Developing an autonomous framework with Security Lake & Torc Robotics
summary
Centralized S3 ingestion via Security Lake automatically enrolls hundreds of AWS accounts and forwards normalized OCSF logs to subscribers like DataDog, removing Torc’s custom collectors and letting the team delete a large maintenance surface. Security Lake compresses and Parquet-converts raw logs (over 90% size reduction), accepts SaaS through AppFabric, and onboarded WAF logs within an hour, while QuickSight Q builds dashboards from Athena/Glue tables for faster, repeatable investigations.
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chapters (21)
- 0:00Introduction and overview
- 1:07Security data lake challenges
- 5:03Open Cybersecurity Schema Framework
- 6:52Security Lake overview and benefits
- 8:36Security Lake architecture and sources
- 10:46Security Lake orchestration and subscribers
- 11:31Security Lake partner ecosystem
- 13:15Security Lake evolution and updates
- 15:27Streamlining security operations
- 17:34Optimizing data storage and movement
- 19:02Live demo introduction
- 20:49QuickSight and generative AI dashboards
- 25:54Torc Robotics introduction
- 28:04Torc Robotics cloud approach
- 30:37Torc Robotics security challenges
- 34:14Why Torc selected Security Lake
- 36:58Torc Robotics Security Lake integration
- 39:09Security Lake benefits for Torc
- 40:56Investigation example with Security Lake
- 42:25Lessons learned and future plans
- 45:35Closing remarks and Q&A
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