Cheap computation and storage mean many impossible operations have become practical. Use of millimeter wave frequencies for commercial end user communications is among the salient examples, but enterprise ability to capture and process nearly all data generated by the enterprise, for the purpose of wringing insights out of that data provides another example.
According to Cisco, companies can expect to see their network traffic triple by 2022. “This will require organizations to make a proportional increase in data storage and maintain a brute force, record-everything approach for network forensics that will cost companies significantly more in terms of time and money,” says Randy Caldejon, CounterFlow CEO.
AIOps plays a key role here, he argues. “Full packet capture is finally entering the age of practicality because of the introduction of AIOps,” he argues.
“Thanks to AIOps, security analysts now have an opportunity to utilize more open source technologies and experiment with ML and AI to make packet capture work better for them and their organization,” he says. “Before, it was unrealistic to expect a group of analysts in a security operations center to proactively ferret through petabytes of data in search of an anomaly.”
Gartner defines AIOps as the application of machine learning (ML) and data science to IT operations problems. The firm also predicts that large enterprises use of AIOps tools will reach 30 percent by 2023.
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