diff --git a/doc/source/examples/notebooks.rst b/doc/source/examples/notebooks.rst
index 08a4b1f6a2..c13baeb401 100644
--- a/doc/source/examples/notebooks.rst
+++ b/doc/source/examples/notebooks.rst
@@ -119,7 +119,7 @@ Production Configurations and Integrations
   
    Example Helm Deployments <helm_examples>
    Max gRPC Message Size <max_grpc_msg_size>
-   REST timeouts <rest_timeouts>
+   Configurable timeouts <timeouts>
    Deploy Multiple Seldon Core Operators <multiple_operators>
    Protocol Examples <protocol_examples>
    Custom Protobuf Data Example <customdata_example>
diff --git a/doc/source/examples/rest_timeouts.nblink b/doc/source/examples/timeouts.nblink
similarity index 100%
rename from doc/source/examples/rest_timeouts.nblink
rename to doc/source/examples/timeouts.nblink
diff --git a/doc/source/python/developer_notes.md b/doc/source/python/developer_notes.md
new file mode 100644
index 0000000000..59a10d1cbf
--- /dev/null
+++ b/doc/source/python/developer_notes.md
@@ -0,0 +1,49 @@
+# Development Tips
+
+
+## Running locally for testing
+
+Sometimes it is useful to be able to test your model locally without the need to build image with s2i or docker.
+
+This can be easily done with `seldon-core` as its installed the CLI command that starts the microservice.
+
+Assuming we have a simple model saved in `MyModel.py` file:
+```python
+class MyModel:
+
+    def predict(self, X, features_names=None):
+        """
+        Return a prediction.
+
+        Parameters
+        ----------
+        X : array-like
+        feature_names : array of feature names (optional)
+        """
+        print("Predict called - will run identity function")
+        return X
+```
+
+We can start Seldon Core microservice with
+```bash
+seldon-core-microservice MyModel --service-type MODEL
+```
+
+Then in other terminal we can send `curl` requests to test REST endpoint:
+```bash
+curl http://localhost:9000/api/v1.0/predictions \
+    -H 'Content-Type: application/json' \
+    -d '{"data": {"names": ["input"], "ndarray": ["data"]}}'
+```
+
+
+And assuming that `seldon-core` code is accessible at `${SELDON_CORE_DIR}` we can use `grpcurl` to send gRPC request:
+```bash
+cd ${SELDON_CORE_DIR}/executor/proto && grpcurl \
+    -d '{"data": {"names": ["input"], "ndarray": ["data"]}}' \
+    -plaintext -proto ./prediction.proto  0.0.0.0:5000 seldon.protos.Seldon/Predict
+```
+
+The `grpcurl` tool can be obtained using binaries released on [GitHub](https://github.com/fullstorydev/grpcurl) or using [asdf-vm](https://github.com/asdf-vm/asdf-plugins).
+
+See [Python Server](./python_server.html#configuration) documentation for config options.
diff --git a/doc/source/python/index.rst b/doc/source/python/index.rst
index 27f4b13b7f..2051690ca0 100644
--- a/doc/source/python/index.rst
+++ b/doc/source/python/index.rst
@@ -17,6 +17,6 @@ You can use the following links to navigate the Python seldon-core module:
    Create image with S2I <python_wrapping_s2i.md>
    Create image with a Dockerfile <python_wrapping_docker.md>
    Seldon Python server configuration <python_server.md>
-   Calling the Seldon API with the Seldon Python client <seldon_client.md>   
-   Python API reference <api/modules>   	      
-
+   Calling the Seldon API with the Seldon Python client <seldon_client.md>
+   Python API reference <api/modules>
+   Development Tips <developer_notes>
diff --git a/examples/ambassador/canary/ambassador_canary.ipynb b/examples/ambassador/canary/ambassador_canary.ipynb
index 17325dd1fd..e880031981 100644
--- a/examples/ambassador/canary/ambassador_canary.ipynb
+++ b/examples/ambassador/canary/ambassador_canary.ipynb
@@ -25,7 +25,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Error from server (AlreadyExists): namespaces \"seldon\" already exists\r\n"
+      "Error from server (AlreadyExists): namespaces \"seldon\" already exists\n"
      ]
     }
    ],
@@ -42,7 +42,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Context \"kind-kind\" modified.\r\n"
+      "Context \"kind-seldon\" modified.\n"
      ]
     }
    ],
@@ -72,7 +72,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.5.0-dev'"
+       "'1.6.0-dev'"
       ]
      },
      "execution_count": 4,
@@ -97,7 +97,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -130,14 +130,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "seldondeployment.machinelearning.seldon.io/example created\r\n"
+      "seldondeployment.machinelearning.seldon.io/example created\n"
      ]
     }
    ],
@@ -147,7 +147,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -172,7 +172,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -189,7 +189,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -204,12 +204,12 @@
       "  tensor {\n",
       "    shape: 1\n",
       "    shape: 1\n",
-      "    values: 0.5531305252881753\n",
+      "    values: 0.71309135369705\n",
       "  }\n",
       "}\n",
       "\n",
       "Response:\n",
-      "{'data': {'names': ['proba'], 'tensor': {'shape': [1, 1], 'values': [0.08599584459790496]}}, 'meta': {}}\n"
+      "{'data': {'names': ['proba'], 'tensor': {'shape': [1, 1], 'values': [0.09942988397161616]}}, 'meta': {'requestPath': {'classifier': 'seldonio/mock_classifier:1.6.0-dev'}}}\n"
