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The IT complexity pain is real. For CIOs, AI is the antidote.

By Bernd Greifeneder, CTO, Dynatrace

The explosion of complexity in modern enterprise cloud environments is more than just a headache for IT; it's a threat. As every business becomes a software company, they all face the same risks of how an inability to manage and measure IT performance affects everything from costs to user experience.

In the 'age of the customer,' being able to guarantee high-quality user experiences is paramount. If CIOs and other IT leaders aren't in control of their destiny in managing IT performance, that can quickly cascade into negative user experiences, service outages and lost revenue from downtime - all of which 44% of CIOs say pose existential threats to their business, according to new research. But, as that survey also makes clear, while CIOs are gripped with fears about the impacts of IT performance run amok, they also see AI as the antidote to those fears.

A cloud-first approach that's supercharging complexity

As many as three-quarters of CIOs believe they're approaching a time where it will be extremely difficult to efficiently manage IT performance. More than just digital transformation or cloud migration, it's specifically businesses' cloud-first approach that is fueling complexity. Cloud-first means more than just lifting and shifting assets to the cloud; it's a complete rethink of how applications are built, deployed and leveraged across an organization.

Look at what underpins the modern enterprise's IT infrastructure: applications, containers, microservices, hybrid- and multi-cloud environments, with millions of lines of code and billions of dependencies between them all. And most CIOs - between 85% and 95% - plan to ramp up their investment in technologies like containers or serverless computing, if they haven't done so already, over the next year. This will just add even more layers and complexity to their technology stacks.

The pressure from that spike in complexity weighs heavily on CIOs, nearly half of whom cited lost revenue (49%) and reputational damage (52%) as among their biggest concerns stemming from complex cloud migrations. These aren't theoretical concerns, either. Surging complexity and the costs of managing it are already having real-world impacts. IT teams spend as much as one-third of their time chasing down digital performance problems, a trend that cost businesses $3.3 million in 2019 - an enormous increase over the $2.5 million spent on it just a year prior.

These numbers point to a scenario where, year after year, a bigger share of IT budgets will go to simply managing performance. As complexity becomes more of a cost issue, we will reach a tipping point where IT simply won't be able to afford to perform this most fundamental task, let alone the other duties they have to execute.

Relieving the strain on IT with AI

There's a clear line of cause and effect here. The pressure to deliver better customer experiences fueled an explosion of technologies, services and interdependencies, creating an ecosystem where a single web or mobile app transaction will pass through 37 separate systems or components. IT spends more of their time and effort on just managing performance, and consequently less time building new products or deploying new services that could improve on those customer experiences more.

The pain is real. And in this research, 88% of CIOs point to AI as the way out. In my own conversations with other CIOs, I get the impression that some segment of this 88% has a "magical thinking" view around AI: that it will simply learn what is being done manually and then automate it, providing an instant cure-all to complexity. In reality it's not that easy. The systems, applications and processes that make up modern enterprise environments change rapidly. More than just needing AI, what CIOs truly need here is a causative, deterministic AI approach that can learn their environments in seconds, not months; an AI that doesn't need errors and failures to occur in order to learn from them.

For instance, Amazon's Alexa requires thousands of human employees to parse through the data collected by the AI to improve its ability to understand queries and provide more relevant answers. When AI requires that many human hands to learn from its mistakes and not internalize the wrong things, that's not exactly automating or streamlining anything.

That said, while there is some nuance to consider on this front (not all AIs are created equal), the bottom line is that, when leveraged properly, AI provides IT with an escape from the current predicament of sinking time, labor and money into a needle-in-a-haystack approach of managing modern cloud environments. With AI, IT can instead begin to refocus their efforts and resources toward more proactive services, customer outreach and product building, all to create even better user experiences.

In the age of the customer, the pressure to deliver robust customer experiences has never been higher. And the complexity of modern enterprise technology stacks has never been harder to manage. That puts IT squarely between a rock and a hard place. But deterministic, causative AI empowers these teams to have their cake and eat it too, automating business functions to provide easier, faster and more precise methods of managing complex technology stacks, while simultaneously freeing up IT and DevOps teams to concentrate more time, energy and money on crafting consistently compelling experiences. If IT complexity is a threat to that experience, CIOs overwhelmingly agree that a deterministic AI is the best tool for turning that threat into a new opportunity.


About the Author

Bernd Greifeneder

Bernd Greifeneder is the CTO at Dynatrace. He's a serial entrepreneur, Dynatrace being his third successful venture. With more than 15 years of engineering leadership under his belt, Bernd owns nine tech patents-including Dynatrace PurePath® technology and the new Dynatrace platform, a generation Software Intelligence solution. In his spare time, he advises startup companies, speaks at entrepreneurial events and supports academic technology research.

Published Friday, October 11, 2019 7:34 AM by David Marshall
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