In our previous blog post, we discussed the three core capabilities that constituted AIOps solutions: data ingestion and handling, machine learning analytics, and remediation. With an exponential increase in the amount of data generated by all these devices and siloed tool sets, the job of IT Ops can only get more challenging.

It is increasingly clear that tools developed to keep a single system or a small cluster running are no longer sufficient in today’s highly distributed, complex environment. The tools that offer service assurance must be able to move their way through complex application systems and prevent slowdowns or application failures. These complex systems now include physical systems, virtual systems and even systems found in a cloud service provider’s data center.

There is a lot of activity in the AIOps vendor market today. With that activity can come a lot of noise and many varying approaches and points of view, and quite a few thought leaders have offered their thoughts on the potential value of AIOps solutions. (Here’s a great take from our own CTO: The Truth About AIOps.) But most IT practitioners starting projects today want to know how they can use AIOps to make their teams more productive in the near term.