      ]
     }
    ],
@@ -230,7 +230,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -280,14 +280,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "seldondeployment.machinelearning.seldon.io/example created\r\n"
+      "Warning: kubectl apply should be used on resource created by either kubectl create --save-config or kubectl apply\n",
+      "seldondeployment.machinelearning.seldon.io/example configured\n"
      ]
     }
    ],
@@ -297,13 +298,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Waiting for deployment \"example-canary-0-classifier\" rollout to finish: 0 of 1 updated replicas are available...\n",
       "deployment \"example-canary-0-classifier\" successfully rolled out\n",
       "deployment \"example-main-0-classifier\" successfully rolled out\n"
      ]
@@ -323,7 +325,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -337,15 +339,15 @@
        "  tensor {\n",
        "    shape: 1\n",
        "    shape: 1\n",
-       "    values: 0.08077854180978328\n",
+       "    values: 0.8694648161558428\n",
        "  }\n",
        "}\n",
        "\n",
        "Response:\n",
-       "{'data': {'names': ['proba'], 'tensor': {'shape': [1, 1], 'values': [0.0554153788429373]}}, 'meta': {}}"
+       "{'data': {'names': ['proba'], 'tensor': {'shape': [1, 1], 'values': [0.11433542420010957]}}, 'meta': {'requestPath': {'classifier': 'seldonio/mock_classifier:1.6.0-dev'}}}"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -356,7 +358,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -367,34 +369,41 @@
     "    r = sc.predict(gateway=\"ambassador\",transport=\"rest\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Following checks number of prediction requests processed by default/canary predictors respectively."
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
-    "default_count=!kubectl logs $(kubectl get pod -lseldon-app=example-main -o jsonpath='{.items[0].metadata.name}') classifier | grep \"/predict\" | wc -l "
+    "default_count=!kubectl logs $(kubectl get pod -lseldon-app=example-main -o jsonpath='{.items[0].metadata.name}') classifier | grep \"root:predict\" | wc -l "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
-    "canary_count=!kubectl logs $(kubectl get pod -lseldon-app=example-canary -o jsonpath='{.items[0].metadata.name}') classifier | grep \"/predict\" | wc -l"
+    "canary_count=!kubectl logs $(kubectl get pod -lseldon-app=example-canary -o jsonpath='{.items[0].metadata.name}') classifier | grep \"root:predict\" | wc -l"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.2948717948717949\n"
+      "0.32894736842105265\n"
      ]
     }
    ],
@@ -406,27 +415,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "seldondeployment.machinelearning.seldon.io \"example\" deleted\r\n"
+      "seldondeployment.machinelearning.seldon.io \"example\" deleted\n"
      ]
     }
    ],
    "source": [
     "!kubectl delete -f canary.yaml"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -446,7 +448,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.8.6"
   },
   "varInspector": {
    "cols": {
@@ -479,5 +481,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }
diff --git a/examples/ambassador/headers/ambassador_headers.ipynb b/examples/ambassador/headers/ambassador_headers.ipynb
index 3c5707b353..fc378db4be 100644
--- a/examples/ambassador/headers/ambassador_headers.ipynb
+++ b/examples/ambassador/headers/ambassador_headers.ipynb
@@ -27,7 +27,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Error from server (AlreadyExists): namespaces \"seldon\" already exists\r\n"
+      "Error from server (AlreadyExists): namespaces \"seldon\" already exists\n"
      ]
     }
    ],
@@ -44,7 +44,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Context \"kind-kind\" modified.\r\n"
+      "Context \"kind-seldon\" modified.\n"
      ]
     }
    ],
@@ -74,7 +74,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.5.0-dev'"
+       "'1.6.0-dev'"
       ]
      },
      "execution_count": 4,
@@ -99,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -132,14 +132,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "seldondeployment.machinelearning.seldon.io/example created\r\n"
+      "seldondeployment.machinelearning.seldon.io/example created\n"
      ]
     }
    ],
@@ -149,7 +149,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -174,7 +174,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -191,7 +191,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -206,12 +206,12 @@
       "  tensor {\n",
       "    shape: 1\n",
       "    shape: 1\n",
-      "    values: 0.6683377893898669\n",
+      "    values: 0.43446257172493064\n",
       "  }\n",
       "}\n",
       "\n",
       "Response:\n",
-      "{'data': {'names': ['proba'], 'tensor': {'shape': [1, 1], 'values': [0.0954937100180911]}}, 'meta': {}}\n"
+      "{'data': {'names': ['proba'], 'tensor': {'shape': [1, 1], 'values': [0.07711519385598731]}}, 'meta': {'requestPath': {'classifier': 'seldonio/mock_classifier:1.6.0-dev'}}}\n"
      ]
     }
    ],
@@ -241,7 +241,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -277,14 +277,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "seldondeployment.machinelearning.seldon.io/example-header created\r\n"
