  We consider a generalization of the fundamental online metrical service
systems (MSS) problem where the feasible region can be transformed between
requests. In this problem, which we call T-MSS, an algorithm maintains a point
in a metric space and has to serve a sequence of requests. Each request is a
map (transformation) $f_t\colon A_t\to B_t$ between subsets $A_t$ and $B_t$ of
the metric space. To serve it, the algorithm has to go to a point $a_t\in A_t$,
paying the distance from its previous position. Then, the transformation is
applied, modifying the algorithm's state to $f_t(a_t)$. Such transformations
can model, e.g., changes to the environment that are outside of an algorithm's
control, and we therefore do not charge any additional cost to the algorithm
when the transformation is applied. The transformations also allow to model
requests occurring in the $k$-taxi problem.
  We show that for $\alpha$-Lipschitz transformations, the competitive ratio is
$\Theta(\alpha)^{n-2}$ on $n$-point metrics. Here, the upper bound is achieved
by a deterministic algorithm and the lower bound holds even for randomized
algorithms. For the $k$-taxi problem, we prove a competitive ratio of $\tilde
O((n\log k)^2)$. For chasing convex bodies, we show that even with contracting
transformations no competitive algorithm exists.
  The problem T-MSS has a striking connection to the following deep
mathematical question: Given a finite metric space $M$, what is the required
cardinality of an extension $\hat M\supseteq M$ where each partial isometry on
$M$ extends to an automorphism? We give partial answers for special cases.
