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With the increasing importance of reliability in business and industrial software systems, new techniques of architecture-based reliability engineering are becoming an integral part of the development process. These techniques can assist system architects in evaluating the reliability impact of their design decisions. Architecture-based reliability engineering is only effective if the involved reliability models reflect the interaction and usage of software components and their deployment to potentially unreliable hardware. However, existing approaches either neglect individual impact factors on reliability or hard-code them into formal models, which limits their applicability in component-based development processes. This paper introduces a reliability modeling and prediction technique that considers the relevant architectural factors of software systems by explicitly modeling the system usage profile and execution environment and automatically deriving component usage profiles. The technique offers a UML-like modeling notation whose models are automatically transformed into a formal analytical model. Our work builds upon the Palladio Component Model (PCM), employing novel techniques of information propagation and reliability assessment. We validate our technique with sensitivity analyses and simulation in two case studies. The case studies demonstrate effective support of usage profile analysis and architectural configuration ranking, together with the employment of reliability-improving architecture tactics.