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Home Edge Eucalyptus (vE) Release Enhances Home Data Privacy and Adds Android Support

By Blog, Home Edge, Project Release

Home Edge—an open source edge computing framework for home devices—is now available in its Eucalyptus (vE) release. Home Edge, an LF Edge project, is a robust, reliable and intelligent home edge computing open source framework and ecosystem running on a variety of devices in the home. To accelerate the deployment of the edge computing services ecosystem successfully, the Home Edge Project provides users with an interoperable, flexible, and scalable edge computing services platform with a set of APIs that can also run with libraries and runtimes.

“I am excited to share the availability of vE version of Home Edge on Github,” said Suresh L C, Home Edge Technical Steering Committee (TSC) Co-Chair. “The new Home Edge release adds Android execution support with a secure, robust and end-to-end framework for intelligent service offloading in smart home scenarios, which in turn provides data privacy with low latency response.”

The vE release adds a number of significant new features, among them are

  • Open Source Security Foundation (OpenSSF) Badge
    • Home Edge has achieved the OpenSSF best practices Gold badge and the OpenSSF scorecard has also been integrated. Go-Project is made compliant by incorporating necessary documentation/quality fixes.
  • Data synchronization to Cloud endpoints – MQTT
    • Independent MQTT based cloud synchronization mechanism as enhancement to vD
    • API’s to send and receive data from and to between Service application and Cloud via Home Edge
    • MQTT broker would be configured at the cloud (Cloud agnostic)
    • Home Edge acts as MQTT client to exchange data 
    • TLS secure mode for all the data exchange
  • Platform enhancement
    • The support for the execution of Home Edge on Android has been added to Home Edge Android
    • The base code currently supports device/service discovery and service offload to Linux device
    • Service offload to Android from Linux is not supported in this release
  • Dependent bot integration
    • Bot to check on the updates on dependent libraries has been integrated
    • The bot has been configured to run once every month in the first week
  • Code enhancements
    • Fixed TxT Record parsing as per mDNS protocol
    • Refactored service list assignment logic TxT record
    • Modified get score API from GET to POST in line with API design rules
    • API to add/delete events from database based on event ID added for DataStorage
    • Code coverage increased by adding more test cases
    • Modified response for Ping request to Pong
  • Auto numerical tagging of code when significant changes are incorporated

Learn more about these and other features of Home Edge vE release in the release notes.

What’s next

For the next steps, the community will work on strengthening the Android version of Home Edge so that the features are in line with the Go version.

If you are using or evaluating Home Edge, please let the project TSC know and join the TSC meetings. Your feedback on the project is greatly appreciated!

November 11, 2022

Edgex Foundry Goes Full Message Bus With Its Latest EdgeX 2.3 “Levski” Release

By Blog, EdgeX Foundry, Project Release
EdgeX Foundry now fully embraces decoupled message bus communication within the platform

I am delighted to announce today the availability of the EdgeX Foundry 2.3 release which is codenamed Levski. This is the project’s 11th official release since its inception in 2017 and includes some significant new features and benefits to users that I’ll explain in this blog.

Having been elected as the chair of the EdgeX Technical Steering Committee (TSC) earlier this summer, it’s great to be able to announce the news of this release but it really is the technical expertise and dedication of the EdgeX development team that helps bring these releases to the wider community. Thanks again for everyone’s effort here. Great to be part of a group of many different companies and individuals working together to make great open source edge software.

What is Levski?

First let me give mention to the Levski codename. As you may know, each EdgeX release is named after a certain place or location in the world, with the specific place chosen each time significant contributors to the project. This version was named by two long term EdgeX contributors, Diana Atanasova and Malini B

handaru, both from VMware. For version 2.3 and the letter “L”, we come back over to Europe because Levski is a large mountain in the beautiful European country of Bulgaria. Bulgaria is also Diana’s homeland so it’s nice to be able to recognize that with the naming of this release.

New in EdgeX 2.3 – More about the Message Bus

Perhaps the biggest single new feature is the enhancement to support the delivery of commands via the EdgeX message bus.

We’ve previously made great strides in EdgeX V2 by delivering data from the southside (from devices and sensors) to the northside (to the core and application layers) via an internal message bus. This release also adds the support in the other direction, i.e., from the northside (the application layers and core layers) down to the southside (the devices and sensors) on the same message bus. Previously the southbound communication was exclusively via REST. Moving to support message bus-based communication in both directions is a big advancement and brings key benefits in terms of reduced latency and increased scalability. The asynchronous communication and the QoS-based control that you get from the message bus implementations that you can choose adds delivery guarantees and retransmissions of messages as needed.

Message Bus

More Run-Time Data

Another key area of development for Levski has been the focus on providing EdgeX users with more live information about how the system is running. EdgeX 2.3 adds System or “Control Plane” Events that can provide live updates as to what is happening. For example, users can receive notifications that new devices are added or that there has been a network disconnection from a specific device.