+      "seldondeployment.machinelearning.seldon.io/example-header created\n"
      ]
     }
    ],
@@ -294,7 +294,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -319,7 +319,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -334,12 +334,12 @@
       "  tensor {\n",
       "    shape: 1\n",
       "    shape: 1\n",
-      "    values: 0.015688371980047133\n",
+      "    values: 0.6178977707280904\n",
       "  }\n",
       "}\n",
       "\n",
       "Response:\n",
-      "{'data': {'names': ['proba'], 'tensor': {'shape': [1, 1], 'values': [0.052105223663186165]}}, 'meta': {}}\n"
+      "{'data': {'names': ['proba'], 'tensor': {'shape': [1, 1], 'values': [0.09122497185647573]}}, 'meta': {'requestPath': {'classifier': 'seldonio/mock_classifier:1.6.0-dev'}}}\n"
      ]
     }
    ],
@@ -350,16 +350,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
-    "default_count=!kubectl logs $(kubectl get pod -lseldon-app=example-single -o jsonpath='{.items[0].metadata.name}') classifier | grep \"/predict\" | wc -l "
+    "default_count=!kubectl logs $(kubectl get pod -lseldon-app=example-single -o jsonpath='{.items[0].metadata.name}') classifier | grep \"root.predict\" | wc -l "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -384,7 +384,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -399,12 +399,12 @@
       "  tensor {\n",
       "    shape: 1\n",
       "    shape: 1\n",
-      "    values: 0.6339240340443978\n",
+      "    values: 0.4904085439061101\n",
       "  }\n",
       "}\n",
       "\n",
       "Response:\n",
-      "{'data': {'names': ['proba'], 'tensor': {'shape': [1, 1], 'values': [0.0925623293728051]}}, 'meta': {}}\n"
+      "{'data': {'names': ['proba'], 'tensor': {'shape': [1, 1], 'values': [0.08119217418182277]}}, 'meta': {'requestPath': {'classifier': 'seldonio/mock_classifier:1.6.0-dev'}}}\n"
      ]
     }
    ],
@@ -415,16 +415,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
-    "header_count=!kubectl logs $(kubectl get pod -lseldon-app=example-header-single -o jsonpath='{.items[0].metadata.name}') classifier | grep \"/predict\" | wc -l "
+    "header_count=!kubectl logs $(kubectl get pod -lseldon-app=example-header-single -o jsonpath='{.items[0].metadata.name}') classifier | grep \"root.predict\" | wc -l "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -442,14 +442,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "seldondeployment.machinelearning.seldon.io \"example\" deleted\r\n"
+      "seldondeployment.machinelearning.seldon.io \"example\" deleted\n"
      ]
     }
    ],
@@ -459,27 +459,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "seldondeployment.machinelearning.seldon.io \"example-header\" deleted\r\n"
+      "seldondeployment.machinelearning.seldon.io \"example-header\" deleted\n"
      ]
     }
    ],
    "source": [
     "!kubectl delete -f model_with_header.yaml"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -499,7 +492,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.8.6"
   },
   "varInspector": {
    "cols": {
@@ -532,5 +525,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }
diff --git a/examples/ambassador/shadow/ambassador_shadow.ipynb b/examples/ambassador/shadow/ambassador_shadow.ipynb
index 370884fbdb..4905f051d7 100644
--- a/examples/ambassador/shadow/ambassador_shadow.ipynb
+++ b/examples/ambassador/shadow/ambassador_shadow.ipynb
@@ -29,7 +29,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Error from server (AlreadyExists): namespaces \"seldon\" already exists\r\n"
+      "Error from server (AlreadyExists): namespaces \"seldon\" already exists\n"
      ]
     }
    ],
@@ -39,16 +39,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Context \"kind-seldon\" modified.\n"
+     ]
+    }
+   ],
    "source": [
     "!kubectl config set-context $(kubectl config current-context) --namespace=seldon"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -62,16 +70,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'1.5.0-dev'"
+       "'1.6.0-dev'"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -93,7 +101,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -126,14 +134,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "seldondeployment.machinelearning.seldon.io/example created\r\n"
+      "seldondeployment.machinelearning.seldon.io/example configured\n"
      ]
     }
    ],
@@ -143,14 +151,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "deployment \"example-default-0-classifier\" successfully rolled out\r\n"
+      "deployment \"example-default-0-classifier\" successfully rolled out\n"
      ]
     }
    ],
@@ -167,7 +175,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -184,7 +192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -199,12 +207,12 @@
       "  tensor {\n",
       "    shape: 1\n",
       "    shape: 1\n",
-      "    values: 0.6517840856894687\n",
+      "    values: 0.9967112738898524\n",
       "  }\n",
       "}\n",
       "\n",
       "Response:\n",
-      "{'data': {'names': ['proba'], 'tensor': {'shape': [1, 1], 'values': [0.09407343218921792]}}, 'meta': {}}\n"
