OT, or operational technology, is the practice of using hardware and software to control industrial equipment, and it primarily interacts with the physical world. OT includes industrial control systems (ICSs) like programmable logic controllers (PLCs), distributed control systems (DCSs), and supervisory control and data acquisition (SCADA) systems.
OT environments supervise physical processes such as manufacturing, energy, medicine, building management, and ecosystems within other industries.
OT stands in contrast to IT, or information technology, which deals with data systems. While OT systems are primarily used to interact with the physical world, IT systems are primarily used to solve business problems for end users, such as service providers in telecommunications. In short, OT networks communicate with physical machines, and IT networks deal with information and data.
The Internet of Things (IoT) refers to the process of connecting everyday physical objects to the internet—from common household objects like lightbulbs; to healthcare assets like medical devices; to wearables, smart devices, and even smart cities. Some even come with their own apps, but all come with diverse use cases. These IoT-enabled devices are connected to and receive and transfer data over wireless IT networks, potentially with the help of a datacenter, with limited human intervention.
A subsection of IoT, the Industrial Internet of Things (IIoT) refers to connected devices that are used in manufacturing, energy, and other industrial settings. IIoT is commonly associated with OT and is significant for bringing more automation and self-monitoring to industrial machines. Combined with edge computing, IIoT helps manufacturers solve problems faster by transforming operations, assisting end users in making business decisions, and making plants more productive.
It’s also common to hear IIoT systems discussed in connection with Industry 4.0, or the Fourth Industrial Revolution. Both terms mean the same thing, and concepts like artificial intelligence and machine learning (AI/ML), machine-to-machine communications, and big data are closely linked to Industry 4.0.
Many aspects of OT and IT environments–including the use of IoT and IIoT devices–are converging as OT systems are more commonly connected to networks, and, with a new level of bandwidth, are able to generate and use increasing volumes of data.
The IT-OT convergence is related to the rise in edge computing. Edge computing (as opposed to cloud computing) involves shifting computing resources toward the physical location of either the user or the source of the data, like data analysis that takes place on a factory floor.
As part of this convergence, software that’s traditionally been the realm of IT teams is now also used in support of OT processes and can be accessed by OT networks.
More industries are adopting underlying technology platforms that can unify disparate data systems—ones used by both the business side and the operations side. This is a significant change for industrial processes that have traditionally been isolated from other systems.
Under these unified systems, businesses have new opportunities to use data to improve efficiency. For example, manufacturing sites can deploy AI/ML model training for quality control and predictive maintenance. Scalable service platforms mean applications like these can be deployed uniformly across multiple locations.
Traditionally, OT security meant ensuring the security, safety, and functionality of physical machines and tasks across multiple locations and within an OT network. IT security focuses on maintaining privacy across the retrieval, storage, and transmission of data. Today, integrating OT and IT networks introduces new digital technologies to factory operations, but it also opens them up to potential cyber threats.
OT devices that might once have worked in isolation are now connected to IT networks and solutions like the cloud, servers, and baseline security measures like firewalls. These new levels of connectivity enable benefits such as remote access controls and automatic system upgrades, but they also can be gateways for hackers to gain access to computer systems and introduce new threats to stability and uptime.
Cybersecurity measures must be integrated throughout the entire infrastructure, application stack, and life cycle. OT used in critical infrastructure—everything from water systems to transportation and power plants–should adopt sensible security strategies to reduce the risk of cyberattacks like malware and other vulnerabilities.
A layered, defense-in-depth approach offers multiple security controls by tapping into each layer in your environment, including operating systems, container platforms, automation tools like Kubernetes, Software-as-a-Service (SaaS) assets, and cloud services. This ensures both the simplest computer worms and other complex computer viruses like ransomware are monitored and addressed early in an automated way.
Hybrid cloud is an IT architecture that incorporates workload portability, orchestration, and management across multiple environments. This can include OT environments that are integrated with a public cloud or private cloud infrastructure.
Hybrid cloud solutions can provide a common foundation for OT and IT. Hybrid environments, with an embrace of open source software and modern software development practices, support flexibility and interoperability across systems.
In an OT environment with hundreds or thousands of pieces of connected equipment, a hybrid cloud model can enable real-time feedback and consistent management across a single control plane.
Hybrid cloud can help organizations introduce DevOps software development methods. Under DevOps, consistent tools and applications allow developers to deliver new capabilities across an entire enterprise at scale.
In practice, this means IT and OT teams can maintain consistent control, visibility, and management of hundreds to thousands of edge nodes in an industrial environment.