are downloaded via HTTPS and auto resuming.
 
To complete all functions
 above, there is no need for mutual IP visibility between the manager and the device, nor the installation of any VPN or SD-WAN. The device can also be safely behind a firewall, NAT, or gateway.
 
 
With the support of these basic functions, it is easy to expand, manage large-scale virtualized devices from the cloud, and deploy edge applications like EdgeX Foundry framework on them. In the workshop on EdgeX Foundry China Day in December 2019, we have demonstrated the deployment of edge applications based on EdgeX Foundry framework with cloud management of virtualized devices.
 
 

Next

The previous two articles described how to build and install virtualized devices, and how to manage virtualized devices from the cloud. 

In the preface, in addition to virtualization devices, another solution is containerized devices.

In fact, the use of containerized equipment is very common, and it often implies local orchestration, cloud operation and maintenance.

  • Local orchestration means that single-point failures of devices cannot be handled well. Even the most common deployment approach of EdgeX Foundry is to deploy core container instances of microservices on one single device.
  • Cloud operation and maintenance means managing containerized devices from the cloud. Most manufacturers have their own specialized solutions, which brings another problem of technology fragmentation.

The solutions to these two problems will be discussed in subsequent chapters. The next article will introduce a cloud managing containerized device solution to solve the problem of fragmentation.

EdgeX Foundry Device Actuation from the Cloud

By Blog, EdgeX Foundry

Written by Jason Bonafide, EdgeX Foundry Contributor and Principal Software Engineer at Dell Technologies

EdgeX Foundry is a platform that serves as middleware in edge computing – serving between physical sensing and actuating devices and our information technology (IT) systems. Edgex’s interoperability enables communication between real world devices with simplicity in mind.

EdgeX Foundry is composed of several interoperable service layers. The layer that we will focus on in this tutorial is called Device Services Layer. The role of a Device Service is to connect “things” (sensors and devices) into EdgeX. For those looking to establish communication between devices and perform actions on conditional system-state, this tutorial is for you!

At Dell Technologies, we wanted to establish bi-directional communication between simulated devices on the edge (in an isolated network) with EdgeX Foundry. This enabled us to deploy a single up-to-date EdgeX Foundry cluster in VMWare’s One Cloud. This would speed up the process in bootstrapping systems on the edge which can showcase the variety of protocols supported by EdgeX. Demonstrating this flow, is the goal of this tutorial.

Tools and Technologies

While this tutorial aims to suit the needs of a variety of setups, below are used in this tutorial:

System Overview

Figure A contains the following components:

  • MQTT Device Service: Application which connects our Temperature Sensor to EdgeX.
  • Temperature Sensor: Simulated MQTT device on the edge.
  • EdgeX Foundry: EdgeX Core Services which handle the device readings, data, and actuation.

Device Overview

EdgeX Foundry’s MQTT Device Service leverages 3 topics when integrating a device with the platform:

  • Device-list Protocol Topic: This topic is used by MQTT Device Service for invoking a command on the device. In our example, we refer to this topic as the CommandTopic. This configuration can be modified at toml.
  • Driver IncomingTopic: This topic is by MQTT Device Service for receiving data, and publishing the data to core-data for persistence. This configuration can be modified at toml.
  • Driver ResponseTopic: This topic is used by core-command in receiving responses from the device actuation. This configuration is can be modified at toml.

Simulated Temperature Sensor Controller Device

  • Publishes temperature every 5 seconds to DataTopic.
  • Subscribes to CommandTopic which contains commands from edgex-core-command.
  • Publishes response for inbound command to RepsonseTopic.

This application used to simulate a temperature sensor can be found here.

Defining Device Profiles

As a pre-requisite to configuring the MQTT Device Service, we will need to define the Device Profiles for the devices.

A Device Profile defines the device’s values and operation methods (Read or Write). The device values and operation methods are essential in defining the “what” and “how” we can begin to tell EdgeX Foundry how it can interact with our devices.

Each Device Profile contains the following sections:

  • Identification: fields which pertain to the identification of a Device Profile.
  • DeviceResources: specification of sensor values within a device which may be read from or written to either individually or as part of a deviceCommand.
  • DeviceCommands: defines access to read and writes for simultaneous device resources.
  • CoreCommands: specifies the commands which are available via the core-command microservice.

Temperature Sensor Device Profile

# Identification properties
name: “TemperatureSensor”
manufacturer: “Generic”
model: “MQTT-123”

# Labels that we can use for filtering especially when invoking endpoints throughout the microservices.
labels:
– “temperature”
– “sensor”
– “controller”
– “mqtt”
description: “Simulated temperature sensor controller device”

# The Sensor is a simple one which only provides read-only access to its constantly updating temperature value.
deviceResources:
– name: temperature
description: “Sensor temperature value”
properties:
value:
{ type: “string”, “readWrite”: “R” }
units:
{ type: “string”, readWrite: “R” }

# Commands that we are concerned with in regards to interacting with the device.
deviceCommands:
– name: temperature
get:
– { index: “1”, “operation”: “get”, deviceResource: “temperature” }

# Defining of endpoints within core-command that we can use to interact with the sensor.
coreCommands:
– name: temperature
get:
path: “/api/v1/device/{deviceId}/temperature”

# 200 response with the temperature value in the response.
responses:
– code: “200”
description: “Get the temperature”
expectedValues: [ “temperature” ] – code: “500”
description: “internal server error”
expectedValues: []

Configuring MQTT Device Service

EdgeX Foundry offers an MQTT Device Service in which we will configure for our devices.

