Autonomous Systems Poised to Become the Norm in IT
This architecture enables several types of automation. Updates to sensors can be deployed on a policy-based method, enabling incremental updates to some sensors while testing an update or rapidly pushing emergency patches to especially vulnerable devices. Similarly, continuous integration and continuous deployment pipelines can be extended to deploying new features to edge devices, much as they currently do in data centers and cloud-based deployments. This kind of policy-driven automation is essential to keep pace with the expected growth in IoT devices and data.
Further standardization across the IoT field is also crucial for keeping pace with business needs. This extends beyond the need for standard data organization and transmission methods. For example, an IoT deployment may use several different connectivity technologies, such as WiFi, Bluetooth, and LTE, in its architecture. Luckily, many Standard Development Organizations (SDOs), such as the International Telecommunication Union, are working on standard protocols and systems to improve scalability, security, and device interoperability in IoT deployments. Standardization practices in these areas will help ensure new IoT architectures can be built to last.
Over the past several years, IoT adoption has grown. In August 2019, Gartner predicted that the total number of IoT endpoints will increase by 21% in 2020, to reach a total of 5.8 billion devices. The greatest number of endpoints will reside in the utilities and physical security sectors, with a total of 3.27 billion devices between them. Gartner predicts smart buildings, automotive and healthcare to be the sectors with the largest growth from 2019 to 2020. Although the expanding use of IoT systems is a testament to the business value of IoT, the technology faces adoption and execution challenges, some of which automation can address.
IoT Adoption to Drive Autonomous Systems
One challenge is how long it takes to implement an IoT system. In 2018, Gartner found that 75% of IoT implementation projects took two times longer than planned. Cost is also a major factor when developing IoT infrastructure, with many industrial applications costing millions of dollars to implement. Finally, there is simply a lack of expertise in IoT architecture. The technology and business applications of it are sufficiently new that enterprises often struggle to find a properly qualified architect to lead deployment. Implementing IoT devices can be a costly, uncertain undertaking. Part of the expense and unpredictability results from lack of automation. As automation practices become established, development and deployment-related costs will fall.
IoT developers and operations managers can expect to see a convergence of policy-driven configuration tools, which include both traditional data center as well as cloud- and edge-based deployments. Larger systems that encompass IoT, edge and data center resources will gain in importance. As with centrally housed resources such as servers and storage arrays, monitoring the state of such systems will be essential to ensuring reliable operations. Accordingly, monitoring tools that encompass IoT, edge computing and data center resources will become key. Also, expect to see widespread adoption of automated remediation, especially for edge devices.