Amanda Blevins

Internet of Things is no longer a buzz-phrase. It is a full-blown race in every industry to capitalize on the total addressable market trending towards $1 Trillion by the year 2021. The technology industry has not seen this type of opportunity in a long time, possibly ever. Internet of Things gives a chance to companies who have never been in the business of servers, network, security, cloud, data center, or internet to interrupt established companies in these previously dominated arenas. Many companies, large and startup alike, want to have the largest impact on the ecosystem first so others will follow the same design and implementation path.

I have mixed feelings about this boom in IoT. While the exponential technology improvements are exciting, it seems we are ignoring important factors in trying to create the next big thing. My main concerns are security, on-premises analytics, data management, and security. Yes, security is that important and mostly being ignored! In IT we talk about technology debt. If we ignore these important factors, there will be more to resolve than the technology debt of trying to redo poorly implemented systems. Without a design focused on security, there will be a large increase in successful device and network compromises. These compromises will result in a range of outages. The start of the range would be an amusing inconvenience, while the other end of the spectrum would be a complete disruption of important services across the globe.

My recommendations for successful IoT deployments are as follows:

1. Security. Security should be designed into the IoT device and ecosystem from the beginning. There must be a baseline for IoT security and compliance. The IoT Security Foundation has published an IoT Security and Compliance Framework. All devices should adhere to these practices whenever possible. IoT devices should be scanned for vulnerabilities just like Operating Systems and Appliances are today and kept up to date. This will be an ever-evolving area as more systems are linked to gain more value from the data.

2. On-premises analytics. There are many platforms for analytics in the cloud. Companies have improved processes and saved money with these platforms already. My favorite story is how Hershey’s will save millions of dollars on Twizzlers production improvements. As a previous employee of a manufacturing company, I do have a soft spot for this industry, but analytics applies to all industries. The more proprietary the data or the more isolated the IoT networks, companies will need to run analytics on-premises for security, compliance, and design reasons. This will require edge computing and storage beyond anything we’ve seen before. IT will need to design the best combination of edge and core analytics to accomplish what their lines of business need. Many companies are trying to consolidate their edge computing instances. Instead, they should be thinking about using SDDC to quickly make their edge computing more uniform in preparations for its growth.

3. Data management. Hershey’s has 22 sensors on each Twizzlers tank. These sensors collect 60 million data points. These astronomical numbers represent a very, very small fraction of IoT data on the planet today. And those numbers will increase exponentially monthly. It is a good time to be in the data management business! We will need a new approach to this compared to how we’ve managed and retained databases, files, and email in the past. The data that isn’t valuable today, might be valuable in the future. Educated guesses will determine which historical data should be retained either at the edge or within the core at the beginning. As IoT matures, deep learning can be used to identify which values will be useful. The size of the data points will be small, but they will be generated quickly and often. This will also require vast improvements to networks – 400GbE and 5G implementations are right around the corner. We’ll see requirements for IPv6 in every organization when IoT proliferates. Design teams must be created around data management solutions and processes to solve these problems.

There are many more perils than those listed above when pioneering a new era of technology, but those three are the ones that I believe are most often overlooked by product teams and engineers. I look forward to more conversation about the blind spots you have identified in this space.