TY - GEN
T1 - BurScale
T2 - 10th ACM Symposium on Cloud Computing, SoCC 2019
AU - Baarzi, Ataollah Fatahi
AU - Zhu, Timothy
AU - Urgaonkar, Bhuvan
N1 - Funding Information:
This research is supported by the National Science Foundation under Grant No. CNS-1717571 and an AWS research credit award. We also thank Sudipto Das for helping shepherd our paper.
Publisher Copyright:
© 2019 ACM.
PY - 2019/11/20
Y1 - 2019/11/20
N2 - Cloud providers have recently introduced burstable instances-virtual machines whose CPU capacity is rate limited by token-bucket mechanisms. A user of a burstable instance is able to burst to a much higher resource capacity ("peak rate") than the instance's long-Term average capacity ("sustained rate"), provided the bursts are short and infrequent. A burstable instance tends to be much cheaper than a conventional instance that is always provisioned for the peak rate. Consequently, cloud providers advertise burstable instances as cost-effective options for customers with intermittent needs and small (e.g., single VM) clusters. By contrast, this paper presents two novel usage scenarios for burstable instances in larger clusters with sustained usage. We demonstrate (i) how burstable instances can be utilized alongside conventional instances to handle the transient queueing arising from variability in traffic, and (ii) how burstable instances can mask the VM startup/warmup time when autoscaling to handle flash crowds. We implement our ideas in a system called BurScale and use it to demonstrate cost-effective autoscaling for two important workloads: (i) a stateless web server cluster, and (ii) a stateful Memcached caching cluster. Results from our prototype system show that via its careful combination of burstable and regular instances, BurScale can ensure similar application performance as traditional autoscaling systems that use all regular instances while reducing cost by up to 50%.
AB - Cloud providers have recently introduced burstable instances-virtual machines whose CPU capacity is rate limited by token-bucket mechanisms. A user of a burstable instance is able to burst to a much higher resource capacity ("peak rate") than the instance's long-Term average capacity ("sustained rate"), provided the bursts are short and infrequent. A burstable instance tends to be much cheaper than a conventional instance that is always provisioned for the peak rate. Consequently, cloud providers advertise burstable instances as cost-effective options for customers with intermittent needs and small (e.g., single VM) clusters. By contrast, this paper presents two novel usage scenarios for burstable instances in larger clusters with sustained usage. We demonstrate (i) how burstable instances can be utilized alongside conventional instances to handle the transient queueing arising from variability in traffic, and (ii) how burstable instances can mask the VM startup/warmup time when autoscaling to handle flash crowds. We implement our ideas in a system called BurScale and use it to demonstrate cost-effective autoscaling for two important workloads: (i) a stateless web server cluster, and (ii) a stateful Memcached caching cluster. Results from our prototype system show that via its careful combination of burstable and regular instances, BurScale can ensure similar application performance as traditional autoscaling systems that use all regular instances while reducing cost by up to 50%.
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U2 - 10.1145/3357223.3362706
DO - 10.1145/3357223.3362706
M3 - Conference contribution
AN - SCOPUS:85091803998
T3 - SoCC 2019 - Proceedings of the ACM Symposium on Cloud Computing
SP - 126
EP - 138
BT - SoCC 2019 - Proceedings of the ACM Symposium on Cloud Computing
PB - Association for Computing Machinery
Y2 - 20 November 2019 through 23 November 2019
ER -