Predicting the future of new technology is often like gambling. Predicting the future of a massive locomotive on a railway track is quite predictable. The future of edge compute is more like a locomotive with a predictable future. It is already impacting the energy and mining industry today and there’s much more to come in the next few years.
Let’s start with some general enterprise market numbers for context. In early 2023 Grand View Research identified that the edge compute market had grown from $1.9B in 2020 to $11.24B in 2022. Their research predicts an exponential growth curve that will continue at 37.9% compounded annual growth rate and reach $155.9B in 2030. That’s a very big number, almost 100X increase in 10 years. It’s safe to say this technology will touch almost every enterprise.
These edge compute numbers may explain my boldness, but the business value of specific outcomes are what drives this growth in energy and mining. The following trends are what provide fuel for this growth in the near term.
I’m often reminded that digital instrumentation has been around for dozens of years in process control. In spite of our history with digital instrumentation, a surprising number of instruments are still read manually and entered by hand into computer systems. This is changing. The use of centralized operations centers and remote experts raises the need for visibility across all process elements from remote tools and dashboards. The move to more complete digital instrumentation is making the role of compute and data infrastructure critical to operations.
Almost everyone has drastically shrunk their corporate data center footprint and moved their compute functions to the cloud. This approach continues to be problematic for many operational environments that struggle to get reliable connectivity. Even with the improvement of today’s connectivity options, the risk of failure is still too high for critical operations. In addition to the reliability risk, the latency risk for certain operations is also too high for cloud services. These two factors make compute at the edge an important consideration.
In 2023, It seems like every conversation or publication must contain a reference to Artificial Intelligence (AI) and for good reason. AI can cut through the noise and focus our attention on the critical data points that affect meaningful business outcomes. In many cases the resulting algorithms are quite simple and can be deployed in lightweight container apps at the edge.
Container Apps at the Cisco Edge
AI is one of multiple use cases that benefit from container-based compute at the edge. Cisco’s container feature (IoX) directly addresses this trend today in energy and mining companies. Here are a few examples of edge software that address operating outcomes today. Each software solution has an instance running at the edge, in a container, on a Cisco router or switch.
Cisco Cyber Vision
What if your network’s routers and switches could give you visibility to the OT inventory on your network and identify any security anomalies that occur? Cisco’s Cyber Vision can provide this visibility from your Cisco infrastructure. The Cyber Vision agents that monitor OT traffic and describe it in meta data for central analysis, live in containers on Cisco routers and switches. There is no need to invest in separate monitoring devices and an expensive backhaul network to reroute that traffic for analysis. It’s built in.
Industrial Network Solutions
What if you could implement a small SCADA function in a router or switch that lives in a small cabinet or pumphouse? Industrial Network Solutions has integrated multiple container based agents that can perform all needed functions from a container on a router or switch. This avoids the old model of putting expensive purpose built boxes at every little site. It puts SCADA into locations with Ignition Edge, Node-RED and others where dedicated SCADA devices were not feasible before.
What if you could objectively measure the communication experience that your remote site is experiencing? A small container app from Cheetah Networks gives you visibility to modem metrics and other local data points that were very difficult and cumbersome to aquire and manage with other solutions. As you guessed this container app can live in Cisco’s routers and switches without additional compute hardware.
Cisco Edge Intelligence
What if you need customized data management? Sometimes data acquisition requires a more flexible tool that can read data locally, normalize it and then send it to a central server as required. Edge Intelligence from Cisco is one such tool that’s highly programmable and comes with a wide variety of connectors and normalization capabilities. As with previous examples, it lives in a container app on Cisco’s routers and switches without additional compute hardware.
These are just a few of the apps that have found a home in the small container space on Cisco routers and switches. The sweet spot for this approach is a small site that can’t justify a dedicated compute platform or an app that is tightly associated with network traffic on the router or switch.
The edge compute trend is coming like a freight train and needs to be assessed across every enterprise. Before investing in a dedicated edge compute platform for every possible location, take a look at the capabilities already built into your network infrastructure. You may be surprised by the capability that’s already there.