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dc.contributor.advisorMadden, Samuel R.
dc.contributor.authorLi, Tianyu
dc.date.accessioned2025-11-25T19:38:44Z
dc.date.available2025-11-25T19:38:44Z
dc.date.issued2025-05
dc.date.submitted2025-08-14T19:40:49.137Z
dc.identifier.urihttps://hdl.handle.net/1721.1/164049
dc.description.abstractModern cloud applications are often distributed systems composed from vendor-provided building blocks (e.g., object storage services, container orchestration services). Consequently, distributed fault-tolerance is a central concern for application correctness. Although each building block may offer individual fault-tolerance, the end-to-end application is still susceptible to failures, because the composition logic that orchestrates them may still fail. This thesis explores resilient composition, a systematic way to assemble fault-tolerant components into resilient end-to-end distributed applications. We begin by presenting the fail-restart system model, which captures the unique fault-tolerance challenges that arise when composing services. Based on this model, we define Composable Resilient Steps (CReSt), an atomic programming abstraction that guarantees fault-tolerance across the assembled application. We then detail efficient methods for implementing CReSt using a range of database techniques, and a novel distributed protocol that allow optimistic, speculative execution ahead of slower fault-tolerance safeguards. Together, these pieces allow developers to assemble fault-tolerant distributed systems that are correct by construction and often more performant than existing solutions.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright retained by author(s)
dc.rights.urihttps://rightsstatements.org/page/InC-EDU/1.0/
dc.titlePerformant and Resilient Service Composition for Modern Cloud Applications
dc.typeThesis
dc.description.degreePh.D.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
mit.thesis.degreeDoctoral
thesis.degree.nameDoctor of Philosophy


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