Operations | Monitoring | ITSM | DevOps | Cloud

AIOps isn’t an IT magic wand, but it sometimes works like one. One day last fall, our IT ops team was heads down on a major cloud migration project. Meanwhile, ServiceNow Event Management detected a high volume of alerts from the monitoring system—600% more than usual. That typically means a lot of unplanned work for our IT team, not to mention a delay in our cloud migration schedule.

I don’t know about you, but April traveled at the speed of light. A blink and it happened. Our teams have been working at the same speed throughout one of our favorite months of the year. With an incredible amount of updates, we’ve made our product even more transparent and easier to use. It’s not just our world-class documentation that enables you, it’s also the in-product visualizations and enablement that help guide you without you even realizing it.

In this blog, we will walk through the scenario of sending or E-bonding ServiceNow incidents to 5 destinations simultaneously, using Robotic Data Automation and AIOps Studio. E-bonding refers to a scenario where data is delivered (one-way) or synchronized (two-way) between two or different systems, which are typically under different administrative boundaries. E-Bonding term originally appeared in Service Provider and Telco space (see: ATT E-Bonding).

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.

Implementing any IT project requires time, planning, and effort and AIOps probably requires even more planning and stakeholder involvement, because of the breadth of coverage and potential to bring profits to multiple IT domains/functions (ex: ITOps/ITSM/NOCOps). Customers have high expectations from AIOps, but, even after taking such major projects, most AIOps vendors are only able to support a few core AIOps use cases, which severely limits the utility and potential of AIOps.

On April 15th Moogsoft’s VP Marketing, John Haley, welcomed Datadog Product Manager, Alex Vetras, along with DevOps Institute Chief Ambassador, Helen Beal, and Moogsoft’s CTO, Dave Casper, for an informal roundtable exploring how users can now see rich-context incidents from across the full stack in minutes, and the opportunities this presents to organizations.

Lately, I have seen fewer call outs from our field teams to our solution engineering team, and I was wondering what could be the reason? Sometimes, our field engineers approach our solution engineering team with advanced requests for data analysis, running what-if scenarios and assessing the quality of data and what new value can be gleaned by combining related datasets.

Gartner jumps right into it, describing a reorientation of a tool that has previously focused on IT service management and automation. AIOps is now also enabling a variety of new observability use cases for DevOps and Site Reliability Engineering (SRE) teams. This blog presents the guide’s major findings and a link so you can read the report for more details. About the AIOps Platform Market

I recently had the honor of moderating a webinar featuring Forrester Senior Analyst Rich Lane and Steve Breen, Head of Managed Services at ANS, titled “AIOps for the Modern Enterprise: Real-World Advice & Implementation Tips from the Pros.” In this informative session, Rich and Steve talked about the importance of building AI and automation into business strategy and provided tips, tricks, and real-life examples of how modern organizations are using AIOps to drive positive business outc