Grids are distributed systems that dynamically coordinate a large number of heterogeneous resources to execute large scale projects involving collaborating teams of scientists, high performance computers, massive data stores, high bandwidth networking, and/or scientific instruments like telescopes, and synchrotrons. Failure in grids is arguably inevitable due to the massive scale and the heterogeneity of grid resources, the distribution of these resources over unreliable networks, the complexity of mechanisms that are needed to integrate such resources into a seamless utility, and the dynamic nature of the grid infrastructure that allows continuous changes to happen. In this thesis, we propose the Recovery-Aware Components (RAC) approach. The RAC approach enables a grid application to tolerate failure reactively and proactively at the level of the smallest and independent execution unit of the application. The approach also combines runtime prediction with a proactive fault tolerance strategy. By managing failure at the smallest execution unit, and combining runtime prediction with a proactive fault tolerance strategy, the RAC approach aims at improving the reliability of the grid application with the least overhead possible.