diff --git a/.travis.yml b/.travis.yml
index 35d31f2b..f470f05c 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -67,6 +67,6 @@ deploy:
   on:
     #tags: true
     branch: plot_density
-  #server: https://testpypi.python.org/pypi
+  server: https://testpypi.python.org/pypi
   distributions: "bdist_wheel sdist"
   skip_cleanup: true
diff --git a/GPy/__version__.py b/GPy/__version__.py
index 21311fc4..01fef660 100644
--- a/GPy/__version__.py
+++ b/GPy/__version__.py
@@ -1 +1 @@
-__version__ = "0.8.8dev0"
+__version__ = "0.8.8dev2"
diff --git a/GPy/plotting/__init__.py b/GPy/plotting/__init__.py
index 8f82720e..28c05cef 100644
--- a/GPy/plotting/__init__.py
+++ b/GPy/plotting/__init__.py
@@ -84,6 +84,11 @@ if config.get('plotting', 'library') is not 'none':
 
     from ..kern import Kern
     Kern.plot_covariance = gpy_plot.kernel_plots.plot_covariance
+    def deprecate_plot(self, *args, **kwargs):
+        import warnings
+        warnings.warn(DeprecationWarning('Kern.plot is being deprecated and will not be available in the 1.0 release. Use Kern.plot_covariance instead'))
+        return self.plot_covariance(*args, **kwargs)
+    Kern.plot = deprecate_plot
     Kern.plot_ARD = gpy_plot.kernel_plots.plot_ARD
 
     from ..inference.optimization import Optimizer
diff --git a/GPy/plotting/gpy_plot/kernel_plots.py b/GPy/plotting/gpy_plot/kernel_plots.py
index daae15b8..01796d84 100644
--- a/GPy/plotting/gpy_plot/kernel_plots.py
+++ b/GPy/plotting/gpy_plot/kernel_plots.py
@@ -136,6 +136,4 @@ def plot_covariance(kernel, x=None, label=None,
         return pl().add_to_canvas(canvas, plots)
 
     else:
-        raise NotImplementedError("Cannot plot a kernel with more than two input dimensions")
-
-    pass
\ No newline at end of file
+        raise NotImplementedError("Cannot plot a kernel with more than two input dimensions")
\ No newline at end of file
diff --git a/doc/source/tuto_plotting.rst b/doc/source/tuto_plotting.rst
index adf00b66..8da53135 100644
--- a/doc/source/tuto_plotting.rst
+++ b/doc/source/tuto_plotting.rst
@@ -89,3 +89,57 @@ meanplot_1d, which we are for the 1d plot::
 
 The full definition of the plotting then looks like this::
 
+    if len(free_dims)<=2:
+        if len(free_dims)==1:
+            # 1D plotting:
+            update_not_existing_kwargs(kwargs, pl().defaults.meanplot_1d)  # @UndefinedVariable
+            plots = dict(covariance=[pl().plot(canvas, Xgrid[:, free_dims], K, label=label, **kwargs)])
+        else:
+            if projection == '2d':
+                update_not_existing_kwargs(kwargs, pl().defaults.meanplot_2d)  # @UndefinedVariable
+                plots = dict(covariance=[pl().contour(canvas, xx[:, 0], yy[0, :],
+                                               K.reshape(resolution, resolution),
+                                               levels=levels, label=label, **kwargs)])
+            elif projection == '3d':
+                update_not_existing_kwargs(kwargs, pl().defaults.meanplot_3d)  # @UndefinedVariable
+                plots = dict(covariance=[pl().surface(canvas, xx, yy,
+                                               K.reshape(resolution, resolution),
+                                               label=label,
+                                               **kwargs)])
+        return pl().add_to_canvas(canvas, plots)
+
+    else:
+        raise NotImplementedError("Cannot plot a kernel with more than two input dimensions")
+
+Where we return whatever is returned by :py:func:`GPy.plotting.abstract_plotting_library.AbstractPlottingLibrary.add_to_canvas`,
+so that the plotting library can choose what to do with the plot later, when we want to show it. In order
+to show a plot, we can just call :py:func:`GPy.plotting.show` with the output of the plot above.
+
+Now we want to add the plot to the :py:class:`GPy.kern.src.kern.Kern`. In order to do that, we inject the plotting function into the
+class in the :py:mod:`GPy.plotting.__init__`, which will make sure that the on the fly change of the backend
+works smoothly. Thus, in :py:mod:`GPy.plotting.__init__` we add the line::
+
+    from ..kern import Kern
+    Kern.plot_covariance = gpy_plot.kernel_plots.plot_covariance
+
+And that's it. The plot can be shown in plotly by calling::
+
+    GPy.plotting.change_plotting_library('plotly')
+
+    k = GPy.kern.RBF(1) + GPy.kern.Matern32(1)
+    k.randomize()
+    fig = k.plot()
+    GPy.plotting.show(fig, <plot_library specific **kwargs>)
+
+    k = GPy.kern.RBF(2) + GPy.kern.Matern32(2)
+    k.randomize()
+    fig = k.plot()
+    GPy.plotting.show(fig, <plot_library specific **kwargs>)
+
+    k = GPy.kern.RBF(1) + GPy.kern.Matern32(2)
+    k.randomize()
+    fig = k.plot(projection='3d')
+    GPy.plotting.show(fig, <plot_library specific **kwargs>)
+
+This explains the next thing. Changing the backend works *on-the-fly*. To show the above example in matplotlib, we just
+exchange the first line by ``GPy.plotting.change_plotting_library('matplotlib')``.
diff --git a/setup.cfg b/setup.cfg
index d79d8bbd..35cc840c 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.8.8dev0
+current_version = 0.8.8dev2
 tag = True
 commit = True