AI Security In The Cloud-Native DevSecOps Pipeline
Cloud Native Now, Monday, August 25th, 2025
AI is exceedingly good. But the push for greater speed and efficiency clashes directly with the novel security risks that AI itself introduces into the development lifecycle.
As cybersecurity teams use AI to harden defenses, hackers are using it to their advantage. Sophisticated phishing campaigns and adaptive malware are increasingly active dangers for cloud-native applications, compelling a difficult choice for engineering leaders integrating AI into their DevSecOps pipelines.
Because reacting to threats is a lost cause when the attacks themselves are learning and adapting, a proactive stance is essential for survival. This is a mindset embraced by security leaders like Akash Agrawal, VP of DevOps & DevSecOps at LambdaTest, an AI-native software testing platform. He argues for a fundamental shift: 'Security can no longer be bolted on at the end,' he explains. 'AI allows us to move from reactive scanning to proactive prevention.' This approach means using AI not just to identify flaws in committed code, but to predict where the next one might emerge.