An empirical analysis of Amazon EC2 spot instance features affecting cost-effective resource procurement

Cheng Wang, Qianlin Liang, Bhuvan Urgaonkar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Many cost-conscious public cloud workloads ("tenants") are turning to Amazon EC2's spot instances because, on average, these instances offer significantly lower prices (up to 10 times lower) than on-demand and reserved instances of comparable advertized resource capacities. To use spot instances effectively, a tenant must carefully weigh the lower costs of these instances against their poorer availability. Towards this, we empirically study four features of EC2 spot instance operation that a cost-conscious tenant may find useful to model. Using extensive evaluation based on both historical and current spot instance data, we show shortcomings in the state-of-the-art modeling of these features that we overcome. Our analysis reveals many novel properties of spot instance operation some of which offer predictive value while others do not. Using these insights, we design predictors for our features that offer a balance between computational efficiency (allowing for online resource procurement) and cost-efficacy. We explore "case studies" wherein we implement prototypes of dynamic spot instance procurement advised by our predictors for two types of workloads. Compared to the state-of-the-art, our approach achieves (i) comparable cost but much better performance (fewer bid failures) for a latency-sensitive in-memory Memcached cache, and (ii) an additional 18% cost-savings with comparable (if not better than) performance for a delay-tolerant batch workload.

Original languageEnglish (US)
Title of host publicationICPE 2017 - Proceedings of the 2017 ACM/SPEC International Conference on Performance Engineering
PublisherAssociation for Computing Machinery, Inc
Pages63-74
Number of pages12
ISBN (Electronic)9781450344043
DOIs
StatePublished - Apr 17 2017
Event8th ACM/SPEC International Conference on Performance Engineering, ICPE 2017 - L'Aquila, Italy
Duration: Apr 22 2017Apr 26 2017

Publication series

NameICPE 2017 - Proceedings of the 2017 ACM/SPEC International Conference on Performance Engineering

Other

Other8th ACM/SPEC International Conference on Performance Engineering, ICPE 2017
CountryItaly
CityL'Aquila
Period4/22/174/26/17

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Software
  • Computer Science Applications

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