How the data centre evolved to suit modern needs and new technology

The basic principle of the IT industry is closely similar to how the rest of the world functions; things change after some time, new advancements and technologies are flown in along with a plethora of ideas and innovations. The past few months have changed how we deal with technology.

It has now become the backbone for business continuity and is mandatory for conventional businesses, data centres (DC) to adopt and be adept to the new norms and technology. As businesses run virtually and screen time of individuals increases, the real pressure is on data centres to be efficient than ever before.

While it is appalling, reality is to normalise the new normal. As per a recent CBRE report, India’s data centre market is set to grow in 2020 with rising demand and supply.

It further stated that with growing digital consumption patterns such as online gaming, education, streaming, ecommerce, data centre operators are expected to see a huge demand for data centre space.

As this data surge increases, traditional data centres will become bogged down. However, making the right investments in conjunction with Machine Learning (ML) can help these data centres drive operational efficiency and reduce costs.

Server optimisation = operational efficiency

Physical servers and storage equipment are the two key entities of any data centre. While their maintenance is not only time consuming but a potentially expensive task, if not done right, it can be a cause of the downfall of any conventional data centre.

Fortunately, AI-based predictive analysis has proven to be efficient for data centre managers to successfully distribute workloads across different servers.

A proper workload distribution allows each server to operate at its full potential, while also enabling to easily predict and manage data centre workload.

As DC managers get better visibility on server performance, network congestion, and disk utilisation, they can easily optimise server storage systems that will reduce cost, lower failure risks, and increase efficiency.

AI making services smarter is precisely why it has emerged as a priority.

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Intelligent monitoring

ML has always been a blessing for IT professionals, having a unique capability to reduce human effort in daily IT monitoring tasks. ML solutions incorporate large amounts of data to accurately predict when a machine is close to its breaking point.

An intelligent rack power distribution unit enables a DC manager to monitor power distribution at a Power Distribution Unit (PDU) as well as the individual output level. It is also designed to give user-defined performance threshold alerts.

These notifications allow DC managers to effectively monitor the entire data centre without being physically present. This presents a huge opportunity in the current frame of business operation – with social distancing being the new norm.

These intelligent PDUs give managers more real-time control of the DC operations – turning a device on or off, managing if a device gets overheated, etc. Intelligence is the new progressive way to manage a data centre.

Having the right flavour of AI and ML

For data centre managers to redeem greater financial benefits and higher efficiency, ML and AI must be carefully infused with right data centre tools. This means that data centre managers must watch the AI and ML space carefully as they try to distinguish better approaches to improve traditional data centres.

Here again, a smart PDU proposition offers an edge clubbed with ML solutions. Data centre managers can effectively allocate resources when provided with insights to better manage power distribution, energy saving, and ensuring reduced server crashes.

As we all get used to the new normal, the virtual world is experiencing growth too. To manage this growing congestion, conventional data centres require a ‘hardware make-over’ if they are to survive the new normal world.

For that, it is essential to accurately identify opportunities for improvement, analyse risks and implement solutions before the next evolution cycle takes place.