Artificial Intelligence, and machine learning in particular, is predicted to have an enormous impact on many industries over the next few years, not least the industry that builds and manages the infrastructure on which machine learning algorithms run.

Data centers are part of all our lives, whether we know it or not. The services we use for work and in our personal lives, the entertainment we consume, the products we buy, the way we travel — everything touches a data center and creates data that can be analyzed.

There are many areas of data center management that will be changed for the better by the intelligent application of machine learning. 

Log Analysis

As data centers grow in complexity and size, the amount of data they generate and log becomes truly astounding. From network hardware to servers to cooling systems and power, every part of the data center generates data that can be logged and used by machine learning algorithms. We can’t analyze all that data effectively without machine learning, which has the ability to spot patterns and regularities that even the most experienced system administrator is likely to miss.

Applying artificial intelligence and machine learning to log analysis will result in faster incident response times and more effective root cause analysis of problems. We’ll be able to predict problems before they occur, and that can only be good news for reliability, availability, and cost.

Eventually, we can expect machines to make decisions based on log analysis, diagnosing problems, notifying system administrators, and eventually effecting repairs or replacing faulty components. 

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Power Consumption

Power is one of the largest expenses associated with data centers. Saving on power can significantly reduce the running cost of a data center and fossil fuel consumption.

As you might expect, Google is at the forefront of the application of machine learning to data center management. Google’s DeepMind researchers have used neural nets to examine sensor data from its data centers and predict future energy demands. In testing, Google was able to reduce energy use by 40% based on the recommendation of machine learning algorithms.

Security

IT security depends on the ability to identify and react to potential issues quickly. But the old-fashioned heuristic-based systems that attempt to identify patterns given to them in advance by developers aren’t as effective as machine learning algorithms that can trawl massive data sets looking for subtle patterns.

The power of machine learning lies in the ability of machines to teach themselves new patterns. Convolutional neural networks and other machine learning technologies are more likely to spot patterns and make effective decisions than human operators.

Distributed Denial of Service attacks are a serious problem for data center and cloud platform operators. It’s challenging to identify and filter malicious data without degrading quality of service for genuine users. Machine learning is being applied by leading DDoS mitigation services to spot potential DDoS attacks and implement mitigation protocols at speeds IT operations personnel can’t hope to match.

Over the next decade, the IT operations and data center management spaces will benefit enormously from machine learning innovations.

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