Detection rules aren’t just for fun—they’re critical for securing cloud environments. But are you using them the right way? In this episode, Ashish Rajan sits down with David French, Staff Adoption Engineer for Security at Google Cloud, to break down how organizations can scale Detection as Code across AWS, Azure, and Google Cloud.
- Why prevention isn’t enough—and how detection fills the gap
- The biggest mistakes in detection rules that could blow up your SOC
- How to scale detections across hundreds (or thousands) of cloud accounts
- The ROI of Detection as Code—why security leaders should care
- Common low-hanging fruit detections every cloud security team should implement
David has spent over a decade working in detection engineering, threat hunting, and building SIEM & EDR products. He shares real-world insights on how companies can improve their detection strategies and avoid costly security missteps.
Guest Socials: David's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
If you are interested in AI Cybersecurity, you can check out our sister podcast - AI Cybersecurity Podcast
Questions asked:
(00:00) Introduction
(03:06) What is Detection as Code?
(03:41) What was before Detection as Code?
(05:36) Business ROI for doing Detection as Code?
(07:49) Building Security Operations in Google Cloud
(12:41) Threat Detection for different type of workload
(14:54) What is Google SecOps?
(20:36) Different kinds of Detection people can create
(24:46) Scaling Detection across many Google Cloud accounts
(28:47) The role of Data Pipeline in Detection
(31:44) Detections people can start with
(34:14) Stages of maturity for detection
(36:43) Skillsets for Detection Engineering
(39:32) The Fun Section
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