Any of the various forms of residuals used in connection with GLMs (raw, Pearson, deviance, Anscombe and even working residuals) can be difficult to interpret visually.
However, broadly speaking, your deviance residuals should be expected to have mean close to 0 and nearly constant variance, when plotted against any predictor, or against fitted values, or even against their index (which usually isn't especially meaningful, unless it represents an ordering in the time the observation was collected or something, in which case it could be quite useful).
In this case, as near as I can discern, you have what looks like mean near 0 against Index.
It can be hard to see where the typical value is in the case of logistic regression (sometimes it may help to consider looking at a smooth of the values for that reason).
If you have not already done so, try