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.
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About the Author
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.