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Understand the trade-offs with reactive and proactive cloudops

It’s a no-brainer. Proactive ops systems can figure out issues before they become disruptive and can make corrections without human intervention.

For instance, an ops observability tool, such as an AIops tool, sees that a storage system is producing intermittent I/O errors, which means that the storage system is likely to suffer a major failure sometime soon. Data is automatically transferred to another storage system using predefined self-healing processes, and the system is shut down and marked for maintenance. No downtime occurs.

[ Also on InfoWorld: PaaS, CaaS, or FaaS? How to choose ]

These types of proactive processes and automations occur thousands of times an hour, and the only way you’ll know that they are working is a lack of outages caused by failures in cloud services, applications, networks, or databases. We know all. We see all. We track data over time. We fix issues before they become outages that harm the business.

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