Building a Cloud Data Platform with Security in Mind
summary
Building a cloud-native data platform with security in mind covers how to protect sensitive data in cloud-based analytics and ML pipelines, comparing implementations and best practices on AWS and GCP. The talk reviews cloud security techniques, integration of modern analytics/ML tools, and compliance/privacy requirements across different countries.
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chapters (9)
- 0:00Cloud data platforms intro
- 6:11Cloud API security
- 9:50Service Perimeter Controls
- 15:34Serverless security myths
- 20:52Networking & container security
- 21:13Encryption for compliance
- 24:09Athena Workbooks access
- 28:35Disable public bucket access
- 32:15Q&A
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