Pivoting your AIOps strategy from science to reality!
The ability to view IT at the business services level rather than at the infrastructure or platform level helps IT executives, their business unit, and customers manage the performance of critical business services with greater clarity.
In an earlier blog, Technology of Tomorrow is Revolutionizing IT Operations Today!, I addressed the topic of AI for IT Operations (AIOps), articulating how AI is helping businesses unleash the full potential of their IT Operations, and ultimately reducing costly service disruptions. I introduced IBM Watson AIOps, and its ability to accelerate adoption with its pre-built AI models delivering insights by leveraging data and evidence from across the IT landscape. In this blog I will go a bit deeper into the use cases of how clients are adopting AIOps, and discuss some key technology partnerships that are accelerating this paradigm shift.
In order to understand the current reality and adoption challenges, I came across a number of use cases with parallels drawn between the current state and a future world with AIOps. The use cases all have a similar current state undertone such as depicting a support staff spending 5 hours, taking 17 separate steps across 4 tools to diagnose an issue, whilst pulling in 10 engineers to get the incident resolved. In many of these cases, as expected, issues were resolved without establishing a root cause and more significantly, without a view on the impact that it had on the business service.
With AIOps, is reality significantly different?
Digging into some of the early adopters of AIOps, I came across several interesting use cases. For instance, an online marketing company was able to leverage AIOps to monitor a degrading application, and remediate a long-standing issue that had been hampering performance for months. In this case the ability to identify anomalies that traditional keyword search against error logs failed to catch, was a proof point of the AIOps capability in uncovering hidden anomalies, that typically are not detectable by traditional management tools. There was also a noteworthy case on AIOps being used in a banking client to monitor and AI call center chatbot uncovering the reason why call volumes were declining. A fascinating anecdote in my view of 'AI Managing AI'.
However, these two cases were all after the fact, so I dug a bit more looking for use cases with pro-active impacts, and uncovered a scenario in a telco. Interesting to note, for a specific application used in a pilot trial, they were able to reduce detection time to near real-time and more appealing is that within the same workflow, they demonstrated the ability to use previous ticket data to quickly identify the resolution steps. The use cases go on, but what is evident is that there are indeed real world examples out there, and within major industries. By scaling these use cases across the landscape and incorporating topological context, it is clear that establishing an AIOps platform will bring business service mapping and real-time insight to the executive level without clouding their view with superfluous infrastructure details. The question is how do organizations accelerate from strategy to reality?
Accelerating AIOps benefits through strategic and innovation partnerships
As the enterprise software market evolves, we have seen many players making bold moves to lead in enterprise hybrid cloud and putting in place an innovation ecosystem comprising some of the biggest names in technology. These players understand that client digital transformation objectives are demanding, and hence creating an innovation ecosystem is vital in order to deliver cross-functional workflows that create great experiences for their customers.
On October 15th, IBM announced an expansion to its strategic partnership with ServiceNow. This partnership will marry the power of Watson AIOps with the capabilities in ServiceNow's Now Platform, and their market-leading IT service and operations management products. ServiceNow CEO Bill McDermott says it best:
"As ServiceNow leads the workflow revolution, our partnership with IBM combines the intelligent automation capabilities of the Now Platform with the power of Watson AIOps. We are focused on driving a generational step improvement in productivity, innovation and growth."
Watson AIOps is able to reduce resolution times by 65% and corporations that are already utilizing ServiceNow IT Service Management tools can benefit by embarking on this 'generational step'. The proposition of being able to push their historic incident information into the deep machine learning algorithms of Watson AIOps will indeed accelerate the adoption of AI to establish smarter operations. With an existing baseline of their regular IT environment and operations, a clear benefit can be derived from being able to gain quicker insights of anomalies outside of their standard operations. Furthermore, IBM has announced the formation of the AIOps Elite Team – a new no-charge advanced engagement team dedicated to engineering AIOps in a client environment and building and refining AI models.
Read more about this exciting partnership in the official press release. Take the next step, and join the upcoming webinar on November 09, 2020, IBM and ServiceNow: Help Companies Driving Greater Efficiency, Reduced Risk, and Lower Costs in IT, to learn more about the partnership, and some of the exciting capabilities behind it.