In recent years, datacenter architectures have been significantly reshaped by the convergence of high-speed networks and the limitations of Moore's Law. This evolution necessitates new strategies to enhance the performance and scalability of distributed systems. Traditional CPU-centric optimizations are increasingly inadequate, leading to the exploration of hardware offload solutions such as RDMA (Remote Direct Memory Access) and SmartNICs. This thesis investigates the integration of RDMA-based network offloads and addresses the challenges of adapting distributed protocols to leverage these technologies effectively. We introduce PRISM, a novel RDMA interface designed for efficient offloading of distributed systems, and propose SLIM (Shared Log Interface to Memory), a simplified log API that bridges the abstraction gap between distributed programming models and specialized hardware accelerators. SLIM offers a higher-level instantiation of the traditional shared memory model, aiming to enhance programming outcomes by providing a more intuitive and effective approach to reasoning about concurrency and consistency in complex RDMA-based offloads.