Governing Data Sovereignty in Distributed Multi-Cloud ML Systems
summary
Multicloud ML faces three major challenges: lawful data residency, full auditability of data movement, and inconsistent regional laws (GDPR, US CLOUD Act, China Cybersecurity Law). Practical controls include ISO 27018, CSA star and NISG 853 for baseline assurance, sovereign cloud zones that localize storage and processing while preserving global scale, a zero trust data model that continuously verifies access, and compliance automation that provides real‑time monitoring and automated audit trails across the ML lifecycle from training to inference to retraining.
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chapters (12)
- 0:00Welcome & What We’ll Cover Today
- 0:22Why Multi-Cloud ML Is Booming (and Getting Harder to Govern)
- 1:57The 3 Big Data Sovereignty Challenges
- 2:35Key Regulations: GDPR, US CLOUD Act, China Cybersecurity Law
- 3:42How Laws Shape Cloud Architecture: Residency + Access Controls
- 4:17Governance Standards to Operationalize Compliance
- 5:06The Data Flow Visibility Gap (and Why Audits Fail)
- 5:41Sovereign Cloud Zones: Local Compliance, Global Scale
- 6:23Zero Trust for Distributed Data Access
- 6:57Compliance Automation That Actually Scales
- 8:04Cross-Region ML Governance Across the Full Lifecycle
- 8:44Closing Takeaways & Final Thoughts
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