At Build
2017, Microsoft has outlined its plan to take Azure beyond the public cloud
towards the edge. Branded as Azure IoT Edge, this offering exploits the growth
in enterprise IoT and industrial automation.
During the
early days of Cloud Computing, the key differentiating factor of the providers
was the number of regions followed by the breadth of services. With the global
presence and a comprehensive set of services, Amazon has been enjoying the
attention and the leadership position in the industry. But the market dynamics
are changing rapidly, and the key competitors of AWS are moving fast. Global
footprint, broad service portfolio, rapid shipping cycles are the new norm in
the industry. Both Microsoft and Google are turning out to be serious
contenders giving stiff competition to Amazon. Microsoft’s recent updates to
Azure indicate its aggressive strategy to outsmart the competition.
Microsoft Azure[/caption]
In the
current context, the core IaaS offerings such as virtual machines, storage, and
virtual networks are table stakes. The real opportunity lies in delivering
intelligent solutions powered by Machine Learning and Artificial Intelligence
to enterprise customers. In scenarios such as industrial automation, this
intelligence layer needs to be closer to the devices reducing the latency. Many
use cases in the manufacturing and healthcare domains cannot afford the round
trip to the public cloud. Edge Computing emulates the public cloud capabilities
by bringing intelligence closer to the devices.
Though there
are a few offerings in the market, Microsoft’s Azure IoT Edge is the most
comprehensive solution for industrial IoT implementations. Azure IoT Edge is a
software that can run on both Microsoft Windows and Linux operating systems. It
supports x86 and ARM architectures making it possible to run on smaller devices
such as Raspberry Pi and BeagleBone. Developers can use a variety of languages
including C, Node.js, Java, Python, and C# to develop applications. Azure IoT
Edge delivers local device management while relying on the concept of device
twins to handle offline scenarios. When the connectivity gets established, all
the changes made to the edge will be automatically synchronized with the cloud.
Azure IoT Edge[/caption]
Azure IoT
Edge acts as a runtime to deploy multiple Azure services locally. Some of these
modules include Machine Learning, Stream Analytics, Functions, and IoT Hub.
Each module is packaged and deployed as a Docker container that runs on top of
Azure IoT Edge. Developers familiar with Azure can target the edge runtime with
no changes. The code snippets that run on Azure Functions will continue to run
on the edge. The SQL-like queries designed for Azure Stream Analytics will work
as is in Azure IoT Edge. The IoT Hub enables machine-to-machine communication
through familiar MQTT and AMQP protocols. Customers can seamlessly move the
code between the edge and the public cloud. The modular architecture based on
containers makes it possible for Microsoft to bring additional Azure-based
public cloud services to the edge gradually. The registered Edge devices can be
seamlessly managed from the same portal that customers use to manage their
public cloud assets.
Customers
will be able to build edge appliances powered by Azure IoT Edge easily. These
appliances can be deployed in shop floors, vessels, automobiles, airplanes, oil
rigs, and construction sites. OEMs may ship hardware appliances with
preinstalled Azure IoT Edge software.
Though Azure IoT Edge is designed for IoT use cases, it can be leveraged
by any data-centric application.
During AWS
re:Invent 2016, Amazon has announced AWS Greengrass and AWS IoT SDK, which are
the key components of its edge software. The devices are expected to run the
IoT SDK while specialized appliances will run AWS Greengrass. Like Azure IoT
Edge, AWS Greengrass supports x86 and ARM architectures. Since its
announcement, the service has only been in limited preview with access to
select customers and partners.
Based on the
currently available information, Azure IoT Edge seems to be complete than AWS
Greengrass. Microsoft has already demonstrated Azure IoT Edge running key
components including hot path analytics and machine learning. On the other
hand, AWS Greengrass includes a subset of AWS IoT and Lambda for essential
machine-to-machine communication and routing. It's not clear on how customers
can run Machine Learning models locally with Greengrass. Amazon has not
disclosed whether the edge service will support Kinesis, the streaming service
of AWS, which is essential for ingesting and analyzing the sensor data. AWS
Greengrass is expected to become generally available in a few months.
The
fundamental difference between AWS Greengrass and Azure IoT Edge is the
availability of the source code. Microsoft has made the source code of Azure
IoT Gateway SDK available on Github. This project will be eventually migrated
to Azure IoT Edge. It’s not clear whether AWS will open source Greengrass.
When
compared to AWS Greengrass, Azure IoT Edge seems to be comprehensive and
complete. Though Google and IBM are yet
to announce their edge computing strategy, they are expected to jump the
bandwagon.
Source: Forbes
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