The characteristics of composite materials are inherently multiscale, with uncertainties occurring throughout all scales. Reliability-based design is often implemented to allow input uncertainties to directly influence the component reliability. The computational cost required for generating each iteration leads to the use of hierarchical multiscale frameworks to propagate effective properties from the microscale to the macroscale. This improves efficiency by neglecting failure at the microscale and using macroscale failure criterion [1], or focusing on stiffness-related failure [2]. The developed framework implements Onset Theory [3], previously known as Strain Invariant Failure Theory (SIFT), with an offline database of randomly generated representative volume elements (RVEs). This allows for failure to be considered at the microscale, while effective properties are propagated to the macroscale, leading to a concurrent-style approach. Techniques and methods are employed to reduce computational cost by predetermining failure sites in the RVEs. This allows for efficient online reliability analysis of unidirectional fibre reinforced composites (FRCs), while considering multiscale uncertainties. The framework will be presented with several examples to investigate its applicability to different macroscale models. [1] G. das Neves Carneiro and C.C. Antonio, Reliability-based Robust Design Optimization with the Reliability Index Approach applied to composite laminate structures, Compos. Struct., Vol. 209, pp. 844–855, 2019 [2] S.L. Omairey, P.D. Dunning, S. Sriramula, Multiscale surrogate-based framework for reliability analysis of unidirectional FRP composites, Compos. B. Eng., Vol. 173, 2019 [3] D.L. Buchanan et al., Micromechanical enhancement of the macroscopic strain state for advanced composite materials, Compos. Sci. Technol., Vol. 69, 2009