Operations | Monitoring | ITSM | DevOps | Cloud

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

To ensure you crush your automation goals, we've created a 12-stage journey to automation success to give you a roadmap of resources chocked full of actionable insights. Because now more than ever, IT teams need intelligent automation to counter the daily onslaught of challenges and demands.

As businesses become increasingly digital, IT operations now deal with more extensive and more complex data than before. Traditional tools and strategies might no longer be enough to help them cope with their growing workload. Hence, many organizations are tuning in to the various AIOps trends available. AIOps is short for Artificial Intelligence (AI) for IT Operations. This is where they use Machine Learning(ML) to enhance and automate IT functions.

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?

“Morning, mate,” I greeted Dinesh as he walked into the office. “Nice get up for the big day!” He was wearing a pressed shirt, rather than his usual hoodie. “Thought I’d make an effort, you know,” he grinned. We’d been planning intensely for this moment for the last week or so – our meeting with Charlie, the CIO, to present the results of our Moogsoft experiments and ask for permission to extend the rollout across the enterprise.

Last week DevOps Institute’s Chief Ambassador, Helen Beal, and Moogsoft’s own Chief Evangelist, Richard Whitehead, continued to follow the exploits of DevOps Engineer Sarah and her journey towards AIOps and Observability enlightenment.