Microsoft has recently made some announcements regarding their Internet of Things (IoT) capabilities within Azure. These announcements coincide with the Hannover Messe Industrial Automation conference that was recently held. Microsoft’s news includes adding a new service called Azure Time Series Insights, additional connectivity platform support for OPC UA and OPC DA and Azure Stream Analytic support on edge devices. In addition to these new capabilities, Microsoft also announced a new SaaS-based IoT Solution called Azure IoT Central.
Azure IoT Central is a fully managed SaaS offering from Microsoft that aims to reduce the complexity of IoT solutions. Sam George, partner director for Azure IoT explains the benefits of Azure IoT Central as:
“IoT brings a new set of benefits for companies that want to keep an edge on their competition, it brings challenges too — IoT solutions can still be complex, and a shortage of skills makes it difficult for everyone to take advantage of this new innovation.”
Currently the service is not public, but interested customers and partners can sign-up to receive updates on the service at MicrosoftIoTCentral.com.
Microsoft is continuing to invest in their platform-as-a-service IoT Platform service as well. These investments include a new preconfigured solution in the Azure IoT Suite called the Connected Factory. This solution provides customers and partners with a reference application in order to get started.
One of the challenges that many customers face is bridging their existing investments in legacy protocols that are used to manage and monitor their existing SCADA investments. In order to address some of these connectivity challenges, Microsoft is enabling support for the OPC UA and OPC Classic specifications which are prevalent in industrial settings such as Power Plants, Manufacturing and Oil & Gas. Customers with heavy investments in industrial protocols, such as OPC, are likely going to need a field gateway solution in order to avoid reconfiguring their facilities to publish telemetry to the cloud. To bridge this need, Microsoft has partnered with Unified Automation, Softing and Hewlett Packard Enterprise to provide this functionality. For organizations looking to provide their own connectivity solution, Microsoft has contributed to the OPC UA .NET standard library which can be found on GitHub.
Once data has been collected from industrial facilities, it needs to make its way to the cloud for analysis. This analysis may include detecting anomalies, predicting future failures and equipment performance trends. In order for customers to identify anomalies and trends, Microsoft has launched a new service, in public preview, called Azure Time Series Insights. George describes the service as a way to:
“Provide a global view of data across various event sources so companies can quickly validate their IoT solutions and avoid costly downtime of mission-critical devices. It helps organizations discover hidden trends, spot anomalies, and conduct root-cause analysis in near real time, all without writing a single line of code through its simple and intuitive user experience.”
Customers can also integrate Azure Time Series Insights with other Azure services through a rich API.
Another investment that Microsoft has recently made is to its Complex Event Processing (CEP) technology called Azure Stream Analytics (ASA). Previously, ASA only executed in the cloud after taking in a real-time data stream from an Azure Event Hub or Azure IoT Hub. However, for use cases where organizations have occasionally connected devices, or have vast amounts of data to send to the cloud, this model may not address all requirements. In response to these customer needs, Microsoft has announced a private preview of Azure Stream Analytics on edge devices. Santosh Balasubramanian, principal program manager within the Azure Stream Analytics team at Microsoft, explains some of the benefits of this new capability:
“Azure Stream Analytics has enabled customers to easily deploy and scale analytical intelligence in the cloud for extracting actionable insights from the device-generated data. However, multiple IoT scenarios require real-time response, resiliency to intermittent connectivity, handling of large volumes of raw data, or pre-processing of data to ensure regulatory compliance. All of which could now be achieved by using ASA on edge device to deploy and operate analytical intelligence physically closer to the devices.”
Azure Stream Analytics on edge devices leverages the Azure IoT Gateway SDK and can run on both Windows and Linux operating systems.