Federated Security Control Data Fabric: Scalable Telemetry Normalization and Orchestration in Multi-Cloud Environments

Abstract

The adoption of multi-cloud architectures has fundamentally reshaped enterprise security operations, introducing unprecedented complexity in managing controls across heterogeneous environments. Traditional security paradigms built around centralized log collection through Security Information and Event Management (SIEM) and Security Orchestration and Automation Platforms(SOAR) struggle to scale economically and operationally when confronted with distributed cloud-native telemetry. Organizations now operate across multiple public cloud providers, each emitting high-volume preventive, detective, and remediative control telemetry in proprietary schemas. The financial cost of data egress and the processing delays introduced by centralized aggregation undermine real-time threat detection, while provider-specific visibility creates blind spots that sophisticated adversaries can exploit.

This paper proposes the Federated Security Control Data Fabric (F-SCDF) as a distributed-first architectural framework for multi-cloud security telemetry. The fabric keeps telemetry processing close to its source while enabling unified semantic interpretation and cross-environment orchestration. Distributed ingestion gateways perform local normalization, enrichment, and filtering to minimize data egress and accelerate event availability. A universal security control schema and semantic mapping registry provide consistent interpretation of heterogeneous events, while a federated lakehouse architecture enables unified querying across source environments without requiring centralized storage. An AI-driven signal prioritization broker applies machine learning models to suppress noise, risk-score events, and feed downstream orchestration systems with actionable intelligence rather than raw alert volume.The F-SCDF architecture delivers vendor-agnostic security operations that align economic efficiency with real-time detection requirements, providing a scalable foundation for protecting distributed enterprise assets as multi-cloud complexity and telemetry volume continue to grow.