This is pointless. Proactive operating systems can detect problems before they become destructive, and can make adjustments without human intervention.

For example, a transaction monitoring tool, such as the AIops tool, sees that the storage system produces periodic I / O errors, which means that the storage system is likely to suffer serious damage soon. The data is automatically transferred to another storage system using pre-defined self-recovery processes and the system is turned off and marked for maintenance. There is no stay.

These types of proactive processes and automations happen thousands of times an hour, and the only way to know they’re working is to avoid interruptions caused by failures in cloud services, applications, networks, or databases. We know everything. We all see. We track data over time. We fix problems before they turn into business interruptions.

It’s great to have this technology to reduce downtime to almost zero. However, like anything, there are good and bad aspects to consider.

Traditional reactive operational technology is just that: it responds to failure and launches a chain of events, including messages from people, to correct problems. In the event of a failure when something stops working, we quickly understand the root cause and correct it, either by an automated process or by sending someone.

The disadvantage of jet operations is the downtime. We usually do not know that there is a problem until we have a complete failure – this is only part of the reactive process. We don’t usually monitor details about a resource or service, such as I / O storage. We focus only on the binary file: does it work or not?

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