Data-center downtime is crippling and costly for enterprises. It\u2019s easy to see the appeal of tools that can provide visibility into data-center assets, interdependencies, performance and capacity \u2013 and turn that visibility into actionable knowledge that anticipates equipment failures or capacity shortfalls.\nData center infrastructure management (DCIM) tools are designed to monitor the utilization and energy consumption of both IT and building components, from servers and storage to power distribution units and cooling gear.\n\nDCIM software tackles functions including remote equipment monitoring, power and environmental monitoring, IT asset management, data management and reporting. With DCIM software, enterprises can simplify capacity planning and resource allocation as well as ensure that power, equipment and floor space are used as efficiently as possible.\nWhat is DMaaS?\nDatacenter management as a service, or DMaaS, is a service that\u2019s based on DCIM software. But it\u2019s not simply a SaaS-delivered version of DCIM software. DMaaS takes data collection a step further: Equipment and device data is collected from scores of data centers, and then that data is anonymized, pooled and analyzed at scale.\nDMaaS could potentially transform the way data centers are managed and operated, says Rhonda Ascierto, research director for the datacenter technologies and eco-efficient IT channel at 451 Research.\n\u201cDMaaS aggregates and analyzes large sets of anonymized customer data and can be enhanced with machine learning,\u201d Ascierto says. \u201cA key goal is to predict and prevent data-center infrastructure incidents and failures and to detect inefficiencies or capacity shortfalls.\u201d\nTwo early players in the DMaaS market are Schneider Electric and Eaton. Both vendors mined a slew of data from their years of experience in the data center world, which includes designing and building data centers, building management, electrical distribution, and power and cooling services.\nAccess to that kind of data, harvested from a wide range of customers with a wide range of operating environments, is the real value of DMaaS, which enables an enterprise to compare its own data center performance against global benchmarks. For example, Schneider\u2019s DMaaS offering, called EcoStruxure IT, is tied to a data lake containing benchmarking data from more than 500 customers and 2.2 million sensors.\u00a0\n\u201cThe key to DMaaS' value \u2013 and what differentiates it from on-premises and SaaS-delivered DCIM \u2013 is the pooling of anonymized data to run big-data statistical analysis using a combination of machine learning, anomaly detection and event-stream playback,\u201d Ascierto says.\n\nREAD MORE:\u00a0AI boosts data center availability, efficiency\n\nThe more data is collected from diverse types of data centers, and the more that data is analyzed, the smarter DMaaS becomes, she says. Having large sets of data about the performance of specific equipment in specific environments \u2013 temperature, humidity, air pressure \u2013 could allow DMaaS suppliers to predict with greater accuracy when equipment will fail, for example, or when cooling thresholds will be breached.\nData-center infrastructure management vs. DMaaS\nSince its emergence, DCIM software has been long on hype and shorter on delivery. It\u2019s difficult to deploy, and ROI can be unclear.\n\u201cDCIM can reduce risk while enabling new efficiencies, better capacity forecasting and improved business agility. Yet it remains an under-deployed technology owing to challenges such as implementing operational changes to support DCIM and difficulties in measuring overall ROI. DMaaS promises to mitigate these challenges and extend DCIM's value,\u201d Ascierto says.\nData-center management is trickier when computing environments are spread among traditional on-premises data centers, cloud and colocation sites, and edge computing applications. A traditional DCIM model requires software installations at every data-center site, which can be challenging when trying to compare performance across environments. DMaaS is a cloud-based remote monitoring service that\u2019s designed to support a range of deployment sites.\nDMaaS limitations\nStill, DMaaS has a long way to go to reach its potential. The long-term goal of DMaaS is to integrate physical data-center infrastructure management with many other services, including IT workload management, energy management, connectivity and business costing, Ascierto says. But it will take time to get there.\n\u201cDMaaS does not yet match the breadth of capabilities available from 'traditional' DCIM, but over time, we expect it will go further,\u201d she says. \u201cDMaaS takes the data-center world beyond DCIM, and beyond single-site, proprietary management. Over time, other data and services will likely be added, including integrated workload management, energy management, customer relationship and business systems, weather, staff services, and security and network management.\u201d\nChoosing between on-premises DCIM and cloud-based DMaaS isn\u2019t a clear-cut decision. It may make sense to keep some DCIM monitoring capabilities on-premises for security and latency reasons, Ascierto says. Sending data to a centralized cloud facility and back isn\u2019t practical for time-sensitive monitoring and alarming, for example. Forecasting, on the other hand, isn\u2019t essential to day-to-day operations and makes sense to do off premises.\n\u201cI don\u2019t think they\u2019re an either\/or proposition. I think they\u2019re an \u2018and,\u2019\u201d Ascierto says.