![](bg7.png)
ble to observe that Amazon instance presented bet-
ter performance in all cases, compared with instance
Google. Due to the inherent characteristics of cloud
environments, this results may change within certain
limits when we chose different service/billing plans,
so this remain to be investigated. Also, it may be use-
ful to gather more performance metrics from specific
cases of Moodle usage, according to the characteris-
tics of each educational institution. To encourage re-
productibility and further work, we made our data and
scripts available in a public repository.
Our choice of a IaaS service model granted us au-
tonomy to install different benchmarks and to perform
measurements directly from our instances. This may
not be possible when Moodle is provided in a SaaS
model, but such alternative still deserves to be inves-
tigated. Obviously, performance is not the only fac-
tor when deciding to migrate Moodle to the cloud,
but simplicity and cost effectiveness are useless when
we are not sure how the system will perform under a
cloud environment.
As a suggestion of future work, it is intended to
conduct experiments with other cloud providers not
contemplated in the study, use other benchmarks for
performance evaluation. Another important aspect is
the possibility, if there are financial resources, to per-
form the cost-benefit comparison on a paid way. For
the customer, may need to hire a service that performs
best, but that fits within your budget.
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