IoT Device Management with AIOps.

Jul 5, 2021. By S V Aditya

Tweet Share Share

IoT Device Management with AIOps

The Internet of Things has emerged fast from a buzzword to a very real way in which machines communicate and operate to make our lives easier. Despite being a relatively new word, its origins have been in place for a long. It can even be called a modern take of SCADA - the Supervisory Control and Data Acquisition systems that handled information between production systems and controlled machine operations in industries. While such legacy systems are still widely used, this term has expanded to involve a host of new applications and devices that can power unique use cases. Moreover, modern technologies like edge computing have evolved their sub-spaces under the IoT banner with many varied and powerful applications. In todays blog, we discuss some of these use cases along with the challenges and the potential application of AIOps to help navigate them.

Before we get into the latest applications and the best hardware, let's talk about the devices still used in the industry. Physical devices are not recycled as quickly as software is - leaving a lot of legacy devices in place. These devices - like IoT sensors in manufacturing or CCTVs for security - are very limited in application and possess minimal capabilities. Usually, they are built for a single purpose only. However, as they are connected to the internet, they can be used in many ways - some of them potentially malicious. Here we come to the first challenge of IoT devices - weak security. One of the most common problems with IoT devices is that they are all left with their default passwords and protocols. This has led to malware like the Mirai(in 2016) or the Mozi(in 2021) capturing and controlling these devices to lead to DDoS attacks that brought down a major cloud provider's services. In addition to weak security protocols, these devices are also running on old firmware that has not been updated in years. Anyone who knows how important security updates on modern systems are can understand how important firmware updates are to a secure system. Each device from a different manufacturer also has its unique ecosystem that is incompatible with the others. Users have to manually configure and manage each device separately, leading to many issues like weak security protocols.

In the case of modern IoT devices with greater functionality, these are dependent on the cloud servers that they are connected to. Any errors in this network connectivity mean that these devices cannot function in any way. Take, for example, a webcam at a toll booth that is expected to read number plates from vehicles for automated toll payments. It sends the video feed to a cloud-based AI service that extracts the numbers from images and sends them to the toll both computers. Without the internet, this device becomes utterly useless. Moreover, these devices are very heavy on network resource consumption. In the toll booth example above, sending video data over the internet is costly in terms of data throughput. With this plethora of problems, scaling IoT device management has become extremely complicated - so much so that little or no ITOps time is spent on these - especially in legacy devices. However, AIOps offers a better alternative to ITOps teams.

Let's look at how these devices are managed with AIOps. Firstly, there are weak security protocols and firmware. AIOps in its Act mode can find the relevant settings to update passwords and other security protocols across devices with Deep Reinforcement Learning. This can be applied across thousands of devices single-handedly automating an entire chain of security protocols. AIOps can do more than basic password workflows. It can also handle device management activities like firmware updates with AIOps Engage + Act. In addition, deep reinforcement learning-powered workflows can react dynamically to different ecosystems and still configure the same result along with managing all the gateways, tools, and apps required to support these devices.

In modern IoT devices, AIOps shows great potential in combination with edge cloud technologies like KubeEdge. With KubeEdge and AIOps complementing each other, they can drive automated workflows, incident recognition, and auto-remediation to keep IoT devices a truly low-touch operation. Finally, AIOps provides tools to interact even with legacy systems to create a truly single pane of glass monitoring and management system for all IoT devices. This can have a great impact on many potential applications.

In the toll booth example, a KubeEdge cluster can run AI applications for text recognition natively using low-level devices at endpoints that service cameras in a small network - or in the camera application itself. AIOps can act as a software issue detector and auto-remediator for issues that cannot be handled by KubeEdge. As another sample use case let's consider the assembly line in a factory. A camera connected to a cloud server is supposed to inspect defects and remove them from the production line. IoT sensors are supposed to measure metrics like machine vibration, temperature, etc to aid in management. An AIOps+KubeEdge solution is incredibly powerful and can be implemented on these low-level devices for unique applications. Now, the assembly line can function without network connectivity, and can also bring in a new level of controls. For E.g. any shutdown in AI models at the system due to container issues can be rectified with a KubeEdge agent while an AIOps incident recognition can identify the root cause of the issue and run auto-remediation for system-level problems. In a more advanced application on modern systems, any edge device - like a mobile phone that functions as a barcode scanner in a delivery company - can have its software issues remotely managed with a lightweight AIOps agent while KubeEdge delivers software capability. The potential applications are endless but more importantly, the resource requirements are managed effectively. That is the future we can create with AIOps and IoT.

To learn more about IoT device management with AIOps, please contact us at

Share this blog.

Tweet Share Share