Intel Reveals DCIM Need More Automation

A study sponsored by Intel revealed data centers lag in employing automation processes. Almost half, or 43 percent, of all data centers revealed they use manual techniques for carrying out automatable tasks. The perception that automated approaches would be too expensive was responsible for 35 percent of respondents not implementing the necessary technology.

Data Centre Infrastructure Management or DCIM uses tools that monitor, measure, manage and control data center resources, as well as energy consumption of IT and facility components. For large data centers, DCIM is critical to ensure optimal performance of the facility. Because balancing the demand of end users, VARs, MSPs or other service providers, with the infrastructure constraints of the center is getting more complex in a world that is always connected.

The survey was conducted of 200 data center managers across the US and the UK, and it revealed the lack of automation that’s responsible for a lot of inefficiencies. More than half or 56 percent of manual planners have to devote more than 40 percent of their time every month to capacity planning and forecasting. Considering how much power large data centers consume and the necessary cooling it takes to ensure the safety of servers, performing these processes manually can only be described as unproductive.

The survey also revealed the amount of time it takes data centers with manual processes to recover from an outage. While 21 percent of the centers using DCIM for capacity planning and forecasting recovered from an outage within two hours, the average time for recovery was seven hours and 53 minutes. The average cost of these outages was $28,900.

With the right DCIM in place, operators can access information that allows them to quickly identify problems so they can start putting solutions in place to fix them. If the process is not automated, it takes that much longer to identify and find solutions.

The value DCIM brings, according to Gartner, includes continuous optimization of data center power, cooling and space as well as integrating IT and facilities management. This helps to achieve a higher degree of efficiency with a model that continually asks “what if” scenarios. Additionally it provides the data that answers how resources and assets are interrelated within the facility.

Edited by Kyle Piscioniere