Who limits the resource efficiency of my datacenter an analysis of Alibaba datacenter traces

Cloud platform provides great flexibility and cost-efficiency for end-users and cloud operators. However, low resource utilization in modern datacenters brings huge wastes of hardware resources and infrastructure investment. To improve resource utilization, a straightforward way is co-locating diffe...

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Vydané v:Proceedings of the International Symposium on Quality of Service s. 1 - 10
Hlavní autori: Guo, Jing, Chang, Zihao, Wang, Sa, Ding, Haiyang, Feng, Yihui, Mao, Liang, Bao, Yungang
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: New York, NY, USA ACM 24.06.2019
Edícia:ACM Other Conferences
Predmet:
cloud computing
Computer systems organization > Architectures > Distributed architectures > Cloud computing
datacenter
Resource efficiency
cloud computing
resource efficiency
datacenter
ISBN:9781450367783, 145036778X
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Shrnutí:Cloud platform provides great flexibility and cost-efficiency for end-users and cloud operators. However, low resource utilization in modern datacenters brings huge wastes of hardware resources and infrastructure investment. To improve resource utilization, a straightforward way is co-locating different workloads on the same hardware. To figure out the resource efficiency and understand the key characteristics of workloads in co-located cluster, we analyze an 8-day trace from Alibaba's production trace. We reveal three key findings as follows. First, memory becomes the new bottleneck and limits the resource efficiency in Alibaba's datacenter. Second, in order to protect latency-critical applications, batch-processing applications are treated as second-class citizens and restricted to utilize limited resources. Third, more than 90% of latency-critical applications are written in Java applications. Massive self-contained JVMs further complicate resource management and limit the resource efficiency in datacenters.
ISBN:9781450367783
145036778X
DOI:10.1145/3326285.3329074