BELLEVUE, WASH. — December 12 — ScaleOut Software today announces the first open-source release of its digital twin APIs and development workbench for its ScaleOut Digital Twins hosting platform. Digital twin APIs allow developers to build powerful applications for real-time monitoring and simulating large systems. The workbench enables fast development and testing of digital twin applications before deployment. To help accelerate the development of digital twin applications, ScaleOut Software is releasing these components as open source under the Apache 2.0 license. 

Going beyond product lifecycle management (PLM), which focuses on improving product design, digital twins enable important new capabilities for real-time monitoring and simulating systems with thousands of components. For example, they allow applications to analyze streaming data in real time instead of requiring offline batch analytics. They can also simulate large complex systems to improve design choices and decision making. Digital twins offer key benefits to data analysts and managers in a wide range of industries, including transportation, logistics, security, healthcare, disaster recovery, and financial services. 

“We are excited to open source our digital twin APIs and new development workbench so that application developers can easily use digital twins to create a new generation of applications,” said Dr. William Bain, ScaleOut Software’s CEO and founder. “These freely accessible software components should simplify and accelerate the development of digital twin applications and encourage community participation.” 

The ScaleOut Digital Twins platform uses highly scalable, in-memory computing technology to host thousands of digital twins for monitoring real-time data from IoT devices and other data sources, enabling real-time analytics that provides actionable results in seconds. The platform also runs large-scale simulations that aid in the design of complex systems, such as airline logistics and traffic control networks. 

Application developers use ScaleOut’s open-source APIs to build digital twin models for deployment on the ScaleOut Digital Twins platform. They can now use the open-source workbench to test application code built using these APIs and gain immediate feedback that shortens the design cycle. Once tested, developers can deploy applications on the platform to run at scale with thousands of digital twins. 

Key Features and Benefits for ScaleOut Software’s Digital Twin APIs and Workbench: 

• Easily Build Digital Twin Models: ScaleOut’s open-source APIs enable developers to build digital twin models in Java or C#. These models serve as templates for creating digital twins. The APIs employ standard, object-oriented design principles to simplify development and avoid the use of specialized or platform-specific techniques. 
• Easily Test Digital Twin Models: ScaleOut’s open-source workbench lets developers test their digital twin models for both real-time monitoring and simulation in the user’s native development and test environment. The workbench accelerates application development by avoiding the need to deploy models to the hosting platform during the development process. 
• Greater Ease of Access and Flexibility: Because ScaleOut’s digital twin APIs and workbench are freely available as open-source components, developers can download them at no cost and immediately start building digital twin applications. These APIs can also serve as the basis for creating digital twins that run on other platforms and provide cross-platform compatibility. 
• Enable High Performance: ScaleOut’s digital twin model simplifies hosting on scalable, in-memory computing platforms. In-memory hosting dramatically reduces latency when digital twins access state information or process messages for both real-time analytics and simulation. It also enables high processing rates that support the creation of thousands of digital twins. 

For more information, please visit www.scaleoutdigitaltwins.com and follow @ScaleOut_Inc on Twitter.  

Additional Resources: 

• ScaleOut Open Source APIs and Workbench Blog Post 
• ScaleOut Digital Twins Product Page 
• GitHub Repositories for Java and C# Open-Source APIs 

About ScaleOut Software 

Founded in 2003, ScaleOut Software develops leading-edge software that delivers scalable, highly available, in-memory computing and streaming analytics technologies to a wide range of industries. ScaleOut Software’s in-memory computing platform enables operational intelligence by storing, updating, and analyzing fast-changing, live data so that businesses can capture perishable opportunities before the moment is lost. It has offices in Bellevue, Washington and Beaverton, Oregon.  

Media Contact 

Brendan Hughes  

RH Strategic for ScaleOut Software
ScaleOutPR@rhstrategic.com
206-264-0246 

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Digital Twins Can Implement Both Streaming Analytics and Simulations

With the ScaleOut Digital Twin Streaming Service, the digital twin software model has proven its versatility well beyond its roots in product lifecycle management (PLM). This cloud-based service uses digital twins to implement streaming analytics and add important contextual information not possible with other stream-processing architectures. Because each digital twin can hold key information about an individual data source, it can enrich the analysis of incoming telemetry and extracts important, actionable insights without delay. Hosting digital twins on a scalable, in-memory computing platform enables the simultaneous tracking of thousands — or even millions — of data sources.