+      "{'data': {'names': ['proba'], 'tensor': {'shape': [1, 1], 'values': [0.12786654068631786]}}, 'meta': {'requestPath': {'classifier': 'seldonio/mock_classifier:1.6.0-dev'}}}\n"
      ]
     }
    ],
@@ -224,7 +232,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -272,14 +280,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "seldondeployment.machinelearning.seldon.io/example configured\r\n"
+      "seldondeployment.machinelearning.seldon.io/example configured\n"
      ]
     }
    ],
@@ -289,7 +297,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -316,7 +324,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -326,25 +334,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
-    "default_count=!kubectl logs $(kubectl get pod -lseldon-app=example-default -o jsonpath='{.items[0].metadata.name}') classifier | grep \"/predict\" | wc -l "
+    "default_count=!kubectl logs $(kubectl get pod -lseldon-app=example-default -o jsonpath='{.items[0].metadata.name}') classifier | grep \"root.predict\" | wc -l "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
-    "shadow_count=!kubectl logs $(kubectl get pod -lseldon-app=example-shadow -o jsonpath='{.items[0].metadata.name}') classifier | grep \"/predict\" | wc -l "
+    "shadow_count=!kubectl logs $(kubectl get pod -lseldon-app=example-shadow -o jsonpath='{.items[0].metadata.name}') classifier | grep \"root.predict\" | wc -l "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -372,27 +380,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Error from server (NotFound): error when deleting \"model.yaml\": seldondeployments.machinelearning.seldon.io \"example\" not found\r\n"
+      "seldondeployment.machinelearning.seldon.io \"example\" deleted\n"
      ]
     }
    ],
    "source": [
     "!kubectl delete -f model.yaml"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -412,7 +413,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.8.6"
   },
   "varInspector": {
    "cols": {
@@ -445,5 +446,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }
diff --git a/examples/models/mean_classifier/MeanClassifier.py b/examples/models/mean_classifier/MeanClassifier.py
index 0c8ee78b75..f3bbf24214 100644
--- a/examples/models/mean_classifier/MeanClassifier.py
+++ b/examples/models/mean_classifier/MeanClassifier.py
@@ -1,17 +1,24 @@
 import numpy as np
 import math
+import time
+import logging
 
 def f(x):
     return 1/(1+math.exp(-x))
 
 class MeanClassifier(object):
 
-    def __init__(self, intValue=0):
+    def __init__(self, intValue=0, delaySecs=0):
         self.class_names = ["proba"]
-        assert type(intValue) == int, "intValue parameters must be an integer"
+        assert type(intValue) == int, "intValue parameter must be an integer"
         self.int_value = intValue
+        logging.info("intValue set to %d",intValue)
 
-        print("Loading model here")
+        assert type(delaySecs) == int, "delaySecs parameter must be an integer"
+        self.delay_secs = delaySecs
+        logging.info("Delay secs set to %d",delaySecs)
+
+        logging.info("loading model here")
 
         X = np.load(open("model.npy",'rb'), encoding='latin1')
         self.threshold_ = X.mean() + self.int_value
@@ -20,10 +27,14 @@ def _meaning(self, x):
         return f(x.mean()-self.threshold_)
 
     def predict(self, X, feature_names):
-        print(X)
+        logging.info("Input %s",X)
         X = np.array(X)
         assert len(X.shape) == 2, "Incorrect shape"
 
+        if self.delay_secs > 0:
+            logging.info("Delaying %d secs",self.delay_secs)
+            time.sleep(self.delay_secs)
+
         return [[self._meaning(x)] for x in X]
 
     def health_status(self):
diff --git a/notebooks/resources/model_long_timeouts.json b/notebooks/resources/model_long_timeouts.json
index f0d18c3c37..127a43adb2 100644
--- a/notebooks/resources/model_long_timeouts.json
+++ b/notebooks/resources/model_long_timeouts.json
@@ -1,49 +1,24 @@
-{
-    "apiVersion": "machinelearning.seldon.io/v1alpha2",
-    "kind": "SeldonDeployment",
-    "metadata": {
-        "labels": {
-            "app": "seldon"
-        },
-        "name": "model-long-timeout"
-    },
-    "spec": {
-        "annotations": {
-            "deployment_version": "v1",
-	    "seldon.io/rest-timeout":"100000",
-	    "seldon.io/grpc-timeout":"100000"
-        },
-        "name": "long-to",
-        "predictors": [
-            {
-                "componentSpecs": [{
-                    "spec": {
-                        "containers": [
-                            {
-                                "image": "seldonio/mock_classifier:1.5.0-dev",
-                                "imagePullPolicy": "IfNotPresent",
-                                "name": "classifier",
-                                "resources": {
-                                    "requests": {
-                                        "memory": "1Mi"
-                                    }
-                                }
-                            }
-                        ],
-                        "terminationGracePeriodSeconds": 20
-                    }
-                }],
-                "graph": {
-                    "children": [],
-                    "name": "classifier",
-                    "type": "MODEL"