Host Configuration

While we intend to communicate with our device on a local network, we will still want to configure the Host for device-mqtt-go to be localhost. Later on in this tutorial, we will talk about port-forwarding to this process.

Each system may look different as to where you can find EdgeX and how you may connect to it. Be sure to update the Host and Port configuration properties for the clients. The device service will need to talk to some Core EdgeX Services.

Device Configuration

We leverage [[DeviceList]] to create our pre-defined Temperature Sensor.

In this section, we flesh out the device’s metadata.

  • Name: TemperatureSensor
  • Profile: TemperatureSensor
  • Description = ‘Simulated MQTT Temperature Sensor device’
  • Labels = [ ‘MQTT’, ‘Temperature’, ‘Sensor’ ]

Next we define MQTT protocol configuration:

  • Schema: tcp
  • Host: [MQTT Borker Host] – In my case, this points to our eclipse mosquitto instance in the Kubernetes cluster.
  • Port: [MQTT Broker Port] – In my case, this ports to the expose NodePort for eclipse moquitto.

Driver Configuration

Other than general MQTT configuration, which will need to point to the eclipse-mosquitto instance, you may or may not need to update the IncomingTopic and ResponseTopic. The example we use in the tutorial, uses the default configuration values provided within the example of the Device Service.

  • IncomingTopic: DataTopic – topic in which our device will push temperature value to.
  • ResponseTopic: ResponseTopic – topic in which we will publish the response from the command invocation.

Finalized configuration.toml

IP Addresses have been redacted and should be modified to better fit your scenario.

# Turning the log-level to DEBUG so that we can capture publish/subscribe actions
[Writable] LogLevel = ‘DEBUG’

# Configuration for the device MQTT service:
# Set the Host my machine’s IP address
# Leaving the defaults for the remaining configurations.
[Service] BootTimeout = 30000
CheckInterval = ’10s’
ClientMonitor = 15000
Host = ‘localhost’
Port = 49982
Protocol = ‘http’
StartupMsg = ‘device mqtt started’
Timeout = 5000
ConnectRetries = 10
Labels = [] EnableAsyncReadings = true
AsyncBufferSize = 16

# We are not using the Registry within this example
[Registry] Host = ‘localhost’
Port = 8500
Type = ‘consul’

# Using defaults
[Logging] EnableRemote = false
File = ”

# Configure clients for the other microservices:
# Pointing at the EdgeX Deployments in the VMWare One Cloud.
[Clients] [Clients.Data] Protocol = ‘http’
Host = ‘k8s.cluster’
Port = 48080

[Clients.Metadata] Protocol = ‘http’
Host = ‘k8s.cluster’
Port = 48081

[Clients.Logging] Protocol = ‘http’
Host = ‘k8s.cluster’
Port = 48061

# Configuration for the device:
# Ensure that ProfilesDir is pointing to the directory which the device profile configrations reside.
[Device] DataTransform = true
InitCmd = ”
InitCmdArgs = ”
MaxCmdOps = 128
MaxCmdValueLen = 256
RemoveCmd = ”
RemoveCmdArgs = ”
ProfilesDir = ‘./res/lf-edge’
UpdateLastConnected = false

# Pre-define Devices:
# Temperature Sensor and AC Fan devices.
# Configured to point at MQTT broker in the Cloud.
# Using CommandTopic as the topic which will handle actuating the devices.
# Configure automated events on the temperature Device Resource
[[DeviceList]] Name = ‘Temperature Sensor’
Profile = ‘TemperatureSensorProfile’
Description = ‘Simulated MQTT Temperature Sensor device’
Labels = [ ‘MQTT’, ‘Temperature’, ‘Sensor’ ] [DeviceList.Protocols] [DeviceList.Protocols.mqtt] Schema = ‘tcp’
Host = ‘k8s.cluster’
Port = ‘1883’
ClientId = ‘CommandPublisher’
User = ‘admin’
Password = ‘public’
Topic = ‘CommandTopic’
[[DeviceList.AutoEvents]] Frequency = ’20s’
OnChange = false
Resource = ‘temperature’

# Driver configs:
# DataTopic is the topic the Device Service will use to provide to Core Data.
# Reference MQTT Broker in the Cloud.
# ResponseTopic is the topic which the Device scripts will use to communicated responses on command invocations.
[Driver] IncomingSchema = ‘tcp’
IncomingHost = ‘k8s.cluster’
IncomingPort = ‘1883’
IncomingUser = ‘admin’
IncomingPassword = ‘public’
IncomingQos = ‘0’
IncomingKeepAlive = ‘3600’
IncomingClientId = ‘IncomingDataSubscriber’
IncomingTopic = ‘DataTopic’
ResponseSchema = ‘tcp’
ResponseHost = ‘k8s.cluster’
ResponsePort = ‘1883’
ResponseUser = ‘admin’
ResponsePassword = ‘public’
ResponseQos = ‘0’
ResponseKeepAlive = ‘3600’
ResponseClientId = ‘CommandResponseSubscriber’
ResponseTopic = ‘ResponseTopic’
ConnEstablishingRetry = ’10’
ConnRetryWaitTime = ‘5’

Router Port-Forwarding

Given a scenario where EdgeX Foundry is deployed in the cloud, and our devices are on a local network, one option is to leverage port-forwarding our your router.

