Why Liquid Software Needs A Stiffer Data Posture
Summary
While the code structures and architecture beneath our applications and data services are actually “liquifying” in the sense that they are becoming more modular, disaggregated and individually componentized (into finer droplets, so to speak), the IT industry is working hard to solidify the outer surface of our technology to prevent outages, to combat malware and to take arms against a sea of troubles caused by cloud network misconfigurations and so on. Using the massive scope for reasoning and learning offered by AI, we can create software functions that exhibit predictive and causal knowledge in order to protect our IT assets more quickly and more comprehensively. In terms of practical usage, a clean room should be implemented as a trusted environment where data and code analysts examine digital evidence related to incidents, breaches, or system events that would broadly be ranked as negative, unwanted and potentially harmful. With budgets always a challenge and the spectre of waning skills failing to keep pace with the speed of AI being used for negative purposes, it is perhaps obligatory for organizations to use this same breed of technology for the greater good - and this action is of course what Cohesity is trying to champion. Using security context as the input stream for generative AI and complementing this with multiple sources including threat hunting scans, ransomware detection, data risk and posture, users can receive an alert to flag anomalous behavior.