Industry executives and experts share their predictions for 2023. Read them in this 15th annual VMblog.com series exclusive.
Change, Automation and DevOps
By Richard Whitehead, Chief Evangelist at Moogsoft
In today's enterprise IT landscape, leaders
must think several steps ahead of their competition - and themselves. That
entails thinking smart, not just fast.
Many IT leaders solve
problems by expanding their tech stacks. But this MO can drive technical debt,
contribute to extended system downtimes and create a fragile data ecosystem.
And in 2023, those problems will be aggravated by an IT market experiencing scaled-back budgets and an extended talent shortage. It's high time for IT leaders to step back and assess
the utility of their existing processes.
For example, many companies spend big on
monitoring tools but neglect to add an intelligent-correlation layer. In other
words, they're collecting immense amounts of data they cannot process or
understand. That's problematic because inaccurate understandings of data and
system downtime are primary drivers of unmet or even violated service level
agreements (SLAs).
Leaders are catching wise to this problem. To
solve it, they'll turn to AI and DevOps - if they haven't already. Let's
discuss these and other drivers for business innovation in 2023.
Change
management will receive the AI treatment
Change management is notoriously difficult to
get right. Not only does the process invite concerns about system
interoperability and 24/7 performance, but there's also the human element of
organizational change. Proper change management requires constant communication
with direct reports, collaboration among disparate teams and trust in all
directions. To facilitate these needs, leadership must be incredibly present
and committed to the cause. As such, IT leaders are increasingly turning to
processes that expedite and improve the implementation side of change
management. Enter: AI.
Early iterations of AI in change management
have been rather successful. The most promising technologies parse data from
newly implemented tech to isolate possibly code-breaking errors. Once a
problematic node is identified, the system determines its relative importance
using machine learning (ML). This information guides the system's ability to
address the error before it becomes a consumer-facing issue and without
compromising other functionalities.
Although at-first challenging for developers,
this process becomes more robust by the day. Moogsoft developers tackled a
similar hurdle in building Vertex Entropy, a graph theory-based
AIalgorithm that identifies which nodes are most likely to be causing problems
under any given set of conditions. Instead of requiring massive amounts of
information, Vertex Entropy operates using only a local subset of data points.
This AI-backed capability will be instrumental for change management moving
forward.
AI will
overtake automation
In our software-defined world, almost every
procedure can be automated. The decision or trigger point for automation
deployment, however, remains tricky. Leaders must carefully consider the ROI
based on several lines of questioning, including whether automation can
accomplish tasks at the same level as a human worker, if not higher. Often, the
answer is "no." Why? Automation operates under an "if-this-then-that" ruleset
that precludes intelligent decision-making irrespective of a human
administrator.
On the other hand, AI is capable of making
less brittle decisions based on existing system data and complex algorithms.
Modern iterations of AI accelerate the decision-making and implementation
processes, much like automation, though with better results. We're starting to
see this realization dawn across leaders in several industries. As it does, AI
will overtake automation in terms of adoption across the entire business
lifecycle, improving generalized efficiency and performance.
DevOps-forward
organizations will excel
The definition of "DevOps" is fluid. More than
a technology, the set of principles and practices adopted by DevOps teams
represents a culture - which means widespread adoption requires a paradigm
shift. Easier said than done, right?
Still, DevOps adoption is critical for all
modern organizations. "Technology" no longer describes the toolkit that sets a
business' internal operations apart from or ahead of its competitors. Software
is the realm in which teams reach their customers, be it through e-commerce
platforms or social media. An IT team's internal operations should reflect this
shift toward digital-first operations by prioritizing DevOps, a philosophy that
leads to reliable and faster deployment, not to mention better security and
scalability.
As the number of people conversant and
comfortable with DevOps grows, adoption will snowball. Organizations that do so
sooner rather than later will ultimately win out, as they will reach DevOps
maturity much faster than their competition. And in the modern world, maturity
in a DevOps team is synonymous with success.
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ABOUT THE AUTHOR
As Moogsoft's chief
evangelist, Richard brings a keen sense of what is required to build transformational
solutions. A former CTO and technology VP, Richard brought new technologies to
market and was responsible for strategy, partnerships and product research.
Richard served on Splunk's Technology Advisory Board through their Series A,
providing product and market guidance. He serves as an Ambassador for the
DevOps Institute, and recently co-chaired the ONUG Monitoring &
Observability Working Group. Richard holds three patents and is considered
dangerous with JavaScript.