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The New Normal for IT Ops Deepens Need for AI - Part 2

Will Cappelli
Moogsoft

The global pandemic has radically changed how enterprise IT services are consumed, both in the short and long term. Here's how AIOps can help IT Ops teams:

Start with The New Normal for IT Ops Deepens Need for AI - Part 1

Managing the New Normal

The new normal includes not only periodic recurrences of Covid-19 outbreaks but also the periodic emergence of new global pandemics. This means putting in place at least three layers of digital business continuity practice:

■ Continuity for illness-free periods

■ Continuity for periods marked by known pandemics

■ Continuity for periods marked by new pandemics

Rules-based, historical data analysis, and predictive analysis based on history become useless in this scenario. Instead, what's needed is technology that can anticipate outages without reliance on stable historical patterns, as AIOps does.

Significant economic contraction and resulting pressure on both capital and operational expenditures will lead to chronic understaffing of IT operations and NOC functions. IT Ops can leverage AIOps to achieve heightened levels of automation and to support radically deep cuts in the number of tools required to both monitor the digital infrastructure and respond to incidents that occur.

As remote work becomes default, it will become impossible to replicate the "monitoring cockpit" experience or the "service desk cockpit" experience. IT operations team members and first responders will need to get by with standard IT management software. That requires a significant increase in the number of signals that require observation on the one hand and the number of tickets which require response on the other hand. AIOps can help to manage this by reducing signals and tickets.

Optimizing the New Normal

The move to an almost entirely virtualized infrastructure and service portfolio will allow for maximum agility and the ability to reconfigure people, processes and technologies to meet emerging business needs (which will themselves likely be novel in the new normal.) To provide continuous assurance of service levels (even as the services themselves evolve), IT Ops teams can leverage AIOps and its ability to anticipate outages and brown-outs on the basis of data as it arrives, as opposed to pre-existing static models of topology and user behaviour.

The shift from an IT budget that, beyond labor commitments, is dominated by capital expenditures and maintenance, to one that is almost entirely dominated by renewable operational expenditures, will increase business resilience in the face of the three types of continuity issues outlined above. AIOps can help in this area as well by helping to anticipate short-term fluctuations in resource requirements based on the possibility of looming outages and brown-outs.

The economic contraction will accelerate digitalization and, in fact, lead to what may be called "maximum digitalization" with the consequence that, for the most part, business process events will be IT system state changes. One will not be able to manage business processes unless one simultaneously manages IT system events. AIOps can be invaluable here by effectively discovering and managing the higher-level IT system event patterns that are, in fact, business process patterns.

Will Cappelli is Field CTO at Moogsoft

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The New Normal for IT Ops Deepens Need for AI - Part 2

Will Cappelli
Moogsoft

The global pandemic has radically changed how enterprise IT services are consumed, both in the short and long term. Here's how AIOps can help IT Ops teams:

Start with The New Normal for IT Ops Deepens Need for AI - Part 1

Managing the New Normal

The new normal includes not only periodic recurrences of Covid-19 outbreaks but also the periodic emergence of new global pandemics. This means putting in place at least three layers of digital business continuity practice:

■ Continuity for illness-free periods

■ Continuity for periods marked by known pandemics

■ Continuity for periods marked by new pandemics

Rules-based, historical data analysis, and predictive analysis based on history become useless in this scenario. Instead, what's needed is technology that can anticipate outages without reliance on stable historical patterns, as AIOps does.

Significant economic contraction and resulting pressure on both capital and operational expenditures will lead to chronic understaffing of IT operations and NOC functions. IT Ops can leverage AIOps to achieve heightened levels of automation and to support radically deep cuts in the number of tools required to both monitor the digital infrastructure and respond to incidents that occur.

As remote work becomes default, it will become impossible to replicate the "monitoring cockpit" experience or the "service desk cockpit" experience. IT operations team members and first responders will need to get by with standard IT management software. That requires a significant increase in the number of signals that require observation on the one hand and the number of tickets which require response on the other hand. AIOps can help to manage this by reducing signals and tickets.

Optimizing the New Normal

The move to an almost entirely virtualized infrastructure and service portfolio will allow for maximum agility and the ability to reconfigure people, processes and technologies to meet emerging business needs (which will themselves likely be novel in the new normal.) To provide continuous assurance of service levels (even as the services themselves evolve), IT Ops teams can leverage AIOps and its ability to anticipate outages and brown-outs on the basis of data as it arrives, as opposed to pre-existing static models of topology and user behaviour.

The shift from an IT budget that, beyond labor commitments, is dominated by capital expenditures and maintenance, to one that is almost entirely dominated by renewable operational expenditures, will increase business resilience in the face of the three types of continuity issues outlined above. AIOps can help in this area as well by helping to anticipate short-term fluctuations in resource requirements based on the possibility of looming outages and brown-outs.

The economic contraction will accelerate digitalization and, in fact, lead to what may be called "maximum digitalization" with the consequence that, for the most part, business process events will be IT system state changes. One will not be able to manage business processes unless one simultaneously manages IT system events. AIOps can be invaluable here by effectively discovering and managing the higher-level IT system event patterns that are, in fact, business process patterns.

Will Cappelli is Field CTO at Moogsoft

The Latest

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

On September 16, the world celebrated the 10th annual IT Pro Day, giving companies a chance to laud the professionals who serve as the backbone to almost every successful business across the globe. Despite the growing importance of their roles, many IT pros still work in the background and often go underappreciated ...

Artificial Intelligence (AI) is reshaping observability, and observability is becoming essential for AI. This is a two-way relationship that is increasingly relevant as enterprises scale generative AI ... This dual role makes AI and observability inseparable. In this blog, I cover more details of each side ...

Poor DEX directly costs global businesses an average of 470,000 hours per year, equivalent to around 226 full-time employees, according to a new report from Nexthink, Cracking the DEX Equation: The Annual Workplace Productivity Report. This indicates that digital friction is a vital and underreported element of the global productivity crisis ...