Owing to the digital twin’s object-oriented design, many diverse applications can take advantage of its powerful but easy-to-use software architecture. For example, telematics applications use digital twins to track telemetry from every vehicle in a fleet and immediately identify issues, such as lost or erratic drivers or emerging mechanical problems. Airlines can use digital twins to track the progress of passengers throughout an itinerary and respond to delays and cancellations with proactive remedies that smooth operations and reduce stress. Other applications abound, including health informatics, financial services, logistics, cybersecurity, IoT, smart cities, and crime prevention.

Here’s an example of a telematics application that tracks a large fleet of vehicles. Each vehicle has a corresponding digital twin analyzing telemetry from the vehicle in real time:

Applications like these need to simultaneously track the dynamic behavior of numerous data sources, such as IoT devices, to identify issues (or opportunities) as quickly as possible and give systems managers the best possible situational awareness. To either validate streaming analytics code for a complex physical system or model its behavior, it is useful to simulate the devices and the telemetry that they generate. The ScaleOut Digital Twin Streaming Service now enables digital twins to simplify both tasks.

Use Digital Twins to Simulate a Workload for Streaming Analytics

Digital twins can implement a workload generator that generates telemetry used in validating streaming analytics code. Each digital twin models the behavior of a physical data source, such as a vehicle in fleet, and the messages it sends and receives. When running in simulation, thousands of digital twins can then generate realistic telemetry for all data sources and feed streaming analytics, such as a telematics application, designed to track and analyze its behavior. In fact, the streaming service enables digital twins to implement both the workload generator and the streaming analytics. Once the analytics code has been validated in this manner, developers can then deploy it to track a live system.

Here’s an example of using a digital twin to simulate the operations of a pump and the telemetry (such as the pump’s temperature and RPM) that it generates. Running in simulation, this simulated pump sends telemetry messages to a corresponding real-time digital twin that analyzes the telemetry to predict impending issues:

Once the simulation has validated the analytics, the real-time digital twin can be deployed to analyze telemetry from an actual pump:

This example illustrates how digital twins can both simulate devices and provide streaming analytics for a live system.

Using digital twins to build a workload generator enables investigation of a wide range of scenarios that might be encountered in typical, real-world use. Developers can implement parameterizable, stateful models of physical data sources and then vary these parameters in simulation to evaluate the ability of streaming analytics to analyze and respond in various situations. For example, digital twins could simulate perimeter devices detecting security intrusions in a large infrastructure to help evaluate how well streaming analytics can identify and classify threats. In addition, the streaming service can capture and record live telemetry and later replay it in simulation.

Use Digital Twins to Simulate a Large System with Many Entities

In addition to using digital twins for analyzing telemetry, the ScaleOut Digital Twin Streaming Service enables digital twins to implement time-driven simulations that model large groups of interacting physical entities. Digital twins can model individual entities within a large system, such as airline passengers, aircraft, airport gates, and air traffic sectors in a comprehensive airline model. These digital twins maintain state information about the physical entities they represent, and they can run code at each time step in the simulation model’s execution to update digital twin state over time.  These digital twins also can exchange messages that model interactions.

For example, an airline tracking system can use simulation to model numerous types of weather delays and system outages (such as ground stops) to see how their system manages passenger needs. As the simulation model evolves over time, simulated aircraft can model flight delays and send messages to simulated passengers that react by updating their itineraries. Here is a depiction of an airline tracking simulation:

In contrast to the use of digital twins for PLM, which typically embody a complex design within a single digital twin model, the ScaleOut Digital Twin Streaming Service enables large numbers of physical entities and their interactions to be simulated. By doing this, simulations can model intricate behaviors that evolve over time and reveal important insights during system design and optimization. They also can be fed live data and run faster than real time as a tool for making predictions that assist decision-making by managers (such as airline dispatchers).

Scalable, In-Memory Computing Makes It Possible

Digital twins offer a compelling software architecture for implementing time-driven simulations with thousands of entities. In a typical implementation, developers create multiple digital twin models to describe the state information and simulation code representing various physical entities, such as trucks, cargo, and warehouses in a telematics simulation. They create instances of these digital twin models (simply called digital twins) to implement all of the entities being simulated, and the streaming service runs their code at each time step being simulated. During each time step, digital twins can exchange messages that represent simulated interactions between physical entities.

The ScaleOut Digital Twin Streaming Service uses scalable, in-memory computing technology to provide the speed and memory capacity needed to run large simulations with many entities. It stores digital twins in memory and automatically distributes them across a cluster of servers that hosts a simulation. At each time step, each server runs the simulation code for a subset of the digital twins and determines the next time step that the simulation needs to run. The streaming service orchestrates the simulation’s progress on the cluster and advances simulation time at a rate selected by the user.