-                },
-                "name": "test",
-                "replicas": 1,
-		"annotations": {
-		    "predictor_version" : "v1"
-		}
-            }
-        ]
-    }
-}
+apiVersion: machinelearning.seldon.io/v1
+kind: SeldonDeployment
+metadata:
+  name: seldon-model
+spec:
+  annotations:
+    seldon.io/rest-timeout: "5000"
+    seldon.io/grpc-timeout: "5000"
+  predictors:
+  - componentSpecs:
+    - spec:
+        containers:
+        - image: seldonio/mock_classifier:1.6.0-dev
+          name: classifier
+    graph:
+      children: []
+      name: classifier
+      type: MODEL
+      parameters:
+      - name: delaySecs
+        type: INT
+        value: "2"       
+    name: example
+    replicas: 1
diff --git a/notebooks/resources/model_short_timeouts.json b/notebooks/resources/model_short_timeouts.json
index 6c76fd9488..5ebe8794a7 100644
--- a/notebooks/resources/model_short_timeouts.json
+++ b/notebooks/resources/model_short_timeouts.json
@@ -1,54 +1,24 @@
-{
-  "apiVersion": "machinelearning.seldon.io/v1alpha2",
-  "kind": "SeldonDeployment",
-  "metadata": {
-    "labels": {
-      "app": "seldon"
-    },
-    "name": "seldon-deployment-example"
-  },
-  "spec": {
-    "annotations": {
-      "project_name": "FX Market Prediction",
-      "deployment_version": "v1",
-      "seldon.io/rest-read-timeout": "1"
-    },
-    "name": "test-deployment",
-    "predictors": [
-      {
-        "componentSpecs": [
-          {
-            "spec": {
-              "containers": [
-                {
-                  "image": "seldonio/mock_classifier:1.0",
-                  "imagePullPolicy": "IfNotPresent",
-                  "name": "classifier",
-                  "resources": {
-                    "requests": {
-                      "memory": "1Mi"
-                    }
-                  }
-                }
-              ],
-              "terminationGracePeriodSeconds": 20
-            }
-          }
-        ],
-        "graph": {
-          "children": [],
-          "name": "classifier",
-          "endpoint": {
-            "type": "REST"
-          },
-          "type": "MODEL"
-        },
-        "name": "fx-market-predictor",
-        "replicas": 1,
-        "annotations": {
-          "predictor_version": "v1"
-        }
-      }
-    ]
-  }
-}
+apiVersion: machinelearning.seldon.io/v1
+kind: SeldonDeployment
+metadata:
+  name: seldon-model
+spec:
+  annotations:
+    seldon.io/rest-timeout: "1000"
+    seldon.io/grpc-timeout: "1000"
+  predictors:
+  - componentSpecs:
+    - spec:
+        containers:
+        - image: seldonio/mock_classifier:1.6.0-dev
+          name: classifier
+    graph:
+      children: []
+      name: classifier
+      type: MODEL
+      parameters:
+      - name: delaySecs
+        type: INT
+        value: "2"       
+    name: example
+    replicas: 1
diff --git a/notebooks/timeouts.ipynb b/notebooks/timeouts.ipynb
index 651d236892..400d9af823 100644
--- a/notebooks/timeouts.ipynb
+++ b/notebooks/timeouts.ipynb
@@ -11,170 +11,302 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "## Prerequisites\n",
+    "\n",
+    "  * Kubernetes cluster with kubectl authorized\n",
+    "  * curl and grpcurl installed\n",
+    "\n",
     "## Setup Seldon Core\n",
     "\n",
-    "Use the setup notebook to [Setup Cluster](https://docs.seldon.io/projects/seldon-core/en/latest/examples/seldon_core_setup.html#Setup-Cluster) with [Ambassador Ingress](https://docs.seldon.io/projects/seldon-core/en/latest/examples/seldon_core_setup.html#Ambassador) and [Install Seldon Core](https://docs.seldon.io/projects/seldon-core/en/latest/examples/seldon_core_setup.html#Install-Seldon-Core). Instructions [also online](https://docs.seldon.io/projects/seldon-core/en/latest/examples/seldon_core_setup.html)."
+    "Use the setup notebook to [Setup Cluster](https://docs.seldon.io/projects/seldon-core/en/latest/examples/seldon_core_setup.html) to setup Seldon Core with an ingress - either Ambassador or Istio.\n",
+    "\n",
+    "Then port-forward to that ingress on localhost:8003 in a separate terminal either with:\n",
+    "\n",
+    " * Ambassador: `kubectl port-forward $(kubectl get pods -n seldon -l app.kubernetes.io/name=ambassador -o jsonpath='{.items[0].metadata.name}') -n seldon 8003:8080`\n",
+    " * Istio: `kubectl port-forward $(kubectl get pods -l istio=ingressgateway -n istio-system -o jsonpath='{.items[0].metadata.name}') -n istio-system 8003:8080`"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 38,
    "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "namespace/seldon created\r\n"
+     ]
+    }
+   ],
    "source": [
-    "Illustration of both REST and gRPC requests. "
+    "!kubectl create namespace seldon"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 39,
    "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Context \"kind-kind\" modified.\r\n"
+     ]
+    }
+   ],
    "source": [
-    "### Short timeouts deployment file\n",
-    "Below is the outputs of the Seldon config file required to set custom timeouts.\n",
-    "\n",
-    "First we'll show how we can set a short lived example by setting the `\"seldon.io/rest-read-timeout\":\"1\"` annotation."
