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%.
@article{arxiv.2210.02589,
title = {Spot-on: A Checkpointing Framework for Fault-Tolerant Long-running Workloads on Cloud Spot Instances},
author = {Ashley Tung and Haiyan Wang and Yue Li and Zhong Wang and Jingchao Sun},
journal= {arXiv preprint arXiv:2210.02589},
year = {2022}
}
Comments
3 pages, 3 figures, accepted to "Third International Symposium on Checkpointing for Supercomputing (SuperCheck-SC22) https://supercheck.lbl.gov/