  We consider the {\em multi-shop ski rental} problem. This problem generalizes
the classic ski rental problem to a multi-shop setting, in which each shop has
different prices for renting and purchasing a pair of skis, and a
\emph{consumer} has to make decisions on when and where to buy. We are
interested in the {\em optimal online (competitive-ratio minimizing) mixed
strategy} from the consumer's perspective. For our problem in its basic form,
we obtain exciting closed-form solutions and a linear time algorithm for
computing them. We further demonstrate the generality of our approach by
investigating three extensions of our basic problem, namely ones that consider
costs incurred by entering a shop or switching to another shop. Our solutions
to these problems suggest that the consumer must assign positive probability in
\emph{exactly one} shop at any buying time. Our results apply to many
real-world applications, ranging from cost management in \texttt{IaaS} cloud to
scheduling in distributed computing.
