Cyber Defense eMagazine January 2021 Edition

4. Security and IT Operations Will Be Better Integrated
As enterprise IT environments continue to mature, the need for advanced security platforms will inevitably
follow. The fundamental data sets used in security platforms, including cybersecurity and product
security, are almost the same as IT operation data sets. Security algorithms dissect metrics and logs that
flow through infrastructures to model historical behavioral patterns and flag anomalies. Using AI, this
process can be further automated towards blocking bad actors in real-time.
For example, say a hacker is trying to penetrate a firewall that is detected by either a change in the
volume of data, or a change in the location of the traditional user. Security features can be used to classify
that particular access as either regular access, hacker access, or insecure access. Once the access data
is detected, automation systems can block the IP address of the hacker’s particular region or that
particular range.
Regardless of the business problem, the underlying data required to gather this intelligence is still logs,
metrics, and transactions within an infrastructure. The only difference is the problem that IT security
teams are trying to solve. Security teams want to know whether a bad actor is trying to access the system,
while ITOps teams are more interested in employing applications that will protect their users and provide
a better customer experience. Next year, ITOps and Security teams will likely collaborate more closely
to not only detect problems in the infrastructure performance, but also prevent cybersecurity threats in
near real-time.
5. AIOps Platforms Will Decrease Time-to-Value
While AIOps platforms are meant to handle added complexity, humans are still required to configure and
deploy them. Next year, AIOps capabilities will become more mainstream within products. SaaS
products, in particular, will improve significantly with better actionable insights and new proactive
capabilities within the product. This advancement will set the foundation for future integrated self-healing
systems, which will further reduce the burden on human teams.
Properly educating employees on AIOps platforms also affects time-to-value. AIOps platforms are most
efficient when they are managed by the right team. Investing in AIOps just to say you have it doesn’t add
value to the business if IT isn’t sure how to use AIOps. Build a team that is cross-functional between the
business, data owners, and engineers. Together, these three pillars will be able to derive real value out
of any AIOps initiative.
I constantly see organizations driving initiatives tied to buzzwords instead of a real business problem.
AIOps is about solving complex business problems, and, therefore, IT teams should identify the problems
they want to overcome before diving in headfirst. Once that is understood across the board, solving
problems using AI becomes easier. If organizations do not follow this basic advice, they will likely remain
in a state of AI immaturity and will spend significant amounts of time on failed projects.
Cyber Defense eMagazine – January 2021 Edition 28
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