In this manner, the streaming service can harness as many servers as it needs to host a large simulation and run it with maximum throughput. As illustrated below, the service’s in-memory computing platform can add new servers while a simulation is running, and it can transparently handle server outages should they occur. Users need only focus on building digital twin models and deploying them to the streaming service.

The Next Generation of Simulation with Digital Twins

Digital twins have historically been employed as a tool for simulating increasingly detailed behavior of a complex physical entity, like a jet engine. The ScaleOut Digital Twin Streaming Service takes digital twins in a new direction: simulation of large systems. Its highly scalable, in-memory computing architecture enables it to easily simulate many thousands of entities and their interactions. This provides a powerful new tool for extracting insights about complex systems that today’s managers must operate at peak efficiency. Its analytics and predictive capabilities promise to offer a high return on investment in many industries.

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BELLEVUE, WASH. — February 21, 2023 — ScaleOut Software today announces new device modeling and simulation capabilities for its ScaleOut Digital Twin Streaming Service. These capabilities extend the service’s ability to perform real-time analytics at scale using digital twins to track devices and other real-world data sources. Users can now simulate the behavior of these data sources using digital twins prior to deployment as a tool to evaluate design choices and improve decision-making. This offers several benefits to data analysts and managers in a wide range of industries, including telematics, logistics, security, healthcare, crime prevention, and financial services.

Going beyond product lifecycle management (PLM), which focuses on improving product design, ScaleOut Software’s new simulation capabilities using digital twins also can assist in developing real-time analytics applications. The streaming service now enables digital twins to both generate and analyze telemetry. For example, developers can model a fleet of trucks with digital twins that send telemetry to additional digital twins which implement real-time analytics for tracking the fleet, identifying issues, and evaluating performance. The streaming service also can record telemetry from live devices and replay it in simulation to assist in performing offline analytics.

“We are excited to extend the capabilities of our streaming service to harness digital twins for both simulation and real-time analytics,” said Dr. William Bain, ScaleOut Software’s CEO and founder. “By hosting digital twins using our highly scalable, in-memory computing technology, we enable our customers to simulate large systems with complex interactions and gain insights not previously possible.”

Managers can also use ScaleOut Software’s simulation capabilities to model thousands of interacting data sources and predict likely outcomes faster than real time. For example, they can model the effect of delays for an airline’s flight schedule within a multi-hour, forward-looking window to predict and mitigate impacts on passengers caused by weather and equipment issues. This predictive capability can assist in decision-making during real-time operations.

Key Features and Benefits for ScaleOut Software’s Digital Twin Simulations:

• Build Simulations at Scale: Now developers can construct simulations that model thousands of devices and other data sources. Fast, in-memory computing ensures high throughput and seamless scaling during simulations with built-in high availability.
• Model with Digital Twins: Developers can harness the popular digital twin model to describe various physical entities using a powerful but easy-to-use, object-oriented representation of each device or data source. The ScaleOut Digital Twin Builder Toolkit lets developers construct digital twin models in both Java and C#.
• Combine Modeling and Analytics: The ScaleOut Digital Twin Streaming Service now helps managers use digital twins to both analyze telemetry from real-world data sources and to model those data sources. This simplifies the creation of workload generators for evaluating real-time analytics. The platform also allows a single digital twin instance to both simulate a data source’s behavior and analyze its telemetry.
• Capture and Replay Live Telemetry: The streaming service can capture telemetry from live data sources and replay it in simulation. This capability streamlines workload generation for simulations and enables offline analysis of live scenarios.
• Make Predictions with Simulation: The streaming service can configure simulations to run faster than real-time. This aids decision-making for operational managers by enabling simulations to predict future events based on parameterizable scenarios.

For more information, please visit www.scaleoutsoftware.com and follow @ScaleOut_Inc on Twitter.

Additional Resources:

• ScaleOut Digital Twin simulations blog post
• ScaleOut Digital Twin Streaming Service product page

About ScaleOut Software

Founded in 2003, ScaleOut Software develops leading-edge software that delivers scalable, highly available, in-memory computing and streaming analytics technologies to a wide range of industries. ScaleOut Software’s in-memory computing platform enables operational intelligence by storing, updating, and analyzing fast-changing, live data so that businesses can capture perishable opportunities before the moment is lost. It has offices in Bellevue, Washington and Beaverton, Oregon.

Media Contact

Brendan Hughes

RH Strategic for ScaleOut Software
ScaleOutPR@rhstrategic.com
206-264-0246

The post ScaleOut Software Adds Simulation Capabilities to its Digital Twin Streaming Service appeared first on ScaleOut Software.