This blog post will discuss preventing memory failures in your data center and maintaining RAS.

Cloud data center managers have their hands full dealing with various hardware failures that can impact service availability and revenue. Unfortunately, as data center operators know all too well, memory failures are one of the top hardware failures. Unlike some other hardware failures, a memory failure can have a devastating effect without giving an early enough warning of a future outage to take preemptive action.

By using machine learning to analyze real-time memory health data, it is possible to predict such failures ahead of time. Machine learning helps to find hidden patterns and insights in data sets to predict future events. So, by applying machine learning to memory health data, it is possible to detect issues early on and predict when a failure is likely to occur. This gives data center operators the time they need to act and prevent an outage from occurring. And that, in turn, leads to better uptime for data center operations.