Over the course of visiting some of the more than 100 data centers Schneider Electric manages, I’m continually struck by this idea: running an effective data center operations team involves many of the same elements that go into running a successful performance race car team.
At a base level, both endeavors require the following:
On the front lines: pit crews and operations teams
Let’s first look at the most visible folks on a race car team. Whether you’re talking Formula One or NASCAR, the setup is much the same.
A successful team has a crew of experienced, proficient mechanics who tune the engine and generally do whatever is required to maximize the car’s speed and safety.
The team also includes a pit crew that specializes in changing tires, adding fuel and making other adjustments in just a few seconds, so the car can quickly get back on the track.
These teams are analogous to the technicians who maintain and repair the power, cooling and safety equipment as part of a data center facility operations team.
All of that equipment must be kept in good repair to ensure uninterrupted data center operations. And, like the pit crew that has to do its job quickly so that the car doesn’t lose ground, maintenance teams must perform their jobs with little to no data center downtime.
Race car teams also rely on vast amounts of data to not only help them engineer their cars, but track performance in real time on race day.
The Ferrari Formula One team, for example, has two data centers that it uses to monitor, store and analyze various components of its cars during test drives and actual races.
Typically, teams will crunch this data in real time and feed results to a technician with a laptop at the race site. With data on tire condition, fuel consumption, brakes and lots more, the technician can determine the optimum time to go in for a pit stop.
This is a significant step forward from the idea of simply taking a pit stop every 50 laps or so; accurate data can help race teams wring more laps out of a tank of gas or ensure a car pits on lap 47 before a tire fails.
Similarly, it’s important for facility operations teams to understand the condition and state of all data center infrastructure equipment. Accurate data can help them determine when maintenance is actually required, as opposed to simply adhering to a schedule. Such data can help them detect conditions that may affect equipment operation (excessive heat or humidity, for example).
Analysis of historical data can also inform improvements going forward, just as race teams continually tweak their cars to improve performance.
It takes more than just data to be successful in racing or data center operations, however.
While data certainly helps inform decision-making, in racing it’s the car’s driver who has to take in all the information his team collects and decide how to act on it.
The driver is watching not only the track, but the car’s dashboard, continually responding to conditions outside and inside the race car, accelerating and braking as conditions dictate.
All of the components, devices, instruments and sensors inform decision-making, but it’s up to the driver to decide what to do when the rubber literally meets the road.
By the same token, data centers require someone with the experience required to take in all the data the support systems provide and decide what to do with it. In some cases it may be obvious that a certain component absolutely needs maintenance today. In others, there may be options to consider, and it takes expertise to decide which is most conducive to reliable data center operations.
So, the question for any organization that operates a data center is, do you have the experience it takes to make effective use of the data you’re getting from your data center infrastructure management (DCIM) or other tools?
Are you driving your data center in the most effective, efficient manner possible?
Most companies are not in the data center business, and simply don’t have the experience required to take on the job of running a data center, a topic we covered in this previous post on data center operations.
And most companies don’t have access to platforms like the Schneider Electric EcoStruxure ITTM architecture, which collects data from numerous customers and deposits it into a secure data lake for analysis to improve asset performance, availability and reliability.
The cloud-based EcoStruxure IT takes computerized maintenance management to another level, applying artificial intelligence to inform a predictive maintenance program that enables our experts to quickly identify data center components that need maintenance.
This ensures we only make pit stops when required, otherwise keeping your data center running at full speed.
Such detailed analytics also allow us to ensure your equipment operates at peak performance levels, ensuring you stay a step ahead of the competition and ultimately win the race.
Article by David Gentry, Schneider Electric blog network.