With the work of Khot and Vishnoi as a starting point, we obtain integrality gaps for certain strong SDP relaxations of Unique Games. Specifically, we exhibit a Unique Games gap instance for the basic semidefinite program strengthened by all valid linear inequalities on the inner products of up to exp(??(log log n)1/4) vectors. For a stronger relaxation obtained from the basic semidefinite program by R rounds of Sherali-Adams liftand-project, we prove a Unique Games integrality gap for R = ??(log log n)1/4. By composing these SDP gaps with UGC-hardness reductions, the above results imply corresponding integrality gaps for every problem for which a UGC-based hardness is known. Consequently, this work implies that including any valid constraints on up to exp(??(log log n)1/4) vectors to natural semidefinite program, does not improve the approximation ratio for any problem in the following classes: constraint satisfaction problems, ordering constraint satisfaction problems and metric labeling problems over constant-size metrics. We obtain similar SDP integrality gaps for Balanced Separator, building on. We also exhibit, for explicit constants ??, ?? > 0, an n-point negative-type metric which requires distortion ??(log log n)?? to embed into ??1, although all its subsets of size exp(??(log log n)??) embed isometrically into ??1.