IoT is bridging the IT–OT divide rapidly. Data is no longer just under the purview of IT. Smart and connected devices, which are under the purview of OT, enable data collection, control and actuation, and enable additional IT-centric applications. The need to collect, store, and analyze data in a cost-efficient and timely manner means that IT and OT architecture and operations models need to converge and coexist. Software-defined OT (SD-OT) and IT–OT convergence are part of an “Intelligent Edge." Converged IT/OT Systems minimize data transfer between the core and edge, and carry out OT and IT functions seamlessly. SD-OT moves OT functions into the software running on industry-standard hardware. OT control and data acquisition functions are network-based and can be performed from the Core or anywhere at the Edge. Converging IT and OT means running IT and OT software on the same core and edge infrastructure tier and possibly on the same physical hardware.
This is an excerpt from an IDC Perspective posted on idc.com on the topic of SD-OT and Intelligent Edge. Link here.
Firms embark on Digital Transformation (DX) Initiatives by embracing a data-driven, analytics-first approach to improve business processes and increase operational efficiencies, better understand customer behavior and preferences, and build deeper customer, supplier and/or partner relationships, and more importantly, be prudent about how they gain insight from the data they collect. Collectively, this results in lower operational costs and higher revenue. Customers can consumers or businesses. In other words, DX initiatives can be B2B (business-to-business) or B2C (business to consumer).
The Internet of Things (IoT) is a key DX initiative. It enables firms to obtain valuable insights from data collected via networks of connected devices (beyond computers, laptops, and smartphones). IoT enables firms to digitize and better control the "things" they rely on to conduct business. IoT is replacing the Industrial Internet. Before the advent of the industrial internet (which is a precursor to IoT), information technologies (IT) and operational technologies (OT) lived in two different worlds:
- (Enterprise) Information technologies are the entire spectrum of technologies for information processing, including software, hardware, communications technologies, and related services. IT is designed to provide business services and mostly operates out of a centralized information aggregation, processing, and dissemination facility known as the datacenter.
- (Enterprise) Operational Technologies (OT) on the other hand are hardware and software technologies that detect and/or create change by the direct monitoring and/or control of physical devices, processes and events. OT is designed to provide operational services and insight, and is placed on the "shop floor", alongside machinery and equipment, in autonomous vehicles, smart cities, a smart grid, a wind turbine, retail stores, in the field or in the supply chain.
Pre-IoT IT and OT had little incentive to comingle. They were owned and operated by two different sets of resources. OT infrastructure has always been outside the IT domain. IT has never appreciated the nuances of OT systems. In fact, in many IT environments, OT equipment and data are perceived to be a risk when interfacing with a company’s Core IT systems and network. The data sharing is therefore limited, unidirectional and mostly transactional (from the OT Edge to IT i.e. from the “shop floor” to the business).
IoT is bridging the IT-OT divide rapidly. Data is no longer just under the purview of IT or OT. While OT has been collecting detailed operational data for as long as IT, it was just mostly isolated to the plant or field. Smart and connected devices – which are under the purview of OT - enable additional data collection, assimilation, and control, which is analyzed and fed back by IT to OT. There is a need to collect, store and analyze data in a cost-efficient and timely manner. This means that IT and OT architecture and operations models cannot be independent of each other. They must converge and coexist. The convergence is the spilling over data and insight from one side of the gap to the other. This convergence has led the industry to recast the boundaries for IT and OT. It has enabled IT and OT to comingle their data and system. It has led to a tiered data-centric model, known as "Core-Edge-Endpoint".
The Edge consists of an IT Edge and OT Edge, each with separate infrastructure design. An "Intelligent Edge" combines the two “Edges” together. In other words, it is designed to carry out OT and IT functions seamlessly without the need for separate infrastructure. It brings about IT-OT convergence with a common infrastructure that can address both IT and OT requirements. A converged and intelligent IT/OT Edge is capable of hosting IT apps and OT systems and software on a common infrastructure layer, enabling a seamless Core-Edge-Endpoint IT-OT infrastructure.
Note: Intelligent Edge and Smart Edge are interchangeable. In this document, we use the term Intelligent Edge.
Moving OT functions onto a converged tier requires making much of it software-defined. Software-defined OT (SD-OT) moves OT functions into software running on industry-standard hardware, which can access or even host OT control systems. Alternatively, OT-related control and data acquisition functions are network-based, and can be performed from the Core or anywhere in the Edge. With SD-OT, the OT software, like IT software, can run on bare-metal on virtual machines, and increasingly inside application containers. This makes it easier for the firm to integrate OT functions with developer frameworks, and the software with cloud infrastructure frameworks like OpenStack and platform orchestration frameworks like Cloud Foundry and OpenShift. As a part of their IoT initiative, they can fully shift their development burden from hardware to software.
Vendors like HPE are now taking the concept further by introducing Converged Edge Systems - converged IT/OT systems that enable firms to build an Intelligent Edge. Converged Edge Systems are ruggedized general-purpose systems that are built with datacenter-grade industry-standard computing hardware and integrate OT functions such as control and data acquisition systems. Since many of the IT functions such as data analytics require significant computing resources, Converged Edge Systems must be built with space and power efficient hardware that provides:
- Connectivity: Includes high-speed data acquisition connectivity from sensors wired or wirelessly, and data transfer to another Edge tier or the Core for further processing.
- Compute: Enables an appropriate level of compute – either datacenter grade or low power compute – for performing data acquisition and analytics.
- Actuation and Control Hardware: Host action and control OT hardware to control such as robotic arms, autonomous cars, conveyer belts, and wind turbines.