In my scenario, EdgeX Foundry exists in VMWare’s One Cloud while my MQTT Device Service and device simulations reside on my local home network. While it is not recommended for this setup on a home network (for security purposes), I am going to use my home network and configure port-forwarding on my router to demonstrate this flow for similar environments. This will allow me to register my MQTT Device Service within EdgeX Foundry using my public IP address.

With the help of port-forwarding, I can configure my router to forward all requests to http://[PUBLIC IP]:49982 to the machine which is running the MQTT Device Service on port 49982.

The flow demonstrated in Figure B assumes ingress/egress routing supports communication between both entities.

Actuating MQTT Devices from the cloud

Before diving in, here are the host and port configurations I will use to access EdgeX:

  • edgex-core-data: k8s.cluster:30800
  • edgex-core-metadata: k8s.cluster:30801
  • edgex-core-command: k8s.cluster:30802

Earlier, we’ve configured MQTT Device Service to run on localhost on a machine within a local network. If your setup is similar to mine, this will not be accessible from a cloud environment. Fortunately, we can use core-metadata’s API to modify the URLs at which the Device Service can be accessed from the cloud. Since device-mqtt-go is still running on localhost with port-forwarding configured, the Device Service can be accessed by EdgeX in the cloud.

Let’s get the Device Service’s Addressable details in effort to capture this device information we will use to update some routing information.

# Invoking core-metadata

curl –location –request GET ‘k8s.cluster:30801/api/v1/addressable’

This will yield a response similar to:

[
{
“created”: 1594771598214,
“modified”: 1594771598214,
“origin”: 1594771598226,
“id”: “0da6eda1-fad9-41b6-a1c3-c50aab4679f8”,
“name”: “edgex-device-mqtt”,
“protocol”: “HTTP”,
“method”: “POST”,
“address”: “localhost”,
“port”: 49982,
“path”: “/api/v1/callback”,
“baseURL”: “http://localhost:49982”,
“url”: “http://localhost:49982/api/v1/callback”
}
]

Now lets use the previous response body and update the following fields to reference our network’s public IP: – address – baseUrl – url

Note that [PUBLIC IP] is used in place of your the IP address that you will use when routing to your network

# Invoking core-metadata

curl –location –request PUT ‘k8s.cluster:30801/api/v1/addressable’ \
–header ‘Content-Type: application/json’ \
–data-raw ‘{
“id”: “0da6eda1-fad9-41b6-a1c3-c50aab4679f8”,
“name”: “edgex-device-mqtt”,
“protocol”: “HTTP”,
“method”: “POST”,
“address”: “[PUBLIC IP]”,
“port”: 49982,
“path”: “/api/v1/callback”,
“baseURL”: “http://[PUBLIC IP]:49982”,
“url”: “http://[PUBLIC IP]:49982/api/v1/callback”
}’

At this point, the Device Service is routable from the cloud. Next, let’s get the TemperatureSensor device ID:

# Invoking core-command

curl –location –request GET ‘k8s.cluster:30802/api/v1/device/name/TemperatureSensor’

This will result in a response like this:

{
“id”: “7af6bad7-7c4f-408b-9a62-eb909e0aad4f”,
“name”: “TemperatureSensor”,
“adminState”: “UNLOCKED”,
“operatingState”: “ENABLED”,
“labels”: [
“MQTT”,
“Temperature”,
“Sensor”
],
“commands”: [
{
“created”: 1594771641016,
“modified”: 1594771641016,
“id”: “118cb3c7-3c1b-4088-bd88-7c27d304aba9”,
“name”: “temperature”,
“get”: {
“path”: “/api/v1/device/{deviceId}/temperature”,
“responses”: [
{
“code”: “200”,
“description”: “Get the temperature”,
“expectedValues”: [
“temperature”
] },
{
“code”: “500”,
“description”: “internal server error”
}
],
“url”: “http://localhost:48082/api/v1/device/7af6bad7-7c4f-408b-9a62-eb909e0aad4f/command/118cb3c7-3c1b-4088-bd88-7c27d304aba9”
},
“put”: {
“url”: “http://localhost:48082/api/v1/device/7af6bad7-7c4f-408b-9a62-eb909e0aad4f/command/118cb3c7-3c1b-4088-bd88-7c27d304aba9”
}
}
] }

We can extract the get command from the response for TemperatureSensor. This URL can be used to get the temperature value from the device itself.

Something worth noting is that the URL generated within the response above, uses the configured Host and Port values from core-command. Depending on your setup, you may need to invoke a different URL to access core-command. In my particular instance, I am exposing core-command via NodePort Service type. This means that core-command is accessible only through a port range allowed by Kubernetes. The port assigned to core-command is not the same as the port used within the cluster. With a load-balancer, ingress, or some proper network configuration, it could certainly be set up in such that the internal DNS names can be resolved.

# Invoking core-command

curl –location –request GET ‘http://k8s.cluster:30802/api/v1/device/7af6bad7-7c4f-408b-9a62-eb909e0aad4f/command/118cb3c7-3c1b-4088-bd88-7c27d304aba9’

response

{
“device”: “TemperatureSensor”,
“origin”: 1594773351741563527,
“readings”: [
{
“origin”: 1594773351741189868,
“device”: “TemperatureSensor”,
“name”: “temperature”,
“value”: “119.017532”,
“valueType”: “String”
}
],
“EncodedEvent”: null
}

We have now demonstrated bi-directional communication between devices on a local network and EdgeX Foundry in the cloud. While this is a simple demonstration, this flow can enable provisioning edge-device clusters which interact with EdgeX Foundry quickly. With an EdgeX instance deployed in the cloud, this flow (depending on networking), is portable enough to experiment with the different protocols EdgeX Foundry supports.

