We live in a connected, digital world that is daily producing exponential amounts of data. Data centres that house, protect and provide secure access to this data have become the cornerstone of the digital economy. Businesses today need data centres to function as strategic business enablers that power growth and innovation, and deliver competitive advantage. It hence becomes crucial for data centre managers to rethink their traditional, reactive approaches to day-to-day operations so that they can proactively and rapidly respond to change.

A Reactive Approach Increases Risk, Reduces Efficiency

The modern data centre is characterised by high complexity and dynamism, which drastically impacts day-to-day operations. But many data centre managers, far from moving to new management approaches, still follow traditional processes that are reactive in nature.

They rely on manual methods, such as spreadsheets, to collect and manage information. The data on spreadsheets often has gaps, is inaccurate, and out of date, and this incomplete data does not offer any useful operational insights. With no insights to facilitate informed decision-making, data centre managers often over-provision power and cooling; the subsequent underutilisation represents wasted operational cost that ultimately impacts the bottom line.

Management of operations aside, data centre managers are sometimes not even equipped to anticipate faults and events. The primary purpose of siloed monitoring tools such as Data Centre Infrastructure Management (DCIM) software and Building Management Systems (BMS) is to provide an alert notification after an event has occurred – which the data centre manager then has to scramble to resolve, using fragmented data, limited knowledge, and their own creativity.

Such reactive ‘fire-fighting’ approaches are resource-intensive, decrease efficiency, and lead to increased cost and risk. Industry experts say that 40 percent of data centre outages are caused by poorly configured changes and human errors; and the inadequate resolution of issues increases the risk of such outages in the future.

The negative business consequences of data centre downtime cannot be overstressed – reduced profitability, loss of credibility and worse, lost customers.

Data centre managers today are hence in dire need of data and expertise that can help them make quick, well-informed decisions to mitigate risk, drive agility, reduce operational complexity, and optimise data centre performance. Traditional, reactive approaches are no longer enough.

Moving from Reactive to Proactive, Predictive Approaches

ENGIE believes that the data centre of the future is one that is proactive and predictive when it comes to decision-making. This new approach requires the capability to continuously gather, filter, and analyse large volumes of real-time and historical data. Data centre managers can then use valuable insights from this data to make short- and long-term predictions around data centre operations. Adopting a predictive approach can help data centres proactively anticipate and respond to change.

Accessing Data Centre Operational Intelligence through Advanced Analytics Technologies

Emerging services powered by machine learning (ML) can help data centres move from being reactive to predictive. These services gather and analyse data, identify patterns, and uncover insights to enable data centre managers to take the guesswork out of decision-making.

ENGIE, for example, can help tackle data centre operational challenges through its Avril Digital Support Services that combines the collective power of advanced analytics with ML technologies and accredited data centre expertise. Avril Digital Support Services uses advanced analytics and ML algorithms to help data centre managers anticipate and detect anomalies, identify performance shortfalls, and predict operational threats that need immediate attention before they escalate into costly problems.

Data centre managers can use such tailored services to:

  • Improve fault management through timely and accurate notifications that enable an effective response to critical faults and prevent future recurrence.
  • Detect operational threats and anticipates anomalies.
  • Maximise asset performance by detecting performance degradation, determining risk and estimating useful life.
  • Sustain data centre operations by managing performance shortfalls and improving system efficiencies at any stage of the data centre lifecycle.
  • Conform to data centre standards (such the BCA-IMDA Green Mark for Data Centres and Singapore Standard for Green Data Centres SS 564: 2013) by aligning energy and environmental performance.

Intelligent data centres are thus able to forecast future complexities and change, and develop anticipatory responses that promise predictable outcomes. This helps reduce risk and operational cost, and improve efficiency. Additionally, the early and intelligent detection, prioritisation and resolution of problems can make data centres agile and responsive to changing needs.

To find out more about how ENGIE can help you reduce data centre operational complexities and be future-ready, contact us now at engieDC@avrildigital.com.

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