Detection Engineering with Google Cloud

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.

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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