This tutorial is a start of what can be accomplished with EdgeX Foundry. We’ve walked through a simple flow where we can establish bi-directional communication between edge devices and EdgeX Foundry in the cloud. With all the supported protocols, it is rather simple to get EdgeX up and running with the the Device Service of your choice.

Visit the EdgeX Foundry website for more information or join Slack to ask questions and engage with community members. If you are not already a member of the community, it is really easy to join. Simply visit the wiki page and/or check out the EdgeX Foundry Git Hub.

State of the Edge and Edge Computing World Seeks to Recognize Women Shaping the Future of Edge

By Awards, Blog, State of the Edge

Written by Candice Digby, Partner and Events Manager at Vapor IO, a LF Edge member and active leader in the State of the Edge Project

As 2020 continues to surprise the world with new changes and challenges, the need for diversified leadership and tech innovation has never been more clear. In an effort to help promote and encourage progress in the edge industry, The LF Edge’s State of the Edge and Edge Computing World present the second annual Edge Woman of the Year Award.

 

The award recognizes leaders who have been impacting their organization’s strategy, technology or communications around edge computing, edge software, edge infrastructure or edge systems. The organizers encourage industry participants to nominate their colleagues, or for qualified women to nominate themselves. The “Top Ten Women in Edge” finalists will be selected by the organizers and the final winner will be chosen by a panel of industry judges. Finalists will be announced at Edge Computing World, being held virtually October 12-15, 2020. The Edge Woman of the Year will be announced on October 12th during the keynote session.

In addition to honoring the 10 semi-finalists and the ultimate Edge Woman of the Year, the organizations will also showcase the exceptional women who make up the advisory board, who are leaders in the industry themselves. Along with last year’s Edge Woman of the Year, Farah Papaioannou, Founder and President of Edgeworx, the 2020 advisory board includes:

  • Nadine Alameh, CEO, Open Geospatial Consortium
  • Samantha Clarke, Director of Business Development, Seagate Technology
  • Eliane Fiolet, Co-founder, Ubergizmo
  • Janet George, GVP Autonomous Enterprise, Oracle Cloud
  • Maribel Lopez, Founder and Principal Analyst, Lopez Research
  • Maemalynn Meanor, Senior PR, Marketing and Social Media Manager, The Linux Foundation
  • Carolina Milanesi, Founder, The Heart of Tech
  • Molly Wojcik, Director of Education & Awareness, Section
  • Michelle Davis, Manager, DoD/IC Specialist SA team, Red Hat

(Matt Trifiro, Farah Papaioannou, Gavin Whitechurch)

The Edge Woman of the Year 2019 award recognized Papaioannou for her outstanding impact on the edge computing industry and her multidimensional technology leadership, including venture capital, edge cloud computing, and open source projects. Now, she’ll join the impressive list of women choosing this year’s winner.

“It was an honor to acknowledge an exceptionally strong group of nominees last year, and we look forward to again recognizing those iterating on the edge computing technology in exceptionally creative ways this year,” said Gavin Whitechurch of Topio Networks and Edge Computing World. “It is imperative we take note of and acknowledge our colleagues leading the edge computing revolution, and we look forward to doing that with this year’s Edge Woman of the Year award.”

For more information on the Woman in Edge Award or to nominate someone, please visit http://www.edgecomputingworld.com/edgewomanoftheyear.

About State of the Edge

State of the Edge is an open source project under the LF Edge umbrella that publishes free research on edge computing. It is a Stage 2 project (growth) under LF Edge and is divided into three working groups: Open Glossary of Edge Computing, the Edge Computing Landscape and the State of the Edge reports. All State of the Edge research is offered free-of-charge under a Creative Commons license, including the landmark 2018 State of the Edge report, the 2019 Data at the Edge report and, most recently, the 2020 State of the Edge report.

About Edge Computing World

Edge Computing World is the only event that brings together users and developers with the entire edge ecosystem to accelerate the edge market & build the next generation of the internet. For 2020 the virtual event focuses on expanding the market, with new features including the Free-to-Attend Edge Developers Conference & the Free-to-End Users Edge Executive Conference.

LF Edge Update: Taxonomy, SIGs and Project EVE

By Blog, LF Edge, Project EVE

Written by Jason Shepherd, LF Edge Governing Board Member and VP Ecosystem ZEDEDA

I hope you and yours are doing well in these crazy times. Things are going great within the LF Edge community as we increase alignment across projects, fine-tune our processes and recently welcomed two new projects: Open Horizon and Secure Device Onboard. Net-net, more and more people by the day are joining in to grow an inclusive, structured community focused on developing an open framework for edge computing.

As a board member who is also involved in a number of the LF Edge working groups, I wanted to take this opportunity to provide an update on several fronts: the recently released LF Edge taxonomy white paper, the emerging Special Interest Groups (SIGs), and Project EVE.

LF Edge Taxonomy White Paper

Released last week, the community-created white paper outlining the LF Edge taxonomy and framework is an important piece that we believe will really help clear up a lot of market confusion by providing a balanced view of the edge landscape that is based on inherent technical and logistical trade offs spanning the edge to cloud continuum. This is compared to many existing edge taxonomies that break down the continuum using ambiguous terms that can be interpreted in different ways.  

