  We study deterministic online embeddings of metrics spaces into normed spaces
and into trees against an adaptive adversary. Main results include a polynomial
lower bound on the (multiplicative) distortion of embedding into Euclidean
spaces, a tight exponential upper bound on embedding into the line, and a
$(1+\epsilon)$-distortion embedding in $\ell_\infty$ of a suitably high
dimension.
