Ryan Budke, product manager—industrial IoT and edge platforms, Advantech: Modern edge controllers must balance two very different workloads: deterministic machine control and flexible software environments used for analytics, visualization and system integration.

A common architecture separates these responsibilities by allowing real-time control tasks, such as motion coordination or machine sequencing, to operate within a deterministic control environment, while higher-level workloads run within a Linux-based environment. Many platforms support isolating CPU cores, memory and network resources so that control loops maintain deterministic performance even while analytics or containerized applications run alongside them.

When combined with modular industrial I/O and high-speed fieldbus networks, this hybrid architecture allows machine data to flow directly from the control layer into edge applications for analysis or integration with enterprise systems.

The result is an edge platform capable of running real-time control and advanced data processing simultaneously without compromising determinism.

What cybersecurity mechanisms, such as secure boot, certificate management, encrypted communications and role-based access control, should be implemented?

Ryan Budke, product manager—industrial IoT and edge platforms, Advantech: Edge controllers increasingly sit at the intersection of operational technology networks and enterprise infrastructure, making cybersecurity a fundamental design requirement.

Modern industrial devices should support hardware-based security features such as TPM modules for secure key storage and hardware-accelerated encryption for TLS communications. Secure boot ensures that only authenticated firmware and operating systems can run on the device.

At the software level, edge platforms should support encrypted communications, certificate-based authentication and role-based access control for device configuration and management.

Because industrial systems often remain deployed for decades, long-term security maintenance is equally important. Edge platforms must support ongoing firmware updates, security patching and lifecycle management so machines can remain secure even as cybersecurity requirements evolve.

What are the advantages or disadvantages of an open or closed edge environment?

Ryan Budke, product manager—industrial IoT and edge platforms, Advantech: The debate between open and closed edge environments largely comes down to long-term flexibility.

Closed systems can simplify deployment initially, but they may restrict the ability to integrate new analytics tools, communication protocols or third-party applications. In contrast, open industrial platforms built on standard operating systems and containerized environments allow manufacturers to adapt their systems as new technologies emerge.

This flexibility becomes increasingly important as edge computing expands beyond traditional automation into areas such as AI, machine vision and predictive maintenance.

An open architecture allows deterministic control systems, modular industrial I/O and high-performance edge computing to work alongside a wide range of analytics frameworks and enterprise platforms. Rather than locking users into a single ecosystem, open platforms allow different technologies to coexist and evolve over the lifetime of the machine.

For many manufacturers, this approach offers the best balance between reliability, security and long-term innovation.

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How do compute resources, such as CPU architecture, cores, RAM or storage, affect the ability to run analytics, vision or AI workloads locally?

Ryan Budke, product manager—industrial IoT and edge platforms, Advantech: The computational capabilities of an edge controller increasingly determine what types of applications can run directly at the machine.

Traditional PLCs were designed primarily for deterministic control logic, but modern manufacturing systems generate large volumes of sensor, inspection and process data. Processing this information locally requires multi-core processors, sufficient memory and, in some cases, GPU acceleration.

Applications such as machine vision inspection, ultrasonic testing or semiconductor packaging can produce high-speed data streams that must be analyzed in microseconds to detect defects or anomalies.

When these workloads run directly at the edge, close to the source of the data, manufacturers benefit from lower latency, reduced network traffic and faster decision-making. In many cases, combining high-speed data capture with powerful edge computing resources enables machine intelligence that would not be practical if the data had to be processed in centralized systems.

Why is it important to know which industrial communication protocols an edge controller natively supports and whether additional protocols be added through software or middleware?

Ryan Budke, product manager—industrial IoT and edge platforms, Advantech: Industrial environments rarely rely on a single communication standard. Machines often need to interact with a mix of legacy equipment, modern automation systems and enterprise software platforms.

For this reason, edge controllers should natively support a broad set of industrial protocols, including fieldbus networks such as EtherCAT, as well as Ethernet-based protocols and interoperability standards like OPC UA.

Native protocol support allows controllers to communicate directly with sensors, motion systems and PLCs while making machine data available to higher-level systems such as SCADA, MES or cloud platforms.

Equally important is the ability to extend protocol support through software or middleware. This flexibility allows the platform to adapt to new communication standards or integrate with specialized equipment without requiring hardware changes.

Ultimately, the most effective edge architectures treat the controller as a convergence point where machine control, industrial data and enterprise systems can interact seamlessly.

Tell us about one of your company’s state-of-the-art products that involves edge computing.

Ryan Budke, product manager—industrial IoT and edge platforms, Advantech: One of the most important shifts in industrial automation is the convergence of deterministic machine control, high-speed data acquisition and advanced analytics at the edge.

A good example is Advantech’s AMAX EtherCAT control platform, which combines real-time machine control with modular industrial I/O in a scalable architecture. EtherCAT enables deterministic communication with distributed I/O while maintaining the flexibility needed for modern edge applications.

In many systems, platforms like AMAX operate alongside high-speed data acquisition modules and industrial edge computers, allowing raw sensor data from motion systems, inspection equipment or high-speed test environments to move directly into edge computing resources for real-time processing.

By bringing deterministic control, high-speed data acquisition and powerful edge computing together, architectures like this allow manufacturers to perform signal processing, AI inference and advanced analytics directly at the machine, reducing latency and enabling more intelligent industrial systems.