Advanced digital technologies facilitate real-time and seamless monitoring of diverse data types throughout the operational lifespan of a product. Consequently, utilizing monitored mission data to devise and model novel approaches for managing the product's reliability over its operational lifespan represents an innovative topic. This paper proposes two random warranties from the fresh perspectives, namely random repair back warranty with renewable coverage (RRBW-RC) and random repair front warranty with renewable coverage (RRFW-RC). Extending the concepts from RRBW-RC, this study presents two random renewable replacements based on the RRBW-RC framework for managing product reliability during the post-warranty coverage: bivariate random renewable back replacement (BRRBR) and univariate random renewable back replacement (URRBR). Finally, the numerical results reveals that as mission cycles statistically elongate, the warranty-service cost increases and the related time lengthens for RRFW-RC, while it shows opposite trends for RRBW-RC; the proposed URRFR is unique and feasible.