The goal was to provide a universal framework for various industries to apply their preferred terminology on top of. We’ve received universally positive feedback in previews with key analysts and encourage you to check out both the paper and this related webinar that presents key insights.

LF Edge Vertical Solutions Focus Groups

With nine projects and the new taxonomy serving as a solid foundation, we’re now increasing focus on spinning up Vertical Solutions Focus Groups within the LF Edge community. These focus groups are a precedent set by CNCF and other Linux Foundation projects. The purpose is to document unique requirements for specific markets and feed desired features back into the LF Edge project working groups for consideration as part of their roadmaps. Doing this across as many use cases spanning Industrial, Enterprise and Consumer markets will ensure that each project is maximizing impact while also recognizing inherent tradeoffs.  

Both member and non-member companies will be welcome to volunteer to lead a vertical, or join one already in flight. It’s a low time commitment and a great way to demonstrate thought leadership as an end user while making sure LF Edge projects are developing the right features and specific extensions for the verticals and use cases that matter the most to your company. Stay tuned for more details, including a virtual launch event in the late summer!

Project EVE Update

LF Edge projects are growing across the board and Project EVE is no exception. The EVE community is now approaching 50 unique contributors from organizations including ZEDEDA, Xilinx, Intel, Global Logic, Atomic, GE Research and Timesys and contributions are also growing at a steady pace.  

In terms of market focus, EVE is optimized for supporting IoT edge computing workloads at the “Smart Device Edge,” as defined in LF Edge taxonomy.  Edge compute nodes in this subcategory are characterized by two attributes: 1) being deployed outside of a physically-secure data center but 2) still having enough memory (approximately 256MB) to support application abstraction in the form of virtualization and/or containerization.

 

Devices at the IoT Edge are constrained, heterogeneous, and physically accessible, dictating that special attention needs to be made to optimize footprint, simplify support for diverse hardware, enable zero touch provisioning, and establish a zero trust security model that eliminates the guesswork in securing distributed edge computing nodes at scale. EVE builds on the principles of traditional virtualization tools optimized for the data center, but is optimized for the unique needs of the IoT Edge.

The chart below explains how EVE takes a balance of architectural approaches to serve as a holistic, open engine for supporting any IoT edge computing workload. The net is that the bare metal foundation enables deep security and networking capabilities, supports both containers and virtual machines to provide options for both modern and legacy workloads, and mitigates lock-in with its open API. 

Since launching as a founding LF Edge project in early 2019, the EVE community has been working hard to modularize the EVE foundation so developers can choose preferred components, ultimately wrapped up into a de-facto standard interface in the form of the open EVE API. 

As part of the community’s effort to increase modularity, support for ACRN and KVM hypervisors as alternatives to the original Xen baseline has been added. The project has adopted continerd given that it is the most common container runtime and a general tenet is to integrate leading OSS projects and standards wherever possible rather than reinventing. 

The community’s goals for the balance of 2020 include further increasing modularity and reducing footprint, and adding support for Kubernetes via K3S. Regarding the latter, this will be done by integrating the right features from the Kubernetes paradigm rather than simply trying to cut and paste the same functionality from centralized data centers to the necessarily different IoT edge. Join in if you’d like to help the community shape this important bridge from the IoT Edge to the data center paradigm! 

In terms of adoption, EVE is being leveraged as the edge computing foundation for deployments in several market verticals including oil and gas, renewable energy, manufacturing and healthcare. Check out the EVE in Market page for a growing list of community-supported images for hardware models from Advantech, Dell, HPE, IEI, Intel, Kontron, Lanner, Nexcomm, Raspberry Pi, Siemens, Supermicro and more! This page also has links to the OSS Adam and commercial controller offers that leverage the open EVE API.

Finally, thanks to the great work of Stefano Stabelini at Xylinx, among others, an image is now available for the Raspberry Pi 4 to make it even easier and cost-effective to get started with EVE! This image includes GPU support and can be used with the OSS Adam controller today. Stay tuned to “EVE in the Market” page for other controller options, or contribute your own!

The mission of the EVE community is to do for the IoT Edge what Android did for the smartphone. Learn more about EVE through the project page on the LF Edge site and in this EVE webinar in which I also highlight the importance of an open edge for realizing the true business potential of digital transformation. We welcome you to join the community to make EVE the one foundational stack needed to scale IoT edge computing deployments with choice of hardware, applications and cloud!

In closing, we have a lot of great things going on within the LF Edge community and we’re just scratching the surface of the opportunity ahead. Our future is bright and we encourage you to get involved, whether it be providing key market input through a SIG or diving straight in and contributing code. After all, LF Edge is a technical meritocracy and the best way to vote on the direction of a project is with fingers on your keyboard!

ZEDEDA is a LF Edge member and leader in Project EVE. For more details about LF Edge members, visit here. For more details about Project EVE, visit the project page

Other resources:

 

Calling all innovators!! You’re invited to compete in the EdgeX Foundry Challenge Shanghai 2020

By Blog, EdgeX Foundry

Written by Intel’s Ying J Lu, EdgeX Foundry Community Member

On July 3, the EdgeX Foundry Challenge Shanghai 2020 was successfully kicked off as a joint effort among EdgeX community members Intel, VMware, Dell Technologies, HP, Thundersoft, IOTech, Tencent, and Shanghai startup incubator Innospace.

