Bellevue, United States – ScaleOut Software introduces Version 2 of the ScaleOut digital twin streaming service with powerful new features for building digital twin models that meet the needs of real-world applications. With this release, developers can now create digital twin models in C# using .NET 6 for deployment on both Windows and Linux systems. Digital twin models also include new capabilities, such as timers for detecting missing messages from IoT devices and automatic initialisation of all digital twins from file-based data. This release also provides performance improvements in the Azure-based execution platform to harness the latest features in .NET 6.
The ScaleOut digital twin streaming service delivers innovative, technology that uses the digital twin model to implement streaming analytics in live systems. This release builds on Version 1’s comprehensive feature set, which integrates machine learning into digital twins using Microsoft’s ML.NET library, provides intuitive business rules to build digital twin models, and integrates with Microsoft’s Azure digital twins.
“We are pleased to release the second major version of our digital twin streaming service with exciting new features for developers,” says William Bain, ScaleOut Software’s CEO and founder. “Digital twins have the potential to significantly boost situational awareness for a wide range of mission-critical applications. We believe this release will further accelerate adoption of digital twins in applications that track live systems with many data sources.”
New features and benefits of the ScaleOut digital twin streaming service, Version 2
Version 2 introduces new capabilities for digital twins that address the requirements of real-world applications. Digital twins can now provide more comprehensive support for tracking data sources in a wide range of live, mission-critical use cases, including healthcare IT, physical security systems, logistics operations, disaster response, telematics, and more. New capabilities include:
- Integrated timers to improve digital twin alerting: Developers can now create timers that trigger code execution. These timers enable digital twins to detect missing or delayed messages from data sources and signal alerts when needed. This capability is important in live applications that must identify failed or unreliable devices, such as smoke detectors and security sensors.
- Aggregate Initialisation of digital twin applications: Users of the ScaleOut digital twin streaming service can now create and initialise digital twins using file-based data. They can optionally supply a .csv file to the service’s UI when a model is deployed for this purpose. In Version 1, digital twins were automatically created when messages arrived from their data sources. This feature enables early detection of unresponsive data sources.
For more information, please visit Scaleoutsoftware and follow @ScaleOut_Inc on Twitter.
- Version 2 of ScaleOut digital twin streaming service blog post
- ScaleOut digital twin streaming service product page
- Azure digital twins integration blog post