How Machine Learning is increasing the efficiency of data centers?

Today’s trending technologies are Machine Learning (ML) and Artificial Intelligence (AI). Gone are the days when we used to do tasks manually. AI has shown its growth from Industry automation processes to domestic household chores, the technology is inventing at every level and in every field. Then why our Data centers will be aside from technological advances of Machine Learning and Artificial Intelligence. In this article, I am going to focus on how we can make the use of Machine Learning to increase the efficiency of data centers.

To start with this, first I would like to describe a little bit about the Machine Learning process. Machine Learning is a branch of computer science that allows computers to learn without being directly programmed. I.e. it is the process of automating and improving the learning process of computers based on their occurrences or past experiences. The process includes feeding the computers with a good quality of data and then training them by implementing the machine learning models for them. Now, let me aware you about Data Centers. Data Centers are the facility that centralizes the organization’s data, IT, operations and it is composed of many technical things like routers, switches, servers, application delivery controllers, and many more electronic devices. These are the components that one needs to store and manage the most critical systems that are essential to the continuous operations of a company. Due to this, the reliability, efficiency, security and constant evolution of a data center are typically on high priority.

Data centers use a vast amount of power and energy for running for operating the computers, devices, servers and other high-performance elements. It is observed that up to 3% of all electricity in the U.S. is consumed by Data Centers. So, we seriously need to think about energy-saving ideas. For making Data Centers more efficient, we can introduce power-saving stand by modes, energy monitoring software, and efficient cooling systems. These improvements can help significant energy savings, reduce the load on the electric grid. Datacenter environments must remain consistent with humidity and temperature. Otherwise, the expensive equipment inside it may start to malfunction. Also, data center customers want to be assured that the valuable information stored in an installation will be available whenever they need it.

Let’s see how Machine Learning and Artificial Intelligence (AI) help improve the management of data centers.

Enable better energy efficiency:

Energy efficiency is a constant concern for data center managers. However, thanks to recent advances in high technology, this goal is more achievable. In 2016, Google began working on a project involving the use of AI to address cooling needs in the brand’s data centers. The resulting system takes snapshots of conditions by collecting data from. Second, deep learning neural networks use this information to predict the impact of combinations of future actions on energy consumption. Each option has a confidence rating and unreliable choices are automatically eliminated. Google engineers said the system had taught them new practices and thought the focus on energy efficiency would have a positive effect on climate change mitigation.

Increased cybersecurity in data centers

Paying attention to cybersecurity is essential for most businesses today, including data centers. Analysts believe that AI ?? will have a significant impact on hackers. Because artificial intelligence processes vast amounts of information much faster than humans, it helps data center operators to detect anomalies. Artificial intelligence and machine learning should not replace cybersecurity professionals who work in data centers, but these technologies complement human expertise. Algorithms often detect things that people miss, helping them to proactively respond to potential threats.

Helping customers and businesses to showcase their competitive advantages

As noted earlier, customers are looking for data center vendors that can meet their needs and provide the kind of reliability they need to run their business with confidence. Artificial intelligence offers data center companies the opportunity to implement the technology and then demonstrate to customers that their high-tech updates set them apart from the market. This change will likely affect businesses in many ways, for example when representatives conduct research or enterprise resource planning software. If they choose to install AI-based features in their data centers or work with companies that offer them, customers can then focus on these offerings to demonstrate their readiness for the future.

Some pioneering companies offer artificial intelligence services similar to those used by Google for energy efficiency. Datacenter managers have more options to upgrade their data centers and implement the AI, whether they are on-premise or in the cloud.

Reduce staffing requirements

Artificial intelligence and machine learning can also reduce or eliminate the number of employees needed to work in data centers. It could also allow employees to focus on more rewarding and challenging tasks, instead of focusing on continuous monitoring to detect problems.

Microsoft’s underwater data center, currently undergoing an initiative called the Natick Project, is an example of what the future will look like. It uses AI to detect anomalies that could lead to equipment failure. Besides, artificial intelligence algorithms compile information to help engineers identify the positive and negative effects of deploying an underwater data center. 

One of the most impressive aspects of the Natick project is the way the test team designed it to run for five years without maintenance. It is too early to know how far data centers can be expected to function so long without the usual human intervention. However, the data collected for this project will undoubtedly shape future projects.

Log management:

Most data center systems generate logs as they work, but they’re not useful to you if they just sit collecting dust once they’re generated. Add in any edge or peripheral devices your organization also uses, and that’s a lot of logs to sift through. Machine learning can centralize and analyze the logs, and create easy-to-use reports that are valuable to your team. 

Conclusion:

Data centers play a vital role in the functionality of websites, apps, and gadgets and overall World Wide Web that internet users access daily. As this list shows, artificial intelligence and machine learning have a positive impact on the search for trouble-free datacenter management and they seem ready to continue along this path. AI and Machine Learning act as a blessing for creating energy-efficient Data Centers.

I hope, you like the article and found it useful. If you have any doubts or queries please feel free to ask in the comments below.