Which maintenance approach should data centers follow for the most effective use of their resources?

With the prevalence of cloud computing and online services, enterprises rely heavily on data centers to serve users. Uninterrupted and reliable data storage has become indispensable for providing stability and continuity of services. However, disk failure can occur without warning, which is why Preventive Maintenance and Predictive Maintenance are indispensable tools for every data center.

Preventive Maintenance prevents disk failure with the help of regular checks and replacement of the drive based on age or usage. The main challenge with this approach is the waste of valuable resources. Apart from the time spent in these maintenance activities, the drive could perhaps work effectively for a longer period of time. There is also a chance of drive failure occurring before the scheduled replacement.

On the other hand, predictive maintenance is a more individualized approach that maximizes the effectiveness of the drive. It predicts disk failure based on historical data of millions of data points collected over years. When a pre-failure pattern is detected by the AI algorithm, it is flagged as an unhealthy or at-risk drive. Data centers can immediately replace the drive. This is the idea behind the ULINK DA Drive Analyzer.

Predictive Maintenance takes advantage of advanced analytics and machine learning to increase reliability and reduce costly outages. It can prevent drive failures that would not be caught in time by common preventive maintenance schedules such as annual drive replacement.

Both Preventive Maintenance and Predictive Maintenance approaches have their merits. The best way forward is to use both the approaches to minimize failures as much as possible and use resources effectively.


QNAP and ULINK Release DA Drive Analyzer, AI-powered Drive Failure Prediction Tool for NAS

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