Critical Infrastructure | In-depth system of systems, that include, people, processes, software, hardware, integrations, communication protocols, plant, energy and cooling systems. Middleware solutions are generally employed to minimize the pain of integration between IT systems, but in the data center, it must do more, simplifying the complexity, and facilitating problem-solving across the data center in a transparent, holistic, and logical manner. Moreover, it needs to be able to see the entire stack of architectures in order to align the various aspects of the business, technology and facilities, which famously have different financial horizons. This means that finding a successful DCIM solution is not an easy puzzle to solve. Fred Koh from Graphical Networks wrote recently that “the most accurate way to define DCIM is this: DCIM is in the eye of the beholder,” which doesn’t sound very promising, and he may well have a point. Every environment will always be slightly different from the next. Koh argues that no single DCIM system should be fit for every organization, which leaves us back at the drawing board in terms of a single market definition. Koh highlights a couple of DCIM companies who have withdrawn from the market, and we have also seen some mergers and acquisitions. We’re die-hard optimists though, and we
see evidence that solutions are emerging. For example, this year, US industry analyst Bill Kleyman said in blog posts: “Data centers are getting smarter,” and “don’t think that AI, machine learning, and neural networks are only for cloud-minded DevOps people. You will see these solutions become deeply integrated with data center operations as well as management.” So have we figured out what DCIM is yet, and has it found its place? If vendors still define it differently, then it can’t yet be classed as mature, and this may be one reason why it’s stuck in the quicksand of the trough of disillusionment. The problem is that people’s DCIM requirements vary widely. Companies have a key client group who are their main income so they cater for those clients first. If they are all in one industry or business sector this particular DCIM implementation becomes tailored to that market.
2014
In summary, there are three major shifts towards the smart data center.
management. A proactive strategy will prevent reactive growth, and reduce risk because people have more time to plan properly and look for pitfalls rather than discovering them.
Integration is more widespread The smart DC is seen by some as a cost saving exercise, by others as a means to improve efficiency, but it could be so much more: A fully automated, connected and autonomous facility that can manage the physical elements of data center management as well as the connected software, using AI, a smattering of robotics and a bit of innovation. It will only take one adventurous company to pioneer this approach and we may see another sea change in the way data centers can be operated.
Vendors have persevered This was never an easy problem to solve, but DCIM is the first step towards delivering change management, incident handling, asset registers and other things. Involving more areas of the business than ever before, and encompassing more systems than ever before, the data center soon will be smart. A real SDDC is nearly here.
ROI is appearing As the wider IT group gets involved in DCIM and sees the advances that have occurred over the last few years, they can now identify where they could use this information to assist in change management, capacity planning and pro-active growth
Marketing, strategy and growth hacking specialist Venessa Moffat and project manager Ken Peters were part of the DCIM Deliberations working group of the Data Centre Alliance
At the Peak
EXPECTATIONS
Entering the Plateau
Climbing into the Trough
On the Rise
Climbing the Slope
Technology Trigger
Peak of Inflated Expectations
Trough of Disillusionment
Slope of Enlightenment
Plateau of Productivity
TIME
Issue 30 • October/November 2018 35