diff --git a/.travis.yml b/.travis.yml
index 1433b3d61af..9bbbfae3894 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -7,6 +7,7 @@ matrix:
   fast_finish: true
   include:
     - python: "2.7"
+      env: PACKAGES=blosc
     - python: "3.4"
       env: COVERAGE=true
     - python: "3.5"
@@ -15,7 +16,7 @@ matrix:
       sudo: true
       dist: trusty
     - python: "3.5"
-      env: HDFS=true
+      env: HDFS=true PACKAGES=blosc
       sudo: true
       dist: trusty
 
@@ -48,7 +49,7 @@ install:
   # Install dependencies
   - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION
   - source activate test-environment
-  - conda install -q pytest pytest-timeout coverage tornado toolz dill futures dask ipywidgets psutil bokeh requests joblib mock ipykernel jupyter_client h5py netcdf4 lz4 paramiko tblib click -c conda-forge
+  - conda install -q pytest pytest-timeout coverage tornado toolz dill futures dask ipywidgets psutil bokeh requests joblib mock ipykernel jupyter_client h5py netcdf4 lz4 paramiko tblib click $PACKAGES -c conda-forge
   - |
     if [[ $HDFS == true ]]; then
         conda install -q libxml2 krb5 boost
diff --git a/distributed/protocol/numpy.py b/distributed/protocol/numpy.py
index e963d557ca3..224f48d1edc 100644
--- a/distributed/protocol/numpy.py
+++ b/distributed/protocol/numpy.py
@@ -48,7 +48,7 @@ def serialize_numpy_ndarray(x):
               'strides': x.strides,
               'shape': x.shape}
 
-    data = x.view('u1').data
+    data = x.ravel().view('u1').data
 
     if blosc and x.nbytes > 1e5:
         frames = frame_split_size([data])
diff --git a/distributed/protocol/tests/test_numpy.py b/distributed/protocol/tests/test_numpy.py
index 3f23b044111..e8f40a41b25 100644
--- a/distributed/protocol/tests/test_numpy.py
+++ b/distributed/protocol/tests/test_numpy.py
@@ -49,6 +49,8 @@ def test_serialize():
          np.array([(1, 'abc')], dtype=[('x', 'i4'), ('s', object)]),
          np.zeros(5000, dtype=[('x%d'%i,'<f8') for i in range(4)]),
          np.zeros(5000, dtype='S32'),
+         np.zeros((1, 1000, 1000)),
+         np.arange(12)[::2],  # non-contiguous array
          np.ones(shape=(5, 6)).astype(dtype=[('total', '<f8'), ('n', '<f8')])])
 def test_dumps_serialize_numpy(x):
     header, frames = serialize(x)