+    "!kubectl config set-context $(kubectl config current-context) --namespace=seldon"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "scrolled": true
-   },
+   "execution_count": 40,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "%%writefile resources/model_short_timeouts.json\n",
-    "{\n",
-    "    \"apiVersion\": \"machinelearning.seldon.io/v1alpha2\",\n",
-    "    \"kind\": \"SeldonDeployment\",\n",
-    "    \"metadata\": {\n",
-    "        \"labels\": {\n",
-    "            \"app\": \"seldon\"\n",
-    "        },\n",
-    "        \"name\": \"seldon-deployment-example\"\n",
-    "    },\n",
-    "    \"spec\": {\n",
-    "        \"annotations\": {\n",
-    "            \"project_name\": \"FX Market Prediction\",\n",
-    "            \"deployment_version\": \"v1\",\n",
-    "\t    \"seldon.io/rest-read-timeout\":\"1\"\n",
-    "        },\n",
-    "        \"name\": \"test-deployment\",\n",
-    "        \"predictors\": [\n",
-    "            {\n",
-    "                \"componentSpecs\": [{\n",
-    "                    \"spec\": {\n",
-    "                        \"containers\": [\n",
-    "                            {\n",
-    "                                \"image\": \"seldonio/mock_classifier:1.0\",\n",
-    "                                \"imagePullPolicy\": \"IfNotPresent\",\n",
-    "                                \"name\": \"classifier\",\n",
-    "                                \"resources\": {\n",
-    "                                    \"requests\": {\n",
-    "                                        \"memory\": \"1Mi\"\n",
-    "                                    }\n",
-    "                                }\n",
-    "                            }\n",
-    "                        ],\n",
-    "                        \"terminationGracePeriodSeconds\": 20\n",
-    "                    }\n",
-    "                }],\n",
-    "                \"graph\": {\n",
-    "                    \"children\": [],\n",
-    "                    \"name\": \"classifier\",\n",
-    "                    \"endpoint\": {\n",
-    "\t\t\t\"type\" : \"REST\"\n",
-    "\t\t    },\n",
-    "                    \"type\": \"MODEL\"\n",
-    "                },\n",
-    "                \"name\": \"fx-market-predictor\",\n",
-    "                \"replicas\": 1,\n",
-    "\t\t\"annotations\": {\n",
-    "\t\t    \"predictor_version\" : \"v1\"\n",
-    "\t\t}\n",
-    "            }\n",
-    "        ]\n",
-    "    }\n",
-    "}"
+    "from IPython.core.magic import register_line_cell_magic\n",
+    "\n",
+    "@register_line_cell_magic\n",
+    "def writetemplate(line, cell):\n",
+    "    with open(line, 'w') as f:\n",
+    "        f.write(cell.format(**globals()))"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 41,
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.6.0-dev'"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "## Seldon Deployment with Short Timeout"
+    "VERSION=!cat ../version.txt\n",
+    "VERSION=VERSION[0]\n",
+    "VERSION"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can then apply this Seldon Deployment file we defined above in the `seldon` namespace."
+    "## Configure Istio\n",
+    "\n",
+    "For this example we will create the default istio gateway for seldon which needs to be called `seldon-gateway`. You can supply your own gateway by adding to your SeldonDeployments resources the annotation `seldon.io/istio-gateway` with values the name of your istio gateway."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [],
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Overwriting resources/seldon-gateway.yaml\n"
+     ]
+    }
+   ],
    "source": [
-    "!kubectl apply -f resources/model_short_timeouts.json -n seldon"
+    "%%writefile resources/seldon-gateway.yaml\n",
+    "apiVersion: networking.istio.io/v1alpha3\n",
+    "kind: Gateway\n",
+    "metadata:\n",
+    "  name: seldon-gateway\n",
+    "  namespace: istio-system\n",
+    "spec:\n",
+    "  selector:\n",
+    "    istio: ingressgateway # use istio default controller\n",
+    "  servers:\n",
+    "  - port:\n",
+    "      number: 80\n",
+    "      name: http\n",
+    "      protocol: HTTP\n",
+    "    hosts:\n",
+    "    - \"*\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "gateway.networking.istio.io/seldon-gateway created\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!kubectl create -f resources/seldon-gateway.yaml -n istio-system"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "And wait until the resource runs correctly."
