"Earlier this year, Amazon Web Services (AWS) announced the availability of the Well‑Architected Data Residency with Hybrid Cloud Services Lens, a new extension of the AWS Well‑Architected Framework aimed at helping organizations design and operate hybrid cloud workloads that must comply with complex data residency and sovereignty requirements. The announcement underscores AWS's growing focus on governance, regulatory compliance, and hybrid operations as enterprises increasingly balance cloud adoption with on‑premises and geopolitical data constraints."
"The Well‑Architected Framework provides architectural best practices across six pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability. The newly published Data Residency with Hybrid Cloud Services (DRHC) Lens delivers prescriptive guidance mapped to each of these pillars, specifically for hybrid environments where data location, legal compliance, and sovereignty policies matter. At its core, the DRHC Lens helps architects and engineering leaders design hybrid cloud workloads that comply with data residency requirements. It guides organizations in classifying workloads and datasets, establishing operational practices for data sovereignty, leveraging AWS regional services to enforce compliance, and applying automation to reduce errors and maintain consistent governance. Applying the lens allows teams to validate their data handling practices and implement actionable recommendations to address gaps."
The Well‑Architected Data Residency with Hybrid Cloud Services (DRHC) Lens provides prescriptive guidance mapped to the six Well‑Architected pillars for hybrid environments governed by data residency and sovereignty requirements. The DRHC Lens helps architects and engineering leaders design hybrid cloud workloads that comply with data residency rules by guiding classification of workloads and datasets, defining operational practices for data sovereignty, leveraging AWS regional services to enforce compliance, and applying automation to reduce errors and maintain consistent governance. The guidance enables validation of data handling practices and implementation of actionable recommendations to address compliance gaps. Four design principles emphasize classification, operational models, regional services, and automation.
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