Hybrid clouds create blind spots, exacerbate the alert fatigue problem, and make it more difficult to detect an intruder’s lateral movements. Artificial intelligence, combined with security graphs, helps organizations fight back.
With nearly all companies adopting a hybrid IT infrastructure strategy, the issue of securing such environments is becoming increasingly urgent. Hybrid cloud environments present numerous challenges for traditional security offerings; however, a solution lies in the use of tools that employ artificial intelligence (AI) and security graphs to map these complex environments and clearly illustrate potential threats.
By the end of 2027, Gartner predicts, 90% of organizations will adopt a hybrid cloud approach.[1] Although good business reasons are behind this shift, including the use of AI technology, hybrid clouds present several challenges from a security perspective.
One is lateral movements, where attackers succeed in breaching network perimeter defenses and then move laterally through a network to find valuable resources. Traditional network detection and response tools generally can’t see across multiple cloud provider networks, making them blind to such lateral movement.
Another major challenge is risk prioritization. Cloud-native application protection platforms (CNAPPs) may seem to offer a solution, but they may struggle to prioritize risks because they lack sufficient business or contextual information.
Lack of prioritization leads to another issue: alert fatigue. Although it is certainly not unique to hybrid cloud environments, the problem is exacerbated by the sheer number of alerts that can come from multiple clouds, on top of those from on-premises infrastructure, and the lack of guidance on how to respond to the alerts effectively.
Finding solutions in security graphs
AI security graphs offer a solution. As discussed in this previous post, AI security graphs are conceptual maps of a network environment that depict transaction flows. The maps provide context that helps organizations understand where they most need security controls. They also enable users to visualize their networks much like intruders do — as a map they follow to find their way to valuable resources.
Because they’re built from a database of all networked elements, no matter where they reside, there are no restrictions on what the maps can depict. Thus, a single security graph can show relationships between resources that reside in different environments.
Conclusion
AI security graphs are at the heart of solutions such as Illumio Insights, a security tool that ingests data flows representing billions of conversations across hybrid cloud environments. Applying AI enables Illumio Insights to detect policy violations in real time, so it can detect attempted attacks on critical resources immediately.
It also enables companies to quickly isolate any resources that are under attack, preventing the lateral movements that intruders rely on to find valuable targets. This compartmentalization, or microsegmentation, is fundamental to the Illumio approach to security — and to protecting hybrid cloud environments.
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[1] “Gartner Forecasts Worldwide Public Cloud End-User Spending to Total $723 Billion in 2025,” November 19, 2024, Gartner.com.
