Legacy data centres represent a bygone era when cloud infrastructure was either in its infancy or non-existent. In the early stages of technological evolution, most organisations opted for on-premises data centres to meet their operational requirements. However, as time progressed, these legacy data centres have become a source of considerable challenges for organisations, exerting a notable impact on day-to-day operations.
The aging hardware and software inherent in legacy systems often lead to diminished performance, causing slowdowns in critical processes and undermining overall operational efficiency. The inherent limitations and high costs associated with scaling legacy systems further impede an organisation’s capacity to meet the expanding demands for data processing. The rigid nature of legacy infrastructure inhibits seamless integration with new technologies, posing a hindrance to technological advancement and innovation within the organisation.
“High maintenance costs, coupled with the challenge of finding skilled personnel to support ageing infrastructure, divert resources from strategic initiatives. Security vulnerabilities in legacy systems expose organisations to increased cyber threats, risking data breaches and compliance issues. The inefficiency of power usage in older data centres leads to higher operational costs and environmental concerns,” says Parveen Mittal, Vice President and General Manager, Celigo.
The challenges posed by legacy data centres have a cumulative impact on daily operations, influencing productivity, responsiveness, and the organisation’s capacity to innovate and remain competitive in a swiftly evolving technological environment. Overcoming these challenges necessitates a strategic approach to modernise the IT infrastructure and transition towards more agile and scalable solutions.
The impetus for organisations to modernise their data centres is primarily driven by emerging technologies that exert influence over this decision. Mayank Kapoor, Chief Product Technology Officer, Rupyy mentions that organisations are compelled to upgrade their data centres to meet the demands of advanced workloads such as AI and big data analytics. The desire for energy-efficient data centres is driven by the need to reduce costs and minimise environmental impact. Also, organisations face heightened security and compliance requirements, necessitating enhanced measures in their data centres. The influence of emerging technologies, especially AI, underscores the importance of more advanced data processing capabilities and specialised hardware like GPUs and TPUs to stay at the forefront of technological advancements.
The emerging technologies like edge computing, cloud computing, and containerisation, has streamlined the adoption of innovative solutions for organisations. Cloud technologies provide cost-effective and scalable solutions, allowing businesses to optimise resource utilisation and facilitate remote access. “By relocating computer resources closer to the data source, edge computing meets the demand for real-time processing,” says Mittal. This technological evolution empowers organisations to stay agile and leverage cutting-edge solutions for their evolving operational needs.
Nearly all large organisations have gone through data centre modernisation. Microsoft, in particular, embraced a cloud-first strategy, initiating a comprehensive modernisation plan that involved a departure from traditional data centre structures. This transformation necessitated the incorporation of containerisation technologies such as Docker and Kubernetes, coupled with substantial investments in Microsoft’s cloud platform, Azure. Through this strategic shift, Microsoft successfully navigated the complexities of modernising its data centre infrastructure, aligning with the evolving landscape of cloud computing and containerised solutions.
One of the primary tactics was moving on-premises apps to the cloud, which allowed for more flexibility, scalability, and cost effectiveness. Concurrent with the data centre modernisation, Microsoft also embraced a DevOps culture, fostering collaboration between development and operations teams to enhance agility and accelerate software delivery. This enabled Microsoft to report a significant reduction in operational costs, faster application development and deployment, and improved overall system reliability.
Even in India, large organisations like the Tata Group, Godrej, ICICI, Kotak Mahindra and the Bajaj Group have adopted cloud technologies. Bajaj Housing, for example, has moved 100% of its technology infrastructure to the cloud.
“We have set some of the data centres for the HPC and AI workload for our customers, and we have implemented form in row cooling to liquid cooling solutions for them, also we do have our own hyperconverged private cloud solution with our own data centre monitoring and control software to see that the top-level efficiency is maintained,” says Hemant Aggarwal, CTO of Netweb Technologies.
“Data centre migration from legacy infrastructure to newer solutions like cloud infrastructure needs to be planned meticulously to reduce risk, cost and outages,” says Mittal. He also mentions that most organisations modernise their data centre requirements in phases to cut risk and gain experience. Organisations adopt a hybrid approach, maintaining certain legacy systems while gradually transitioning others. This minimises disruptions to critical operations. Another best practice is to run both legacy and newer infrastructure in parallel for some time before completing the transition to the future solution. Organisations should prioritise thorough testing in staging environments to identify and rectify issues before implementing changes in the production environment.
Kapoor also pointed out some keyways for organisations to overcome challenges, such as potential downtime and data migration complexities, during the data centre modernisation process:
1. Mitigating downtime: Employing phased approaches, where systems are upgraded incrementally to maintain operations.
2. Handling data migration: Using automated tools and services to streamline the migration process, reducing complexity and risk of data loss.
3. AI tools: Leveraging AI for predictive maintenance, automated troubleshooting, and optimisation of data centre operations.
4. Expertise and planning: Involving IT experts and thorough planning are critical for a smooth transition, minimising potential issues and ensuring system compatibility.
As most organisations don’t have prior experience in the data centre migrations, it’s often helpful to get the service of an experienced partner. These days, data migration complexities can be tackled by leveraging advanced tools and technologies designed for seamless transitions. Collaborative efforts between IT teams, end users and stakeholders ensure a well-coordinated migration process, and contingency plans are established to address unforeseen challenges promptly. Thorough risk assessments, backup systems, and failover mechanisms are implemented to address potential downtime concerns.