+    "### Short timeouts deployment file\n",
+    "Below is the outputs of the Seldon config file required to set custom timeouts.\n",
+    "\n",
+    "First we'll show how we can set a short lived example by setting the `\"seldon.io/rest-read-timeout\":\"1\"` annotation."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "scrolled": true
-   },
+   "execution_count": 57,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "!kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=seldon-deployment-example -o jsonpath='{.items[0].metadata.name}')"
+    "%%writetemplate resources/model_short_timeouts.json\n",
+    "apiVersion: machinelearning.seldon.io/v1\n",
+    "kind: SeldonDeployment\n",
+    "metadata:\n",
+    "  name: seldon-model\n",
+    "spec:\n",
+    "  annotations:\n",
+    "    seldon.io/rest-timeout: \"1000\"\n",
+    "    seldon.io/grpc-timeout: \"1000\"\n",
+    "  predictors:\n",
+    "  - componentSpecs:\n",
+    "    - spec:\n",
+    "        containers:\n",
+    "        - image: seldonio/mock_classifier:1.6.0-dev\n",
+    "          name: classifier\n",
+    "    graph:\n",
+    "      children: []\n",
+    "      name: classifier\n",
+    "      type: MODEL\n",
+    "      parameters:\n",
+    "      - name: delaySecs\n",
+    "        type: INT\n",
+    "        value: \"2\"       \n",
+    "    name: example\n",
+    "    replicas: 1"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now that it's deployed we can send requests to the model using the python client"
+    "We can then apply this Seldon Deployment file we defined above in the `seldon` namespace."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 58,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "seldondeployment.machinelearning.seldon.io/seldon-model configured\r\n"
+     ]
+    }
+   ],
    "source": [
-    "from seldon_core.seldon_client import SeldonClient\n",
-    "sc = SeldonClient(deployment_name=\"seldon-deployment-example\",namespace=\"seldon\")"
+    "!kubectl apply -f resources/model_short_timeouts.json -n seldon"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This next request should fail as the timeout is too short"
+    "And wait until the resource runs correctly."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 59,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "deployment \"seldon-model-example-0-classifier\" successfully rolled out\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=seldon-model -o jsonpath='{.items[0].metadata.name}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "HTTP/1.1 500 Internal Server Error\r",
+      "\r\n",
+      "access-control-allow-headers: Accept, Accept-Encoding, Authorization, Content-Length, Content-Type, X-CSRF-Token\r",
+      "\r\n",
+      "access-control-allow-methods: OPTIONS,POST\r",
+      "\r\n",
+      "access-control-allow-origin: *\r",
+      "\r\n",
+      "seldon-puid: b8937292-f055-45a6-a3c4-c887af2e88ae\r",
+      "\r\n",
+      "x-content-type-options: nosniff\r",
+      "\r\n",
+      "date: Tue, 08 Dec 2020 10:51:03 GMT\r",
+      "\r\n",
+      "content-length: 0\r",
+      "\r\n",
+      "x-envoy-upstream-service-time: 1000\r",
+      "\r\n",
+      "server: istio-envoy\r",
+      "\r\n",
+      "\r",
+      "\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!curl -i -d '{\"data\": {\"ndarray\":[[1.0, 2.0, 5.0]]}}'    -X POST http://localhost:8003/seldon/seldon/seldon-model/api/v1.0/predictions    -H \"Content-Type: application/json\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ERROR:\r\n",
+      "  Code: DeadlineExceeded\r\n",
+      "  Message: Deadline Exceeded\r\n"
+     ]
+    }
+   ],
    "source": [
-    "r = sc.predict(gateway=\"ambassador\",transport=\"rest\")\n",
-    "print(r)"
+    "!cd ../executor/proto && grpcurl -d '{\"data\":{\"ndarray\":[[1.0,2.0,5.0]]}}' \\\n",
+    "         -rpc-header seldon:seldon-model -rpc-header namespace:seldon \\\n",
+    "         -plaintext \\\n",
+    "         -proto ./prediction.proto  0.0.0.0:8003 seldon.protos.Seldon/Predict"
    ]
   },
   {
@@ -186,11 +318,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 63,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "seldondeployment.machinelearning.seldon.io \"seldon-model\" deleted\r\n"
+     ]
+    }
+   ],
    "source": [
     "!kubectl delete -f resources/model_short_timeouts.json"
    ]
@@ -201,70 +341,42 @@
    "source": [
     "## Seldon Deployment with Long Timeout\n",
     "\n",
-    "Now we can have a look at how we can set a deployment with a longer timeout by setting the annotations `\"seldon.io/rest-timeout\":\"100000\"`, and `\"seldon.io/grpc-timeout\":\"100000\"`."
