Operations | Monitoring | ITSM | DevOps | Cloud

James Beard, the pioneer of television cooking shows, once asked, “Where would we be without salt?”. Salt is often underrated, even though it is the ingredient that has the greatest impact on food and flavor in the modern world. It has its own taste, but also balances and enhances the flavor of other ingredients. Salt boosts sweetness and blocks bitterness, it has scientifically proven capabilities to intensify flavor compounds that are too subtle to detect (i.e.

Our human capacity for ingesting information and acting on it, is constant. As the systems we operate grow more complex, we need to make sure we use technology that presents us with only the relevant information we need, exactly when we need it. In aviation, this lesson was learned long ago, and now IT Ops is catching up.

With so many IT vendors claiming they provide AIOps platforms, how do you understand the differences between them, and decide what flavor of AIOPs to choose for your organization? Join us in a CTO Perspective discussion with Elik Eizenberg, CTO and co-founder at BigPanda, to find the answer. Read the skinny for a brief summary, then either lean back and watch the interview, or if you prefer to continue reading, take a few minutes to read the transcript. Enjoy!

Coined by Gartner in 2016, the term ‘AIOps’ refers to the combining of big data AI and machine learning to automate and improve IT operations processes. Back then, this very broad definition led to some confusion, with different IT vendors characterizing AIOps differently, depending on what they were actually offering.

Today’s IT landscape is complex, hybrid, and fast-moving, and the adoption of multi-cloud infrastructure, applications, and new digital transformation initiatives is accelerating. IT operations teams, playing a vital role in enabling the delivery of uninterrupted services and creating business value for enterprises, are finding they need to constantly grow their resources to manage all the moving pieces in their IT stack. This can get expensive … but how much are they spending?