diff --git a/samples/notebooks/KubeFlow Pipeline Using TFX OSS Components.ipynb b/samples/notebooks/KubeFlow Pipeline Using TFX OSS Components.ipynb
index 20140537808..caa68c93f38 100644
--- a/samples/notebooks/KubeFlow Pipeline Using TFX OSS Components.ipynb	
+++ b/samples/notebooks/KubeFlow Pipeline Using TFX OSS Components.ipynb	
@@ -31,7 +31,10 @@
    "outputs": [],
    "source": [
     "# Install Pipeline SDK\n",
-    "!pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.1/kfp.tar.gz --upgrade"
+    "!pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.1/kfp.tar.gz --upgrade\n",
+    "    \n",
+    "# Component building requires this package. For now you need to install it explicitly.\n",
+    "!pip3 install kubernetes"
    ]
   },
   {
@@ -84,15 +87,63 @@
     "# Note that this notebook should be running in JupyterHub in the same cluster as the pipeline system.\n",
     "# Otherwise it will fail to talk to the pipeline system.\n",
     "client = kfp.Client()\n",
-    "exp = client.create_experiment(name='demo_exp')\n",
-    "# See Screenshot 1"
+    "exp = client.create_experiment(name='demo')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Test Run a Pipeline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Copying gs://ml-pipeline-playground/coin.tar.gz...\n",
+      "/ [1 files][  978.0 B/  978.0 B]                                                \n",
+      "Operation completed over 1 objects/978.0 B.                                      \n"
+     ]
+    }
+   ],
+   "source": [
+    "# Download a pipeline package\n",
+    "!gsutil cp gs://ml-pipeline-playground/coin.tar.gz ."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "Job link <a href=\"/pipeline/#/runs/details/97280443-e3ae-11e8-860c-42010a800274\" target=\"_blank\" >here</a>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "run = client.run_pipeline(exp.id, 'coin', 'coin.tar.gz')"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Define a Pipeline with OSS TFX components\n",
+    "## Define a Pipeline\n",
     "\n",
     "Authoring a pipeline is just like authoring a normal Python function. The pipeline function describes the topology of the pipeline. Each step in the pipeline is typically a ContainerOp --- a simple class or function describing how to interact with a docker container image. In the below pipeline, all the container images referenced in the pipeline are already built. The pipeline starts with a TFDV step which is used to infer the schema of the data. Then it uses TFT to transform the data for training. After a single node training step, it analyze the test data predictions and generate a feature slice metrics view using a TFMA component. At last, it deploys the model to TF-Serving inside the same cluster."
    ]
@@ -270,12 +321,13 @@
     }
    ],
    "source": [
+    "# Compile it into a tar package.\n",
     "compiler.Compiler().compile(taxi_cab_classification,  'tfx.tar.gz')\n",
     "\n",
+    "# Submit a run.\n",
     "run = client.run_pipeline(exp.id, 'tfx', 'tfx.tar.gz',\n",
     "                          params={'output': OUTPUT_DIR,\n",
-    "                                  'project': PROJECT_NAME})\n",
-    "# See Screenshot 2"
+    "                                  'project': PROJECT_NAME})"
    ]
   },
   {
@@ -583,8 +635,7 @@
     "run = client.run_pipeline(exp.id, 'my-tfx', 'my-tfx.tar.gz',\n",
     "                          params={'output': OUTPUT_DIR,\n",
     "                                  'project': PROJECT_NAME,\n",
-    "                                  'model': 'mytaxi.beta'})\n",
-    "# See screenshot 3"
+    "                                  'model': 'mytaxi.beta'})"
    ]
   },
   {