There has been a lot of communication in the market about the definition of edge computing, Internet of Things (IoT), and explaining how edge is where computing happens between here and there to reduce latency. Assuming you know most of this already (and if not, check out this informative blog on the relationship between edge and IoT), we are going to examine service expectations at the edge.
Why Scaling Services for Edge Computing Environments Makes Sense
Because edge environments can be smaller deployments but high in volume, it is critical that services are scaled appropriately. Services for a single UPS should not cost the same as services for hundreds of UPS deployments as digitization should enable scalability. Your edge deployments are unique, and the services to protect your deployments are no different.
Since edge is mainly about processing data locally, closer to the sources, we are finding that our customers are building and distributing more critical IT infrastructure across their enterprises. As these critical applications are deployed in retail, healthcare, banking, industrial environments, and other markets, our customers are becoming more concerned about services for these distributed locations. These may be smaller deployments than traditional medium to large datacenters, but they are equally as critical. Downtime can mean lost revenue, just as when a large data center experiences issues. The challenge unique to edge environments is that there typically are no qualified professionals nearby to resolve critical situations. It is not feasible (economically speaking) to have full-time IT or facilities staff in every location. With the right service strategy, in addition to real-time monitoring, predictive analytics, and alerts, this issue can be averted.
Choosing the Right Data Center Services Strategy
Let’s start with some basic services that can keep you available on the edge:
Monitoring & Predictive Analytics: Increase resiliency and transparency through service personnel equipped with 24×7 real-time device monitoring to quickly troubleshoot and dispatch. Data-driven analytics can proactively advise on potential failures, fundamentally improving the ability to service critical equipment prior to failure.
Fleet Management: Powered by remote monitoring & predictive analytics, this in-person service is tailor-made and offers a “white glove” experience for an enterprise-wide solution, minimizing business interruptions and effectively planning for lifecycle management of critical infrastructure.
Service Plans: Comprehensive service packages allow you to design the coverage you need to operate your solutions efficiently and manage costs. Service plans can be flexible to include regular preventive maintenance visits, on-site coverage, as well as access to spare parts.
With the right relationship and planning with your provider, services should be standardized with a customized approach to your requirements. At Schneider Electric we believe having peace of mind should be a piece of cake, not the whole pie when it comes to your edge environment.
More information on our latest monitoring and predictive services can be found here. For more information on edge solutions, see here. What are your thoughts? Feel free to comment below. You can also contact your Schneider Electric sales representative to learn more.