AI in Data Center Operations: The Effects of Artificial Intelligence

Impact of Artificial Intelligence

Operating a data center properly takes a lot of work, and getting it right is essential for proper long-term functionality. Over the years there have been countless improvements and innovations that have helped companies to optimize their facilities. Currently, artificial intelligence is one of the biggest areas of technology that is just starting to be utilized in data centers and will undoubtedly be an essential tool in the future. Understanding the effect of AI in data center operations today, and the opportunities for tomorrow, will help all data center managers get the most out of this incredible technology.

How are People Using AI in Data Center Operations?

While artificial intelligence is developing in many areas, it is already in use to accomplish many tasks in data centers. Looking at the following ways that these facilities are deploying AI in data center operations today, and what we can look forward to in the future, helps to illustrate how this technology is impacting the industry.

Improved Data Center Security

Security is one of the most important requirements for a data center. This includes both physical security and digital security, and artificial intelligence can actually benefit in both areas. With physical security, an AI system can help to manage the security cameras, biometric access doors, logging visitors, and more. This will help to track who is in and around the data center at all times, so the AI system can send alerts to security professionals when someone unexpected is in the security racksolutions

When it comes to digital security, artificial intelligence really has a lot to offer. Cyber threats are a major issue that can come in many different forms. In addition, hackers are constantly trying new methods of attack, which makes this type of security even more difficult.

A growing number of data centers today are implementing cybersecurity systems that use artificial intelligence to constantly grow and improve their effectiveness. For example, an AI system can monitor the network traffic of a data center 24/7/365. Based on this data, it will learn what type of traffic is normal, and what is potentially dangerous. This system can identify unusual data patterns and block them before they can cause any harm. Engineers then review this to determine if they should continue to block it, or if it’s from a legitimate source.

Reduced Energy Usage

Data centers are used to house anywhere from a few dozen pieces of equipment to many thousands. Having all this hardware in place means using lots of energy to power these items and cool the area.

  • More Efficient Cooling – Computer equipment generates a lot of heat, which needs to be removed from a data center. AI can analyze data from temperature and humidity sensors throughout the facility and optimize the use of cooling systems.
  • Managing Lights – There is no need for lights to be on in a data center when no people are present. An AI system can manage the lighting system in the data center, as well as the surrounding offices, to ensure they are on when needed, but shut off when not required. This is a very simple task that can lead to significant savings.
  • Identifying Unused Equipment – AI systems can monitor an entire network of equipment to watch for outages and other issues. As the system ‘learns’ about the environment, it can identify devices that are on the network but aren’t being used. These devices can then be removed to help cut energy usage and other expenses.
  • Directing Resource Usage – An AI system can accomplish the task of directing data storage and processing power to the most efficient resources available. This can help to reduce the power draw to a minimum while still accomplishing important tasks.

Improving Reliability

One of the most important benefits that data centers provide is reliability. Individuals and companies rely on data centers to ensure their servers, data, processing power, and other resources are always available. Even brief outages can cause major problems for those who rely on data center services. While traditional data centers have done an excellent job of improving reliability, artificial intelligence takes it to the next level.

AI systems can identify problems with power, hardware, latency, or just about anything else and take action immediately. This action may include routing traffic to an unaffected system, engaging backup systems, or alerting an engineer to the issue. As the AI system learns more about a data center, it is able to begin predicting problems before they occur, so action can be taken to reduce or even eliminate customer-impacting outages.

Advanced Monitoring

Monitoring the hardware and software running in a data center is a major responsibility. Most non-AI monitoring systems rely on relatively simple technologies such as pinging devices to ensure they are up. Using AI allows the monitoring system to actively watch network traffic in much greater detail so that it can take action whenever there is an abnormality. This action can be directly on the software or alerting someone to investigate potential hardware issues.

AI of Tomorrow

The thing that sets AI apart from traditional automated tools used in data centers is the ability to ‘learn’ and adapt based on many different factors. As this technology continues to advance, data center engineers will be able to install AI systems and specify one or more goals to accomplish (reliability, energy efficiency, security, etc). That system will begin learning about the system and taking beneficial steps toward improvement.

While artificial intelligence today is very useful and impressive, experts predict that it will become an invaluable resource in virtually all industries in the future.

AI in Data Center Operations: The Effects of Artificial Intelligence - RackSolutions
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AI in Data Center Operations: The Effects of Artificial Intelligence - RackSolutions
People are using AI in data center operations for improving security, advanced monitoring, improving reliability, and other very important ways.
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