I was in Washington DC last week meeting with quite a few government agencies to discuss all the ways Nlyte can be used to enable data center consolidation, capacity planning and optimization. There was a tremendous interest in looking forward with regards to data processing in the federal government and each agency is handling their planning a bit differently, but they all agreed that the existing data center structures that they currently operate are fairly inefficient. Gear is dated, processes are inconsistent and timeframes to execute even the simplest of tasks are enormous.
Although there were a wide variety of data center types in those discussions, the vast majority of those people I spoke with seemed to have a genuine interest in the Nlyte approach to optimization, and specifically proactive asset lifecycle management. They recognized how important knowing which assets they had, where they were, how they were being used and when they should be retired. They also needed processes to manage all that change. They fundamentally would love to have the same and granular level of control that their agencies have in more common business management practices, such as budgeting and policy enforcement.
However, given that they collectively seemed to have such a high level of interest in taking big business-savvy steps forward through the use of “DCIM”, it was a bit surprising to me that several of them also seemed to be confused about how to execute pro-active strategy initiatives while having to continuously deal with reactive daily tactics. If I had to sum up the tone of those discussions, they all had a common theme associated with the relative difficulty (and hence the importance) of process re-engineering required to make any data center (of any type) operate more efficiently. In fact, several folks said, “I have been curious about DCIM for a long time, but this sounds like I will have to retrain and redesign the people and processes that I use today in my data centers to take advantage of DCIM”. Politely, I confirmed that they were correct…. and that I was thrilled that they zero’d in so quickly on the BIG opportunity for their data center optimization challenge. I acknowledged that they could continue to make any number of tactical moves, like raising the temperature of the data center, and save a few dollars along the way, but that the BIG optimization available to them required commitment to process efficiency and workflow management.
Data Center optimization is all about managing change more effectively, and is the direct result of identifying inefficient behavior(s) and then correcting those. Nlyte’s asset lifecycle management solution is the most capable offering in this space to help manage that change and provides a means to model good behavior and then enforce it. In a nutshell, well designed processes to deploy new gear, remediate existing gear, and then retire aged gear is what this is all about. Once these new and well-conceived processes are adopted, users find their ability to support new applications and plan for their own future becomes significantly easier.
Yes, it does take a certain amount of discipline to reap the benefits possible through DCIM. Times have changed and today there is significant support throughout the ranks to think different, think smarter. It’s not just about keeping everything running, it’s about keeping it running at the right cost. The Nlyte solution is one of the easiest ways to think smarter and enable that BIG cost-savings once you have decided that it is the right thing to do. People have to be willing to re-think how they solved their data center change problems perhaps 10 or more years ago and instead challenge themselves to solve the data center challenge using modern means and business metrics.
The question people have to ask themselves: Is it better to hold fast to a sinking ship, one that is well recognized to be inefficient, or is it better to take the leap and swim as fast as possible to the rescue ship with modern proven approaches? Methinks there is a short-term versus long-term answer to this question. What is your timeframe?