Background: The retail sector faces intense pressure to ensure high availability and low latency, especially during peak traffic events. However, many established retailers operate on complex, monolithic legacy infrastructures that are inherently resistant to modern DevOps practices. Site Reliability Engineering (SRE), pioneered in cloud-native environments, offers a compelling model for managing reliability, yet its application in 'brownfield' legacy contexts is poorly understood.

Objectives: This study aims to (1) analyze the socio-technical friction points when implementing SRE principles within legacy retail organizations and (2) propose and evaluate a phased framework for this transition.

Methods: We employed a qualitative, multi-case study methodology, analyzing three anonymized retail organizations (grocery, e-commerce, department store) undergoing SRE adoption. Data was collected through 30 semi-structured interviews with engineering and leadership staff, supplemented by an analysis of internal documentation (postmortems, roadmaps, and monitoring data). We analyzed these cases through the lens of a proposed three-phase implementation framework: (1) Stabilize & Observe, (2) Automate & Abstract, and (3) Modernize & Scale.

Results: The findings indicate that the most significant barriers are cultural rather than technical, particularly the resistance to blameless postmortems and the adoption of error budgets. Defining meaningful Service Level Objectives (SLOs) for monolithic applications emerged as a complex initial hurdle. However, the study found that SRE-derived data (SLO breach reports, toil logs) provided a critical, objective language for prioritizing technical debt and de-risking modernization efforts, such as API abstraction and the introduction of new microservices.

Conclusion: SRE is a viable and necessary strategy for legacy retail, acting as a catalyst for incremental modernization. Successful adoption hinges on adapting SRE principles, prioritizing cultural change alongside technical automation, and using SRE metrics to bridge the divide between operations and development.