Somewhat related to System Events are the Telemetry Metrics. In contrast to events though, the metrics provide numeric information relating to how the platform is operating. Examples include the number of data readings that are persisted by core data or the number of secrets or tokens that are stored. Building of what was delivered previously, Levski adds more metrics across all of the services.

All of this information can be collected and reported however the user sees fit. In addition, the System Events and Telemetry Metrics mechanisms are available for users to add their own metrics as needed.

Many other updates and enhancements

There are many other new additions in this last release cycle including:

  • Availability of NATS as alternative implementation of the internal EdgeX Message Bus. NATS is a popular and lightweight protocol with native delivery of EdgeX messages and potential advantages in high availability (HA) use cases
  • Authenticated access to the MQTT message bus
  • Securing of the Consul registry service with access tokens
  • Passing status at the Open Source Security Foundation (OpenSSF)
  • Initial construction of the EdgeX STRIDE threat model
  • Improving the EdgeX development process with a new Use Case Requirements (UCRs) phase in the design procedure

See the release notes here for full details of what the Levski release provides.

New adopters and use cases for EdgeX

Running as a mature, stage 3 Linux Foundation project, there are now many users and adopters of EdgeX technology around the world. That includes users who download and deploy the open source EdgeX code, but also users of commercial products (including ours at IOTech) that are based on EdgeX. Take a look at some of the companies who are users of EdgeX. There are also a good set of presentation videos from different adopters of the technology.

One of my personal aims as TSC chair is to help encourage the adoption and wider use of EdgeX. Thanks to Building System Integrators (BSI) who recorded a talk at a recent TSC meeting. It would be great to hear from more companies who would like to do something similar. Please do reach out to me to arrange it.

What’s coming next?

Each release marks a busy period where of course we finalize the current version, but already we are looking forward at what we can achieve in the next release. Codenamed Minnesota and expected to be version 3.0, we are looking to add new features to help with the scalable configuration of EdgeX. Tune into the Minnesota technical planning conference that we are running next week where we will scope out what we can do. As always, attendance and contributions are very welcome.

Thanks again to everyone who had a hand in this release, and we look forward to more successful releases in the future.

November 9, 2022

eKuiper Issues 1.7.0 Release, Adding Lookup Table, Analytic Functions and More

By Blog, eKuiper, Project Release

eKuiper—a lightweight IoT data analytics and streaming software—is now available in its 1.7.0 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 1.7.0 continues to improve the expressiveness of the rules by providing the lookup table, updatable sink, and more SQL syntax and functions. The 1.7.0 release adds a number of significant new features, among them are

  • Stream batch combined computation
    • Not all data changes frequently, even in real-time computation. In some cases, you may need to supplement stream data with externally stored static data. For example, user metadata may be stored in a relational database, and the stream data only has data that changes in real time, requiring a connection between the stream data and the batch data in the database to enrich the data. In the new version, eKuiper adds the new Lookup Table concept for binding external static data, which can be joined with stream data in the rules to realize the operation of stream-batch combination. Additionally, with the support of updatable sink, eKuiper can process CDC data and update the batch storage.
  • Enhanced analysis capabilities
    • Analytic functions refer to functions that perform state-related analysis by saving state, allowing users to complete some of the common stateful calculations without complex time windows or custom functions. In the new version, we have added the Partition By syntax to the analytic functions, allowing users to perform partitioned stateful calculations based on the dimensions defined by Partition By clause. We also added a new analysis function latest to get the latest value of data. It is used to collect unstructured data whose columns are not fixed and can be automatically stitched to calculate the complete data.
  • Expanding the connectivity ecosystem 
    • On one hand, we continue to add built-in and extended source/sink by adding Httppush source, which allows users to push data to eKuiper via HTTP protocol; adding built-in Redis lookup source, which supports using Redis as external lookup table; adding Influx V2 sink, which supports writing to InfluxDB 2.x version. At the same time, Memory, SQL, and Redis source are adapted to support lookup tables; Memory, SQL, and Redis sink are adapted to be updatable.
  • Enhance the Ops experience
    • The new release refactors the external connection configuration API to enable easier connection resource management. Another major update comes from the bulk import/export and initialization of streams and rules to facilitate the migration of eKuiper instances.

Learn more about these and other features of eKuiper’s 1.7.0 release in the release notes.

What’s next

In the next release, the community will work on enhancing graph API to support more nodes, such as switch node and script node, to provide a more powerful and easy-to-use rule pipeline composing tool. A new function to run tensor flow lite model will be provided to easily integrate with AI models. Check out the evolving Github 1.8.0 milestones and we welcome you to add your wisdom.

November 9, 2022
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