Lower Your Data Center’s Operating Costs and PUE with AI

May 11, 2021

Artificial Intelligence (AI) dates back to the 1950s and is becoming a staple in everyday life. Where can you find AI in your daily routine? From virtual assistants like Siri and Alexa to getting help from an online chatbot or sitting behind the wheel of a self-driving car, AI is impacting our lives in many ways. There’s no surprise that AI can also be found in today’s modern data center to help reduce operational costs. In fact, in an article written by Forbes,Gartner has claimed that more than 30% of data centers that don’t deploy AI and machine learning won’t be operationally and economically feasible in 2020." For those that don’t want to fall behind, deploying AI might be a great goal to work toward this year.

In this blog post we’ll cover:

  1. How AI can be used to help your data center conserve energy.
  2. How AI can help optimize your servers.
  3. How AI can monitor your resources to help your data center avoid downtime.
  4. How AI can keep your servers secure from various cyber-attacks.

We will also provide a few quick tips to start implementing AI in your data center, so by the time you’re finished reading this, you will have a baseline on why and how to utilize AI in your data center.

What is Artificial Intelligence?

AI is commonly divided into three main subcategories: machine learning, neural networks and deep learning.

Machine learning gathers information to find insights and breakthroughs to improve user experience. Netflix’s ability to recommend what a user should watch next is a popular example of machine learning. The company also uses that same data to determine what new shows and movies to create.

Neural networks are made up of interconnected units and are used to solve high-level problems. Neural networks are used in medicine, such as cardiology, where neural networks can detect minor differences in a heartbeat to warn of heart attacks and arrhythmia.

Deep learning uses data analysis and abstractions from large neural networks to learn complex patterns. A great example of deep learning in action is in image recognition, such as iPhone facial recognition.

Both machine learning and deep learning are used in data centers today.

Now that we’ve reviewed AI, see how it can improve your data center operations.

AI and Data Center Energy Conservation

Maintaining a data center is expensive, and much of the cost management burden falls on data center facility managers and operators. Data centers can employ AI to reduce their operating costs through energy conservation, which is a common goal for all data centers. The use of machine learning has been incredibly effective in lowering cooling costs.

AI in Action: Google Data Centers

Google data centers recently teamed up with DeepMind and implemented machine learning to reduce its cooling energy used by 40%.The energy reduction from cooling allowed for a 15% improvement in overall Power Usage Effectiveness (PUE). The results were a breakthrough for the data center industry since cooling is one of the largest energy usage sources in data centers. They accomplished this feat by training deep neural networks with historical data they had collected over a few years and allowing the program to predict recommended actions. The graph below is from one of their tests on a live data center, which shows the point where machine learning was turned on and off.

Google DeepMind Graph                
Graph from Google shows the impact AI had on data centers: https://blog.google/topics/environment/deepmind-ai-reduces-energy-used-for/

AI and Server Optimization

Data centers can have inefficient methods for distributing workload across servers. AI can help with this by using predictive analysis to help balance the workloads. Server data can be input into machine learning and deep learning tools to help the programs learn how to balance workloads and make them more predictable. AI can collect and generate data quicker than human-run design algorithms, which makes it easier to optimize servers.

AI and Resource Monitoring

Qualified data center personnel are in high demand. There will always be a need for people to manage and oversee operations, and AI can help overworked IT staff focus less on routine tasks like updates, security patches and backups. While performing these tasks, AI can also work to detect and avoid downtime.

Implementing AI technology can help prevent costly downtime from equipment or application failures, which can have damaging effects on a data center’s reputation. Using smart sensors installed in the data center equipment, AI can learn from the data patterns and detect defects such as vibrations that are either too low or high to be working correctly. Data center engineers would be alerted to where the potential problem is, and it could save precious time in remedying the situation. By utilizing AI, data center staff have more time to focus on the larger operations of the data center and less on the routine tasks.

AI and Security Improvements

According to Data Center Knowledge, there are four main types of cyber attacks on data centers:

  • Distributed denial of service (DDoS)
  • Ransomware
  • External access services
  • Application attacks

Cyber threats are continually evolving, and data center technology needs to improve to protect against them. By using both deep learning and machine learning, AI detects changes from the “normal” operating pattern, alerting IT staff of possible cyber threats. AI can also scan incoming and outgoing data for the same type of deviations, to make sure no malware or ransomware gets in or out.

How to Get Ahead of the AI Curve

As mentioned previously, Gartner claims that 30% of data centers that don’t utilize AI already this year are going to fall behind the curve. But introducing AI into your data center isn’t a task that can be tackled in one day. With that in mind, here are a few quick takeaways on how to get started.

1) Installing smart sensors:

Installing smart sensors into equipment is an efficient way of gaining critical insights into the effectiveness of the data center. Collecting historical data is essential to the recommendations that the technology makes.

2) Start small:

Is it reducing your energy consumption or making your data center more secure? Identifying a manageable area within your data center is a great way to build the best tool for improvements, and direct you towards the best AI technology to help you achieve your goals.

3) AI improves over time:

Once you’ve established AI in your data center, remember that both deep learning and machine learning are doing just that, learning, so the results will get better as time goes on. Rome wasn’t built in a day, and AI can’t immediately drop your PUE score to 1.

Final thoughts

If your data center hasn’t already implemented AI, there’s no time like today to get started. AI can help your data center conserve energy, optimize servers, monitor resources, reduce downtime and improve data center security.

If your data center is looking to improve your PUE and reduce operational costs, DAMAC is here to help with server racks, aisle containment and other premium data center solutions to fit your data center’s needs. Learn more here: www.damac.com

©2020 Maysteel Industries, LLC

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