What would applying AI to operations mean for the security of your company’s IT infrastructure? AIOps are the next big thing in cybersecurity and here’s why. In today’s post, we welcome the latest addition to the rather long chain of IT acronyms and phrases: AIOps. The pleasure is ours. And as it often happens with IT buzzwords on top of their hype cycle, most of us don’t know what they're really about.
So, AIOps, a short way of referring to applying AI to IT operations, encompasses a vast territory and coming up with one singular definition of the term is complicated. In its Market Guide for AIOps Platforms, Gartner
defined AIOps as the “marriage of big data and machine learning in IT”. So, in other words, AIOps platforms leverage historical data (big data) and allocate resources to repetitive tasks (machine learning).
All modern enterprises deal with an influx of data, so it has become evident that in addition to a dedicated IT team, the company will need more to properly manage their IT infrastructure. And AiOps could automate a big part of the most mundane tasks that the IT operatives face, leaving them time for more innovative projects.
If combined with IT infrastructure monitoring and applied to cybersecurity, AIOps would be able to predict and detect issues before they are even there. But before we go into more detail about AIOps for Cybersecurity, we would like to share some numbers that reflect the general benefits of using AI in operations.As we discussed in our previous post dedicated to cybersecurity
, and in this case to the threats that have surfaced now that a bigger part of the global workforce is carrying out their tasks remotely, it’s cheaper for your company to spend money proactively than reactively. Meaning, preventing the issues always beats the risks of dealing with the consequences.
It’s in the context of the ever-evolving cyber-threat landscape that AIOps surface as a great approach to tackle cybersecurity challenges. AIOps tools permit the IT team of your company to leverage the automation capabilities of analytics, AI and ML
for advanced threat detection and dealing with insider threats.
AIOps tool is able to determine, in real-time, if a certain activity is benign or suspicious based on the baseline of the system and continually reassessing it from a behavioral perspective.Jumping on board of a new technology that holds such potential should never be done by investing in tools first. Maybe the best way to get started is by identifying the problem
we could solve more efficiently with AIOps. The basic steps to follow are:
1. Set your priorities.
AIOps can be applied to cybersecurity, systems resiliency, IT infrastructure, etc. Put together a team to identify and work on your top priority.
2. Know your data.
Having an overview of the data you have collected and identifying what part of that data is relevant to solving the problem you have set as your priority.
3. Concentrate on a narrower problem area.
It’s recommendable to look at the areas individually to understand where data might not be analyzed or well interpreted. That’s the quickest way to obtaining real benefits.
4. Choose your AIOps platform wisely.
It’s only at this point that you are ready to find your solution among the many AIOps vendors and ITOps tooling vendors.
5. Integrate the AIOps platform into your IT infrastructure.
AIOps tools won't be able to replace all your old tools. Most probably some IT processes will have to be re-engineered and reviewed.
6. Never stop learning and trying new functions.
If anything, it’s a journey and along the way, you might have to rethink teams, processes, and methods. There are no silver bullets, it’s about hard work and learning from your mistakes. But AIOps can definitely be a game-changer for defining the path of your organization.
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