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Shifting towards computing at the edge

Last week, Microsoft announced that Azure IoT Edge is now generally available for release. This is a powerful addition to Microsoft's IoT portfolio that includes - Azure IoT Central, IoT Hub and a host of solution accelerators. 

Before we unpack the specifics of Azure IoT Edge, let's take a step back to understand why edge computing is critical. Here are a few key reasons that would support business needs,

  • Low latency especially in scenarios that require real-time responses and decision-making. For instance, in a pedestrian detection system, which cannot wait while the data is sent to the cloud, then make a decision and take action. Here the need is to base action on real-time analysis
  • Computing is based on available data instead of historical, business process data, or external data sources. This saves on bandwidth, unnecessary computing on the cloud, and privacy. For instance, shutting off a device based on threshold value is not dependent on location, device attributes, and allows for decisions to be made locally
  • Proprietary protocol protection through integration with a plethora of protocols that have been developed over the years. This is especially true in industrial scenarios. Computing at the edge helps in protocol adaptation and filters noise out of the data
  • Lack of reliable connectivity requires computing at the edge, storage and a forwarding mechanism. For instance, if there are deployments in remote locations where connectivity is not always on

A review of Azure IoT Edge

In this post, I will focus on key features that stand out above and beyond the standard set that is required for an edge product. First, Microsoft recommends that the minimum hardware requirement be 128MB memory, and support Windows and popular versions of Linux. In addition, there is zero-touch provisioning through Device Provisioning Service (DPS) and Automatic Device Management (ADM), this means there is no need for operator intervention, and the ability to manage thousands of devices remotely. 

Azure IoT Edge is open source and supports Docker-based containerization for all edge services. It also offers secure communication between IoT edge and IoT Hub, and provides original design manufacturers an option for device based security


M
icrosoft has also expanded its programming language support. In addition, it offers local storage for 'store and forward' and enables the development and deployment of custom functions.  

Here are a bunch of Azure IoT Edge features that I think stand out

  • Device twin, as the name suggests creates a mirror image of device attributes in the IoT hub. These twins have properties that are owned by the cloud or device, and methods for request-response messages. The device twin is a powerful concept that can be used for device management and querying device attributes 

  • Azure services to run on edge as containerized services. The Azure Stream Analytics, machine learning, and cognitive services can now be run on the edge. For instance, if information were to pass across two different devices, or if action were to be taken on sensor data beyond just a simple average,  machine learning service can be used. In addition, these services are all cloud managed, that is, they can be developed along the way, on the cloud and deployed as containerized services on the edge

  • Enabling development and test workloads as part of the CI-CD (Continuous Integration-Continuous Deployment) pipeline. This is a crucial feature in the world of IoT solution development, especially to mimic real devices in the field. Coupled with the device and module twins features, this will facilitate testing and deployment at scale

  • Edge Marketplace will help partners and developers to collaborate, share, and monetize edge modules. This is a good beginning towards building a rich ecosystem of pre-integrated and certified modules for industry-specific solutions

Edge computing is here to stay, and both, Microsoft and AWS have an edge solution and strategy. The IoT domain is truly multi-disciplinary and I expect to see the edge development community grow over the next few years. 


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