Pandemic can fuel demand for edge data centres and automation

The office computing scenario is segregated into three important components and all of them were impacted by the pandemic – the end user, the networking layer, which connects the users with the data centre and finally, the place of computing, which is the data centre itself. The coronavirus has resulted in companies making the employees opt for WFH or WFA scenario. This trend is likely to continue, which is prompting CIOs, CTOs, IT Infrastructure Heads to relook at their data centre strategy.

The new normal requires a change in the approach of hosting the IT resources in one location because in the traditional set-up, when all employees were operating from one office, it was done with the assumption that the computing will all happen at one particular location however now, it will have to be reoriented based on the geographical presence of the employees. “Companies can buy a 300-500 square feet place at a location close to a host of users with common work profiles, and host a small data centre. This will allow for faster work completion with low latency and all the necessary safeguards in place,” says Gopi Thangavel, VP & Head- IT Infrastructure, Reliance Industries. This data centre can be integrated with the main data centre.

Edge datacentres at work
This model has worked well for the manufacturing Industry, during the pandemic, when the physical movement of the people was impacted severely. “The edge data centre or the cloud computing concept allowed the manufacturing units to operate inspite of the main data centre wasn’t able to operate,” says Thangavel.

The concept of edge can be used in various verticals in the area of training. For e.g. In the times of the pandemic, when employees are WFH, there is a strong use case for augmented reality to be used to train employees. It requires Live data. The edge computing concept can be used in this scenario. Similarly, the CCTV cameras and the data getting captured can be hosted in the local sites on the LAN. Instead of hosting the heavy feeds on the cloud. It reduces the latency to a phenomenal extent.

According to Gartner, by 2025, there will be a seventy five per cent jump in the data generation and processing happening at the edge and not at the central data centre.

Data centre automation
The automation of the data centres will get further traction as there are attempts to reduce manual intervention. These are perfect use cases for the use of artificial intelligence and machine learning in the data centres. The pandemic has highlighted these needs because manpower movement was handicapped during the lockdown.

AI and ML can be used in the fundamental building blocks of running a data centre – power management, UPS, chillers, coolers, etc. “It can be used in preventive maintenance and in other words, for uninterrupted power supply, for e.g. the servers can be monitored with respect to their CPU, storage, network, hard disk, etc. Moreover, subject to availability, the historical information of the respective IT resources can be set in the algorithm, which can auto-learn and take appropriate action,” says Thangavel.

AI and ML has excellent use cases in the cyber security aspect of the data centre. AI, ML, when integrated with the monitoring tools, which are already operational. When the bots are added to this equation, it will further power the AI and ML functionalities, for example, if there is an SQL service, which always needs to be up gets down, the AI can be accordingly configured to resume the SQL service without any human intervention. Bots, combined with AI can play a critical role in many aspects of the data centres like floor management, equipment monitoring, temperature control, fire alarm system, cooling, server monitoring. The compliance report filing for HIPAA, SOC, PCI-DSS, etc can also be done using Bots.

Given, the increasing amount of security breaches in the last few months, companies are increasingly going for a zero-trust concept in the data centres and Privileged Access Management (PAM) is getting fine-tuned based on the need to access and user activity monitoring.

DevOps & DevSecOps in Datacentre (automate the automation)
Datacentres going forward will be managed using predictive analytics, limited human intervention, automated systems and tools to manage more datacentre operations issues, with real-time response.

DevOps is now getting adopted widely by enterprise level datacentre teams, using tools such as Chef, Puppet, Jenkins.

Since many applications and data originating from various streams is now getting integrated, data breach may cost more to any organization, and DevSecOps may help here. DevOps and DevSecOps together can automate the automations in the datacentre.