When it comes to data centers, what is ‘peak performance’? Is it a case of using a data center monitoring system so that it works to full capacity? Or, is it more a case of maximizing its potential? Data centers are complex but integral, which is why, for the average business, achieving the best results can be difficult.
Challenges for data center operations will differ from firm to firm. However, no matter the size of server rooms and the ‘mission-critical’ status, some parameters always run in common.
Consider a few challenges that data center operators can hope to overcome to achieve that optimal performance.
Why Peak Performance Matters
As StorMagic confirms, customer experiences change and evolve. They discuss the need for HCI, or hyper-converged infrastructure and microdata centers. These are only two examples of how data center management can adapt to fit evolving needs and concerns.
Customers and businesses all benefit from peak data center performance. There is the concept of a ‘mission-critical’ data center, too. It can be the heart of the operation. For example, a hospital or medical service may depend on a data center keeping essential hardware online. What if a power outage was to hit that resource?
Data Center Frontier states that resource management is essential when it comes to assessing performance’s effects. Arguably, a data center that doesn’t perform at its best might fall short of customer expectations.
That could have effects on reputation as well as quality control. On top of this, do we know what our ‘best’ performance looks like?
Challenges in Performance: Where a Data Center Monitoring System Could Help
It’s essential to look at areas where data center monitoring could help us reach peak performance. It’s not always a case of making sure a center runs to schedule! As you may expect, it can be a complex issue.
Cooling and Power Usage
To ensure servers perform as we expect them to, we need to be careful with the power they use. Data centers are sometimes large and complex. There is the risk that they may overheat or burn out. That could lead to power outages and service delivery failures.
A common challenge in managing data centers is ensuring systems don’t reach these thresholds. Managing this can require data scientists to be exceptional at spotting problems early. However, human fatigue and human error, as a result, can lead to issues in this sector.
A center monitoring solution could be useful in helping to set thresholds for heat and energy expenditure. Remote software could communicate with a center to shut off resources, for example, when things start getting too hot.
Optimal performance isn’t necessarily about ensuring all resources work at max capacity. It is perhaps more a case of providing they all work together, comfortably, with the same end goal in mind.
Environmental conditions are essential to keep an eye on, too. Humidity can lead to system breakdown, which can lead to lost time and productivity. It may be a perfect storm for a mass power outage to occur.
Temperature and humidity could turn mission critical systems into failing resources in a matter of seconds. It is not worth the risk!
Data centers have many different parts. Once again, human management of all these working systems could lead to fatal errors. There is also an argument that some data scientists may not know what all the pieces in the data center puzzle physically look like!
Therefore, a data center monitoring system could help us to see the bigger picture. On top of this, as Stratoscale points out, moving to a hybrid system could help make resources ‘fit for purpose’. This is not just simplifying analysis and oversight but also ensuring all resources are present and known. Furthermore, this means data center managers can carefully analyze which resource is fit for which job.
Hybrid cloud models are ideal for refining data center resources. They are efficient at helping managers see the bigger picture, as well as to help refine costs!
Automated Checks and Measures
Human error is only one issue that can affect a data center’s performance. It is not always possible for data scientists to monitor and anticipate every problem that might arise. For example, tying in with the above, it is not always possible to know when a system might overheat!
A smart data center monitoring system may help by working on setting thresholds. It could learn when to switch loads or to make decisions. It could take away the need for scientific control.
In practice, this would mean that a center could look after itself without the need for intervention. When it comes to optimizing performance, software users could set their expectations.
Technology is always evolving. So, too, are customer demands. Therefore, sometimes data centers are at risk of never ‘performing’ as well as we expect them to.
That is another reason why a monitoring solution could help us to adapt to changing demands. For example, data center monitoring could help us offload processes, which could improve efficiency.
Alternatively, hybrid cloud monitoring could help us to scale. Instead of working to boundaries, managers could free up infinite potential.
For example, this may include freeing up memory to process more significant network traffic. Again, it may also help to reduce pressure when it comes to specific environmental conditions.
A big challenge for data center managers may be that they do not know their ‘best-case scenario.’ How do you know if you are working at optimal performance? An efficient, automated monitoring solution could help users understand these targets. Not only that, but it could also help them achieve these goals.
The future of pain-free data center control lies in smarter monitoring solutions. The idea of ‘peak performance’ may differ from company to company. However, the best data center monitoring system could help them achieve their maximum potential. That, for many businesses, may be enough to scale to increasing pressure and demand.