Leaders from the Linux Foundation and LF Edge welcomed community members for a virtual kick-off of the EdgeX Challenge, aimed at building a learning platform for EdgeX Foundry ecosystem partners in China. This initiative enables development of open, scaled industry solutions. It brings together participants with in-depth industry knowledge and developers to identify use cases to solve top industry problems and build demonstrations that move toward an integrated commercial solution. So far, more than 16K people have tuned in to view the challenge kick-off.

Why is edge important?

In today’s data-driven landscape, the Internet of Things provides a number of sensors and terminal devices with a variety of protocols, creating complexity to integrate them into a unified platform. To address the increasing demand to introduce new workloads such as artificial intelligence at the edge, fuse data on customers’ premises and the interwork with different cloud service providers,  this and future EdgeX challenges will help to accelerate a community of practice for architecting modern solutions.

As the world’s learning open edge computing framework, EdgeX Foundry is well positioned to address the edge opportunities as well as its complexity. “Intel is committed to support development of EdgeX Foundry”, says Wei Chen, Vice President of the Intel IOT Group, “including active code contribution, strong evangelism, and active development within the open source EdgeX ecosystem. Intel is also supporting the EdgeX China Project, which specifically supports the EdgeX Foundry community in China.”

Intel has also been actively collaborating in the greater open edge ecosystem by introducing OpenVINOTM toolkits to accelerate AI at the edge, growing the Open Retail Initiative to create and drive adoption of data rich solutions in retail leveraging open source ingredients, and launching Edge reference implementations for Retail and Industrial use cases available at the Intel’s Edge Software Hub. All of these efforts focus on nurturing a healthy and strong edge compute ecosystem.

The Challenge Highlights

The EdgeX Challenge Shanghai is co-hosted by the Linux Foundation and Science & Technology Commission of Shanghai Municipality (STCSM). The goal is to create a space for collaboration, using state-of-the-art technology frameworks, such as EdgeX Foundry which is part of the Linux Foundation, to address business challenges related to commerce and industrial verticals.

There are two major tracks covering the following industries:

  • Commerce: Retail, banking, hospitality, education, smart home, healthcare, cities and campus
  • Industrial: Manufacturing, power, oil and gas, utilities

The Challenge contest consists of two rounds, before winners are selected. In the preliminary round, all participants are required to submit an ideation document to describe how EdgeX-based technical frameworks are used in conjunction with a relevant industry use case. Judges will then select ten use cases to compete in the final round. Each team must demonstrate and showcase their solution which will consist of an interview by the judge’s review committee. Three levels of prizes will be awarded to winning teams.

Challenge Timeline:

Join the Competition

Registration for the EdgeX Challenge Shanghai is open until July 20, 2020. All are welcome—system integrators (SIs), independent solution vendors (ISVs), original equipment manufacturers (OEM, developers, universities and research institutes—to join the challenge.

Register here by July 20, to join the EdgeX Challenge Shanghai.

To see the kickoff from July 3, visit the EdgeX Challenge Shanghai 2020 video challenge here.

Collaborate with the EdgeX Foundry community

Akraino’s Debut at China Mobile’s “Innovation 2020 Cloud Technology Week”

By Akraino Edge Stack, Blog

Written by Tina Tsou, Co-Chair of the Akraino TSC, and Su Gu, Senior Researcher with China Mobile

On June 17, China Mobile Science and Technology Association held the “Innovation 2020 Cloud Technology Week” forum, which officially opened a series of cloud related activities  that included product launches, lectures, networking opportunities and more. For example, there was an announcement of “NEST+” plan geared for external industrial ecological cooperation. The event theme was innovation and celebrated the collaboration, openness, and win-win of technology companies both big and small. 

The event was attended and viewed by more than 734,000 people ranging from academicians, scholars, thought leaders and industry experts. There was a lot of buzz around the 5G development and collaboration in the  innovation, 6G frontier, artificial intelligence, Internet of Vehicles, Internet of Things, and other fields. 

As an important part of this ecosystem, LF Edge was represented at this event through project leaders and members. LF Edge’s Tina Tsou, Co-Chair of the Akraino TSC and Enterprise Architect at Arm, was on-hand to host a workshop with China Mobile Technology (USA) about the trend of edge computing and LF Edge’s Akraino Edge Stack project.

Other member speakers include Dr Oleg Berzin, Senior Director at Equinix, Jason Shepherd, LF Edge Governing Board member, Project EVE leader and Vice President at Zededa and Tapio Tallgren, a member of the LF Edge Technical Advisory Council and Lead SW Architect at Nokia, to introduce their contributes to Akraino and share their views on MEC.

Joe Ward, CEO at EdgeVideo, Arif Khan,CEO at ParserLabs and China Mobile’s Su Gu, Senior Researcher, and Dr Jian Li also shared their views on Telco MEC and how to interwork with public clouds on MEC.

The “Innovation 2020 Cloud Technology Week” was a great success.  To learn more about Akraino Edge Stack, click here

 

Baetyl 2.0

By Baetyl, Blog

Written by Leding Li, Chair of the Baetyl Technical Steering Committee and Chief Architect at Baidu Cloud IoT

Baetyl, a Stage 1 (at-large) project under the LF Edge umbrella, seamlessly extends cloud computing, data and services to edge devices, enabling developers to build light, secure and scalable edge applications.  Today, Baetyl is thrilled to announce Baetyl 2.0, which features the long-awaited remote management system and support for the Kubernetes ecosystem.

A number of active contributors from the Baetyl community helped develop these new features to Baetyl, which brings Baetyl closer to its fundamental goal of creating a free and open edge computing platform.

