DCIM providers have long advertised DCIM as an ideal tool for industry professionals due to its specialty in asset monitoring and planning. However, there is a remnant from DCIM’s predecessor the BMS or building management system – that most DCIM solutions have yet to shake: the exclusive focus on managing existing assets and not sufficiently planning for future states. A true DCIM is one that allows the user to manage potential or planned datacenter assets along with existing assets in order to establish capacity metrics that influence future business decisions.
In many ways, a run-of-the-mill DCIM is a simple extension of BMS systems. The assets managed in these DCIMs are tailored to the IT world and will occasionally throw in some limited real-time monitoring capabilities in an attempt to distinguish itself from the crowd.
There are, however, some simple questions asked by business professionals that most DCIM providers cannot answer:
- How many more full SKUs can I fit in my datacenter?
- Do I have enough power allocated to my data hall to cover my future expansion?
- When will I run out of resources in accommodating all these promised projects?
By simply managing existing assets, industry professionals are caught flat-footed by these questions. How will I know when I run out of resources when I am only presented with information on my current inventory? To what degree can I expect to expand if all I know is that I am currently under my capacity limit? To answer these questions, attention must be shifted from simply managing inventory to managing capacity.
How does one manage capacity in any application? Fundamentally this boils down to knowing the maximum amount of a group of resources a given product can support. For example, cinemas know they can fit 200 people in any given theatre because they have provided 200 seats.
Think of these “seats” in datacenters as potential locations for cabinets to be placed. For example, if 4 cabinets exist in a row but the row has the potential for 16 a common DCIM solution would simply say “There are 4 cabinets in that row.” A true DCIM solution would say “There are 4 cabinets in that row with a potential for 16.” Datacenter Clarity LC believes in switching focus from managing the 4 existing cabinets to managing the 16 potential cabinet positions while expressing that 4 of those positions have been filled.
There are numerous benefits to this solution. By simply reporting on a percentage of filled cabinet positions, the denominator in any one capacity metric has been identified. Instead of simply stating “This row is using 100kW of power” you can now state that “This row is using 100kW of the 450kw available for this region.” These metrics can be applied to power requirements, cooling requirements, and even U-space utilization in the cabinets themselves, thus creating a powerful engine for capacity planning.
In addition to capacity metrics, users can plan their future projects by reserving cabinet locations for future use. If there is a known project that is scheduled for operation in July of next year, an operator can reserve the exact number of cabinet positions required from start date to end date, while also detailing the resources required from those individual positions (power requirements, cooling requirements, etc).
On a small scale, this is useful for general operations, but when this forecasted usage is rolled up, managers can generate powerful reports and dashboards that can forecast the usage required from their datacenter for years to come. The questions posited above can now be answered.
By taking a big step away from the BMS philosophy, DCIM solutions can finally answer the questions on the minds of business professionals planning for their future. It is clear that forecasting capacity metrics should be the centerpiece of any mature DCIM product.
Author: Oliver Foster