A Digital-Twin Workflow for Recovery Testing in Cloud-Hosted Engineering Services

Abstract

Cloud engineering services depend on storage replicas, simulation files and external interfaces whose failure order is often poorly documented. The difficulty is particularly visible when a system is transferred to a new setting. To address this, the study will evaluate an inspectable digital twin for rehearsing dependency-aware service recovery. The research design centres on a scenario-based systems-design study with a dependency graph, synthetic faults and operator-reviewed restoration steps. The choice of evaluation units and exclusion criteria is informed by the broader methodological record [3–7]. The analysis will contrast traditional runbook recovery and recovery supported by a transparent discrete-event digital twin. The design prioritises precise operational definitions and a straightforward baseline before introducing more complex alternatives. Related enterprise-storage studies inform the assessment of operational reliability [1] and the deployment assumptions adopted for system-level comparison [2]. Assessment will focus on recovery-order correctness, time to validated service restoration and missed dependency counts. The supporting evidence base motivates the chosen comparator conditions and robustness criteria [8–12]. Critical sensitivity checks address unobserved links, incomplete topology, correlated outages and potential overconfidence in simulation output. Further systems and modelling literature supplies context for the proposed sensitivity analyses [13–17]. Primary analyses would be reported by the main deployment or participant subgroup so that averaged results do not conceal systematic failures. The expected output is a reusable evaluation framework with transparent uncertainty and reporting rules, informed by wider reproducibility literature [18–23].