Other Baetyl 2.0 features include:

  • A new remote management system called Baetyl-Cloud to support the management of multiple edge nodes.
  • The Edge and Remote Management system all evolve to Cloud Native model and are supported to run on both vanilla Kubernetes and K3S.
  •  A “declarative resource definition” design for edge-cloud synchronization through IoT device shadows.
  • An internal architecture upgrade to support future edge clusters.

We have always believed that a complete edge computing system should not only have the hosting capabilities to support applications and services running on a variety of devices, but also make developers be freed from insecure physical consoles, and that devices should be able to be operated and managed remotely in bulk, which is especially meaningful for devices that are about to be placed in remote, dangerous, or harsh environments. Remote management also combines edge computing together with existing cloud computing, allowing data to cross physical boundaries in the desired way, making application development and deployment more agile.

In order to ensure the cohesion of the code, we created a new repository for Baetyl-Cloud at https://github.com/baetyl/baetyl-cloud/. The first Baetyl-Cloud official release will provide a wide range of management capabilities by its OpenAPI:

  • Edge node management: support for multi-device group management, tag-based application synchronization, node information and application information collection and display.
  • Application deployment management: Supports deploying container applications, function calculations, and AI inference services by tag.
  • Configuration management: Supports management of nodes, functions, secrets, certificates, and container repository.
  • Batch management: Use a pre-prepared configuration to pre-install a large number of devices for out-of-the-box use.

Another important feature in Baetyl 2.0 is the Cloud Native support. We changed the underlying runtime of Baetyl from Docker to Kubernetes, and at the same time changed the way Baetyl main program is run, making it a container instance with administrative privileges running in Kubernetes. This change will bring many benefits to developers, including:

  • Updatable main program. In the original model, the Baetyl system itself needs to be updated manually or using the operating system package manager, which inevitably requires the operator to obtain a console. The new model considers “system updates” as part of Baetyl OTA, which will make edge devices can always keep in touch with the latest security update and bug fixes.
  • Multi-container applications that can be updated separately. In the original model, although each container is a completely independent service, the upgrade needs to be carried out together, and the operator cannot define the runtime dependencies between services. The new model leverages Kubernetes’ rich application definitions and enables each service to be independently deployed and upgraded, which will allow edge devices to have more diverse functions.
  • Future support for edge clusters. In the original model, limited to the capabilities of Docker, a Baetyl instance could only be deployed on a single device. The new model enables Baetyl instance to be distributed on multiple different work nodes by the orchestration capabilities of Kubernetes which can not only improve the total computing power, but also obtain higher availability.

Behind these new functions, we have also redesigned the communication protocol between Baetyl and Baetyl-Cloud, which combines the declarative resource definition style of Kubernetes and the device shadow mechanism of the IoT.

Declarative resource definition implements an idempotent distributed communication method, which ingeniously guarantees the consistency of resources in the entire distributed system. However, this method relies on high-quality network conditions. In edge computing scenarios with high latency, packet loss, and unscheduled network interruptions, a lighter communication mechanism suitable for unstable networks is needed.

For this reason, Baetyl-Cloud will convert the declaration of resources into the status expectation of the device shadow and continue to send notifications to Baetyl devices with MQTT message. Baetyl device decodes and uses the resource declaration and then reports the new device shadow status with MQTT message too. Through this method, we can always synchronize the cloud and the edge correctly under weak network conditions.

The above new features will be available immediately with the official release of Baetyl 2.0. Click here for more information.

Other resources for Baetyl include:

LF Edge Drives Cross-Ecosystem Collaboration — Publishes Industry-Defining White Paper on Multi-Functional Edge Computing, Adds Projects and Members

By Announcement

 

  • White paper, created collaboratively from across the LF Edge ecosystem, helps define open source edge computing across telecom, industrial, enterprise and consumer markets
  • Industry unification accelerates with the addition of the Service Device Onboard project, an automated “Zero-Touch” onboarding service to more securely and automatically onboard and provision a device on edge hardware
  • New members bring additional community expertise across smart IoT, software-defined data fabric, servers, and open cloud

SAN FRANCISCO – July 7, 2020 –  LF Edge, an umbrella organization under The Linux Foundation that aims to establish an open, interoperable framework for edge computing independent of hardware, silicon, cloud, or operating system, today announced continued ecosystem collaboration via a new collaborative white paper, “Sharpening the Edge: Overview of the LF Edge Taxonomy and Framework.” Additionally, LF Edge announced  a new project (Secure Device Onboard) and four new members. LF Edge welcomes General members High Peak Data, Jiangxing Intelligence, and Super Micro; and Associate member OpenStack Foundation.

Edge computing represents a new paradigm in which compute and storage are located at the edge of the network, as close as both necessary and feasible to the location where data is generated and consumed, and where actions are taken in the physical world. The optimal location of these compute resources is determined by the inherent tradeoffs between the benefits of centralization and decentralization. 

In collaboration with the Open Glossary project to align ecosystem terminology, the LF Community created a white paper entitled “Sharpening the Edge: Overview of the LF Edge Taxonomy and Framework” to introduce the key concepts of edge computing. Additionally, the paper highlights emerging use cases in telecom, industrial, enterprise and consumer markets. The paper also provides details of eight LF Edge open source edge projects. The paper will be available for download following a webinar presentation on Thursday, July 9 at 9:00 am PT. Register for the webinar, “Demystifying the Edge with the new LF Edge Taxonomy and Framework” here: https://zoom.us/webinar/register/WN_icv5h6wFTcuw9O0xvMpgLw.

