A Cloud-Native Reference Architecture for Governed Observability and Explainable Operational Intelligence

Abstract

Enterprise observability today is assembled from disconnected tools for collection, storage, visualization, and automated operations, leaving governance, lineage, and explainability fragmented across the telemetry lifecycle. This paper presents a cloud-native reference architecture that treats operational telemetry as a governed enterprise asset rather than a byproduct of individual tools. The architecture specifies layered telemetry acquisition, event-driven processing, a governed telemetry lakehouse, and an Operational Intelligence Engine that produces anomaly detection, incident correlation, root cause support, and forecasting outputs, each accompanied by an auditable explanation artifact rather than an opaque recommendation. Governance, meaning catalog, schema, lineage, and policy, is embedded directly into the processing path rather than layered on afterward, and high-impact automated actions default to human approval. The architecture is evaluated through a methodology intended for implementers, including a disclosed simulation study that illustrates how governance-aware correlation degrades gracefully under incomplete metadata where rule-based approaches degrade sharply. The contribution is systems integration and governance contracts for trustworthy operational intelligence, not a new instrumentation standard or a single detection model. Enterprises adopting this architecture can expect clearer accountability for automated operational decisions, improved ability to reconstruct incident history, and a practical path toward observability practices that satisfy both operational and audit requirements as cloud-native estates continue to grow in scale and complexity.