Credit to Author: Scott Cassidy| Date: Thu, 04 Jan 2018 16:04:32 +0000
While the branding of EcoStruxureTM IT is a relatively new announcement, Schneider Electric’s cloud-based services based on DCIM software, were launched during 2016. However, Data Center Management-as-a-service, or DMaaS, differs from both DCIM and DCIM delivered as a SaaS offering in a number of ways, as highlighted by Rhonda Ascierto and Jeffrey Fidacaro of 451 Research in their Spotlight entitled “The disrupted datacenter; datacenter management as a service.”
The first step in managing infrastructure is to start monitoring components and equipment. DMaaS has simplified this process when compared to on-premises and as-a-service DCIM. Right from the get-go, DMaaS starts a process of aggregating and analyzing large sets of anonymized data directly from the customers’ data center infrastructure equipment via a secure and encrypted connection. This data can be enhanced using machine learning with the key goal of predicting and preventing data center failures, foreseeing service requirements and detecting capacity shortfalls.
This is useful for data center managers with resource limitations, because DMaaS “ties remote cloud-based monitoring into maintenance and fix services,” say the authors, “enabling a full-service business model for suppliers.” It therefore opens a pathway to get additional smart eyes on the infrastructure (from our network operations center) to support the internal team. It also opens the way to the development of new offerings from managed service partners (MSPs), from energy management to proactive maintenance. Again, for those with resource constraints, the ability to be able to have full insight into data center infrastructure and the IT load, enables intelligent support to be provided on a data driven basis.
The value of data is multiplied when it is aggregated and analyzed at scale. By applying algorithms to large datasets drawn from diverse types of data centers operating in different environmental conditions, DMaaS providers can predict, for example, when equipment will fail, and when cooling thresholds will be breached. The larger the dataset, the smarter DMaaS becomes with every iteration. “… as more data is amassed by DMaaS,” says 451 Research, “the greater their analytical capabilities will be and the more compelling the service will become.
The researcher goes on to say that having more data about the performance of specific equipment in specific environments (temperature, humidity, air pressure), the more accurate the predictions will become over time. They predict that in the not-too-distant future, increased data center automation will be made possible as well as full remote control as part of DMaaS-driven services, e.g., automatically switching UPS to eco-mode when utilization is low, directing IT load away from areas of potential failure, and power capping and shedding.
In other markets, the emergence of IoT technology and use of big data has also been the stimulus for the introduction of innovative business models. A potential capability of DMaaS is to enable service suppliers and manufacturers to bundle monitoring and management services into lease agreements for data center infrastructure equipment to deliver asset-as-a-service offerings. With this type of DMaaS enabled service, the supplier maintains ownership and charges for operation service. 451 Research believes that this might be especially interesting for highly distributed IT deployments and edge data center portfolios.
What makes DMaaS unique? It’s a combination of factors, some of which are already baked in, and some of which are the very real possibilities which are opened as data and analytics have a more influential role in the way that data centers are managed and operated for higher levels of utilization, efficiency and, of course, uptime. To learn more read “The disrupted datacenter: datacenter management as a service” by 451 Research.