As if You Need Another Challenge, the IoT Will Change IT Operations Management

Your next challenge, should you choose to accept it, is to integrate the Internet of Things into your daily operations management. It’s not a project for the faint of heart.

As more and more devices get Internet-enabled, our dependence on connectivity will only continue to increase. Consumer, commercial and industrial applications of the IoT are getting even more diversified and an ever-expanding assortment of services are filling the pipeline.

According to IDC, worldwide spending on the overall IoT will reach $772B this year – and solution providers hope to profit from the IoT goldmine going into the new year. The retail, healthcare and industrial/supply chain industries will likely see the greatest growth. Manufacturing alone will account for $189B of the spending.

Forrester Research has predicted the IoT will become “the backbone” of customer value as it continues to grow. IT organizations are recognizing the business benefits of bringing intelligence closer to the end customer. Organizations will be pushed to the edge with IoT data and will require advanced analytics and machines to help manage it.

According to Forbes’ Top 8 IoT Trends for 2018, this year will be more of a steady (rather than explosive) growth period for the IoT. It will see lots of investment, growth and widespread adoption in a few major industries. But it will also see some growing pains – “fragmentation frustration,” potential data breaches and security issues galore.

That sound you hear is the other shoe dropping – IT operations management teams will continue to be held accountable for predictable service delivery, even as they ramp up to support the growing needs of the IoT, industrial Operational Technology (OT) environments, the intelligent edge and the underlying cloud and other infrastructure.

Finding the right partner can help smooth the road. According to CRN’s 10 IoT Predictions for 2018, in 2017, vendors started to flesh out their channel strategies for IoT as they realized that IoT essentially requires an ecosystem play.

For example, in edge computing, sensors and other connected devices collect and analyze the data locally, alleviating the dependence on cloud or Internet connectivity in specific situations where information needs to be processed quickly, reliably and securely.

So let’s not confuse managing IoT with dropping these devices into your Configuration Management Database, although that may happen over time. The point is that IoT is creating enormous pressure on the service application, not just because of the sheer number of devices but because of the nonstop, dynamic nature of their use.

The trend makes it increasingly necessary for service providers to get even better at managing larger volumes of data and speedily determining where and why service interruptions occur. The need to guarantee uptime and predictable service performance is paramount to maintaining SLAs and keeping customers satisfied.

As a result, your IT operations management provider needs to not only discover IoT devices but also understand the complex relationships between IT infrastructure and IoT applications.

The traditional approaches of infrastructure management that largely depend on centralized servers can rapidly get overwhelmed by the impositions driven by the confluence of these new trends. Furthermore, centralized systems have the potential to become bottlenecks. When centralized servers handling large amounts of information go down, entire service delivery systems can be affected.

Potential solutions include the move to a more decentralizing paradigm that moves some tasks and activities to the edge of the network, distributing the overall workload across multiple infrastructure elements. This leads directly to the evolution of fog computing models where IoT hubs manage groups of devices on the edge, and multiple cloud based servers take on monitoring and analytical responsibilities.

Another rapidly evolving approach is the development of mesh-based infrastructure architectures that inherently eliminate single points of failure and improve fault tolerance.

Either way, the challenges for IT operations management continue to evolve. The volumes of data to be managed are set to increase exponentially, and the expanding size of the infrastructure brings additional challenges of scale in terms of monitoring, analysis and effective remediation.

The need to rapidly assimilate vast amounts of data, intelligently perform analysis, determine root cause, remediation steps and affected business service impact will only continue to become increasingly important as we venture into this brave new world of IoT-based infrastructure.

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