SILVA, I. S.; http://lattes.cnpq.br/8800276401663245; SILVA, Ítallo de Sousa.
Abstract:
Several works covered the characterization of web servers’ workload.
These works resulted in a compilation of patterns called invariants,
i.e., recurrent observations seen in multiple servers. Although
some of these works focused on ecommerce systems, they analyzed
data from small store servers within a short timespan in the late
90s and early 2000s. Thus, this work proposed a workload characterization
of a multinational ecommerce company server and its
comparison with the previous invariants found in the literature.
We found that some patterns, such as the presence of peaks and
valleys in the arrival rate distribution over time and its relation with
the working hours of the day, continue to be present in modern
ecommerce servers. Meanwhile, others have diminished or disappeared,
such as the correlation between the arrival rate and the
latency. We also conducted analyses not found in the literature,
such as the impact of Black Friday on the server workload and
the analysis of two new metrics: surge queue length and spillover
count. We found a higher arrival rate during Black Friday than
on typical days, a skewed distribution for surge queue length, and
an association between the spillover count and high queue length
values and latency.