“We are thrilled to see such strong cross-community collaboration within LF Edge and beyond,” said Arpit Joshipura, general manager, Networking, Edge & IoT, the Linux Foundation. “A diverse set of members from various companies came together to help define our unified approach to open edge computing, which is a key tenant of LF Edge. Concurrently, we welcome the Secure Device Onboard project and four new member organizations to the fold as we prepare for more edge computing milestones to come in H2.” 

Secure Device Onboard 

Secure Device Onboard (SDO), which joins LF Edge as a Stage 1 project,  is an automated “Zero-Touch” onboarding service. To more securely and automatically onboard and provision a device on edge hardware, it only needs to be drop-shipped to the point of installation, connected to the network and powered up. SDO does the rest. This zero-touch model simplifies the installer’s role, reduces costs and eliminates poor security practices, such as shipping default passwords.

A primary objective of Secure Device Onboard is to expand TAM for IOT devices.  To achieve this goal, a cross-industry collaboration of device manufacturers, distributors, systems integrators, cloud service providers, and device management software vendors is required to accelerate adoption.  The Linux Foundation is the ideal organization to facilitate this collaboration and accelerate adoption of this important technology and help accelerate adoption of devices into Home and Industrial ecosystems, helping drive the need for all of the current projects in the LFEdge community.

Initially released as open source software by Intel Corporation in February 2020, it’s based on Intel® SDO Version 1.7. The original Intel® SDO launched in September 2017 as a stand-alone Intel product reflecting the original SDO protocol and architecture specifications.  With the complex ecosystem needed for success of this product, Intel decided to open source and donate the core functions of Intel® SDO to the community in order to drive an industry standard, resolve key industry friction points, and allow the IOT market to grow faster.  

SDO  joins LF Edge’s other projects including: Akraino Edge Stack, BaetylEdgeX Foundry, Fledge, Home Edge, Open Horizon, Project EVE and State of the Edge. These projects support emerging edge applications across areas such as non-traditional video and connected things that require lower latency and faster processing and mobility. By forming a software stack that brings together the best of cloud, enterprise and telecom, LF Edge helps to unify a fragmented edge market around a common, open vision for the future of the industry.

What’s Next

Join LF Edge for a webinar presentation of the new white paper, July 9 at 9:00 am PT, entitled “Demystifying the Edge With the New LF Edge Taxonomy & Framework,” as part of the ongoing On The Edge with LF Edge webinar series. Presenters include LF Edge community experts Jason Shepherd, Vikram Siwach, and Matt Trifiro. Details and registration here.

LF Edge has just published a YouTube channel with easy access to the latest LF Edge webinars and presentations. Subscribe today and never miss a new video: https://www.youtube.com/channel/UCY7H1oSt8gvXNdXH9wrNq5Q

Register today to join the LF Edge community for the Open Networking and Edge Summit virtual experience, happening September 28-29. Details and registration here: https://events.linuxfoundation.org/open-networking-edge-summit-north-america/register/ 

Support from the Expanding LF Edge Ecosystem

Jiangxing Intelligence

Jiangxing Intelligence is committed to the development of advanced edge computing technology and application in the fields of smart IoT. Leveraging EdgeX Foundry as an advanced Open Edge Computing platform, Jiangxing has developed a series of products, which are successfully deployed in power grid, renewable energy and utility infrastructures. Jiangxing has established strategic partnerships with State Grid, China Southern Power Grid, Beijing Enterprises Water Group, China Unicom, China Tower, etc.

 “Jiangxing is looking forward to joining LF Edge to collaborate with the community and contribute to the world’s leading open interoperability platform for the global IoT Edge ecosystem,“ said Xiaoyi Fan, CTO of Jiangxing. “Jiangxing is a leading edge computing startup. The  industry does have a working system, but to make the system work best, and much better than their competitors, they need a lot of advanced techniques, and we can help them.”

OpenStack Foundation

“The LF Edge community offers strong synergies with both the OpenStack project, OSF software project communities, and Edge Computing Group,” said Ildiko Vancsa,  Ecosystem Technical Lead, OpenStack Foundation. “In fact, many contributors work actively across these communities. By working together more formally, these projects will more closely collaborate so that organizations deploying open infrastructure at the edge, the core or in between can do so with confidence that the two leading foundations in the space are supporting and streamlining the integration of technologies to solve their most pressing issues.”

Super Micro

“LF Edge harmonizes hardware & software blueprints for a variety of use cases including 5G, AI/ML, IaaS/PaaS,” said Srini Bala, Senior Director of Solutions at Supermicro (SMCI). As a global leader in enterprise computing, storage, networking solutions, and green computing technology, we are pleased to join LF Edge to collaborate with the Akraino community and contribute to open-source ecosystems.

About The Linux Foundation 

Founded in 2000, the Linux Foundation is supported by more than 1,000 members and is the world’s leading home for collaboration on open source software, open standards, open data, and open hardware. Linux Foundation’s projects are critical to the world’s infrastructure including Linux, Kubernetes, Node.js, and more.  The Linux Foundation’s methodology focuses on leveraging best practices and addressing the needs of contributors, users and solution providers to create sustainable models for open collaboration. For more information, please visit us at linuxfoundation.org.

The Linux Foundation has registered trademarks and uses trademarks. For a list of trademarks of The Linux Foundation, please see our trademark usage page: https://www.linuxfoundation.org/trademark-usage. Linux is a registered trademark of Linus Torvalds.

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