2022/10/05 by Ashley Tung, Tung, Ashley, Haiyan Wang +7
Computer Science · #Cloud Computing and Resource Management #Distributed #Distributed systems and fault tolerance #FOS: Biological sciences #FOS: Computer and information sciences #Genomics (q-bio.GN) #IoT and Edge/Fog Computing #Parallel #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.2210.02589
openalex publication_date 2022/10/05 · openalex created_date 2022/10/08 · openalex updated_date 2026/07/28
Spot instances offer a cost-effective solution for applications running in the cloud computing environment. However, it is challenging to run long-running jobs on spot instances because they are subject to unpredictable evictions. Here, we present Spot-on, a generic software framework that supports fault-tolerant long-running workloads on spot instances through checkpoint and restart. Spot-on leverages existing checkpointing packages and is compatible with the major cloud vendors. Using a genomics application as a test case, we demonstrated that Spot-on supports both application-specific and transparent checkpointing methods. Compared to running applications using on-demand instances, it allows the completion of these workloads for a significant reduction in computing costs. Compared to running applications using application-specific checkpoint mechanisms, transparent checkpoint-protected applications reduce runtime by up to 40%, leading to further cost savings of up to 86%.