Although AI and AR were developed more than a decade ago, they experienced a slow adoption into mainstream technology, partially due to a lack of innovation. However, virtual reality (VR), AR, the Internet of Things (IoT), and digital innovations have increased technological advancements significantly. Now, these technologies are now commonly used in data centers, making them more energy-efficient, thermally optimized, and partial or fully autonomous.

Data Usage Trends of 2021 and Beyond

According to research published by giffgaff, global data consumption is predicted to rise from 9.4 billion GB in 2016 to well over 67 billion GB in 2021. This represents an astounding 720 percent increase in just five years. There are roughly seven billion internet-connected gadgets, and the numbers are growing exponentially. Many of these devices generate massive amounts of data, which must be gathered, routed, stored, analyzed, and accessed. This is where the data center takes significant importance.

The rapidly growing demand for data usage is placing increasing pressure on existing data center operators and solutions providers, further increasing the need for large data center projects. According to Crisil Research, India’s data consumption increased by 38 percent year over year for FY21 due to COVID-19, and the sector is expected to grow at a speedy 25 percent CAGR to $4.5-5 billion by FY25.

Need of AI/AR in Data Center Operations

With AR, AI, machine learning (ML), self-driving robots, and other innovative technologies taking center stage in 2021, as a response, data center architecture is seeing a large shift from classic, box-like systems to more futuristic, complex structures.

Data center operations involve a plethora of sophisticated systems, modern equipment, and machinery that require a high level of experience and skill for effective operations and rapid upkeep. AI and ML systems can simplify or, in some cases, completely automate these procedures. AR can aid in real-time data center infrastructure maintenance by allowing on-site technicians and engineers to verify live data with a single click.

Enhancing Data Center Infrastructure Management With Augmented and Mixed Reality

In an ideal world, machines would continuously function without any issues. However, real-life experiences are much different. Technicians must troubleshoot devices far too often. They must keep up-to-date with the latest technology to be able to repair, maintain, and update devices properly.

The combination of information (in various forms, such as text, images, video, and other virtual upgrades) and real-world objects, also known as Augmented Reality (AR), seeks to improve users’ engagement with the physical environment through holographs and animations. Mixed reality takes the AR a bit further. It utilizes inside-out tracking to detect the area and objects surrounding the user, allowing holograms to interact realistically with the structures in the room and enabling the user to manipulate the holograms via gesture control.

Data Center Maintenance With Augmented Reality

The evolution of AR for data center maintenance and repair offers enormous potential for on-site workers and engineers. Real-time data can be shown on a tablet, mobile device, or wearable device, displaying 3D graphics to aid personnel in executing maintenance operations.

By scanning the barcode of the rack whose maintenance is being performed via the AR application or device, it will retrieve data from the primary server and generate a 3D visualization using blocks and lines to display real-time insights and statistics. The operator can execute the project by following the pathways and directions depicted through a hologram in augmented reality.

AR is taking data center operations to the next level of digitalization by preparing the IT workforce of the future and, making it simpler for engineers and technicians to manage and repair devices on-site with less or no extra training required.

AI and Machine Learning Are Playing an Increasingly Important Role in Building Self-Driving Data Centers 

When AI was first introduced, its application was rather limited. Five years later, AI is thriving in every industrial area, and organizations are attempting to leverage the power of data for decision-making and deeper operational insights. The data center business, however, has been slow to apply AI to operational challenges. 

Impact of Artificial Intelligence on Data Center Infrastructure Management 

AI automation can scale to analyze enormous amounts of data, gathering critical insights required for minimizing energy consumption, spreading workloads, and optimizing efficiency to achieve greater data-center resource utilization. Gartner’s research has claimed that more than 30% of data center operators won’t be economically and operationally feasible if they don’t deploy AI in their data center Infrastructure Management.

Artificial intelligence can help organizations to cut their data center energy and emissions by optimizing power Management. One-third of the power saving can be done by cutting power from the data center cooling modules. Data centers in the United States alone require more than 90 billion kilowatt-hours of power each year. Power usage on a global scale can reach 416 terawatts, i.e., approximately 3% of total electricity generated on the planet. This necessitates the development of more environmentally sustainable data centers with lower carbon footprints and efficient power optimization.

Automating Manual DC Operations With AI

The temperature control requirements of data centers are influenced by data traffic and weather. Legacy cooling systems do not precisely meet the cooling service requirements of the equipment. Cooling systems in data centers are more sophisticated than those in our homes; they include cooling towers, chillers, pumps, and an indoor unit. Managing this system manually is a daunting process, thus most of the energy is lost in cooling rather than producing an optimal output. AI and ML-based power management may aid in the optimization of heating and cooling systems, lowering electricity costs, reducing manpower, and increasing efficiency. 

AI and ML are also utilized for equipment management, where the AI can learn what is normal from the data it collects and forecast any abnormalities that are found. AI systems can keep track of the health of servers, storage, and networking equipment, ensure that systems are configured correctly, and predict when the equipment can go into a breakdown.

AI systems can ‘learn’ how typical network traffic looks through machine learning, identify anomalies in the data, prioritize which alarms need security expert’s attention, assist with post-incident analysis of what went wrong, and provide suggestions for patching vulnerabilities in organizational security defenses.

Data center failures can cause long periods of downtime. As a result, businesses employ specialized personnel to monitor and predict data failures. Manually forecasting data losses, on the other hand, might be a difficult task. Data center employees need to decode and evaluate a range of vulnerabilities to determine the root cause of various issues. The deployment of AI in the data center can be a viable solution for this problem. AI can help in identifying and forecasting data failures by monitoring server performance, network congestion, and disc usage. AI systems can execute mitigation techniques on their own to assist the data center in recovering from a data outage.

Augmented Reality Solution for Data Center Infrastructure With Rahi Made Easy

Today’s data centers need to upgrade, update, and utilize the power of AI to be relevant tomorrow. Revolution in AI and ML can transform data center architecture and allow for more automated and efficient data management. As a global IT solutions provider and systems integrator, Rahi helps Data Center Providers around the globe in implementing advanced solutions for DC infrastructure management.

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