+    "Now we can have a look at how we can set a deployment with a longer timeout."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 64,
    "metadata": {
     "scrolled": true
    },
    "outputs": [],
    "source": [
-    "%%writefile resources/model_long_timeouts.json\n",
-    "{\n",
-    "    \"apiVersion\": \"machinelearning.seldon.io/v1alpha2\",\n",
-    "    \"kind\": \"SeldonDeployment\",\n",
-    "    \"metadata\": {\n",
-    "        \"labels\": {\n",
-    "            \"app\": \"seldon\"\n",
-    "        },\n",
-    "        \"name\": \"model-long-timeout\"\n",
-    "    },\n",
-    "    \"spec\": {\n",
-    "        \"annotations\": {\n",
-    "            \"deployment_version\": \"v1\",\n",
-    "\t    \"seldon.io/rest-timeout\":\"100000\",\n",
-    "\t    \"seldon.io/grpc-timeout\":\"100000\"\n",
-    "        },\n",
-    "        \"name\": \"long-to\",\n",
-    "        \"predictors\": [\n",
-    "            {\n",
-    "                \"componentSpecs\": [{\n",
-    "                    \"spec\": {\n",
-    "                        \"containers\": [\n",
-    "                            {\n",
-    "                                \"image\": \"seldonio/mock_classifier_grpc:1.5\",\n",
-    "                                \"imagePullPolicy\": \"IfNotPresent\",\n",
-    "                                \"name\": \"classifier\",\n",
-    "                                \"resources\": {\n",
-    "                                    \"requests\": {\n",
-    "                                        \"memory\": \"1Mi\"\n",
-    "                                    }\n",
-    "                                }\n",
-    "                            }\n",
-    "                        ],\n",
-    "                        \"terminationGracePeriodSeconds\": 20\n",
-    "                    }\n",
-    "                }],\n",
-    "                \"graph\": {\n",
-    "                    \"children\": [],\n",
-    "                    \"name\": \"classifier\",\n",
-    "                    \"endpoint\": {\n",
-    "\t\t\t\"type\" : \"GRPC\"\n",
-    "\t\t    },\n",
-    "                    \"type\": \"MODEL\"\n",
-    "                },\n",
-    "                \"name\": \"test\",\n",
-    "                \"replicas\": 1,\n",
-    "\t\t\"annotations\": {\n",
-    "\t\t    \"predictor_version\" : \"v1\"\n",
-    "\t\t}\n",
-    "            }\n",
-    "        ]\n",
-    "    }\n",
-    "}"
+    "%%writetemplate resources/model_long_timeouts.json\n",
+    "apiVersion: machinelearning.seldon.io/v1\n",
+    "kind: SeldonDeployment\n",
+    "metadata:\n",
+    "  name: seldon-model\n",
+    "spec:\n",
+    "  annotations:\n",
+    "    seldon.io/rest-timeout: \"5000\"\n",
+    "    seldon.io/grpc-timeout: \"5000\"\n",
+    "  predictors:\n",
+    "  - componentSpecs:\n",
+    "    - spec:\n",
+    "        containers:\n",
+    "        - image: seldonio/mock_classifier:1.6.0-dev\n",
+    "          name: classifier\n",
+    "    graph:\n",
+    "      children: []\n",
+    "      name: classifier\n",
+    "      type: MODEL\n",
+    "      parameters:\n",
+    "      - name: delaySecs\n",
+    "        type: INT\n",
+    "        value: \"2\"       \n",
+    "    name: example\n",
+    "    replicas: 1"
    ]
   },
   {
@@ -276,24 +388,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 65,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "seldondeployment.machinelearning.seldon.io/seldon-model created\r\n"
+     ]
+    }
+   ],
    "source": [
     "!kubectl apply -f resources/model_long_timeouts.json -n seldon"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 66,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Waiting for deployment \"seldon-model-example-0-classifier\" rollout to finish: 0 of 1 updated replicas are available...\n",
+      "deployment \"seldon-model-example-0-classifier\" successfully rolled out\n"
+     ]
+    }
+   ],
    "source": [
-    "!kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=model-long-timeout -o jsonpath='{.items[0].metadata.name}')"
+    "!kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=seldon-model -o jsonpath='{.items[0].metadata.name}')"
    ]
   },
   {
@@ -305,15 +434,106 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 67,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "HTTP/1.1 200 OK\r",
+      "\r\n",
+      "access-control-allow-headers: Accept, Accept-Encoding, Authorization, Content-Length, Content-Type, X-CSRF-Token\r",
+      "\r\n",
+      "access-control-allow-methods: OPTIONS,POST\r",
+      "\r\n",
+      "access-control-allow-origin: *\r",
+      "\r\n",
+      "content-type: application/json\r",
+      "\r\n",
+      "seldon-puid: 1525aa31-e857-46f7-b583-8cae93e71a52\r",
+      "\r\n",
+      "x-content-type-options: nosniff\r",
+      "\r\n",
+      "date: Tue, 08 Dec 2020 10:52:48 GMT\r",
+      "\r\n",
+      "content-length: 138\r",
+      "\r\n",
+      "x-envoy-upstream-service-time: 2010\r",
+      "\r\n",
+      "server: istio-envoy\r",
+      "\r\n",
+      "\r",
+      "\r\n",
+      "{\"data\":{\"names\":[\"proba\"],\"ndarray\":[[0.43782349911420193]]},\"meta\":{\"requestPath\":{\"classifier\":\"seldonio/mock_classifier:1.6.0-dev\"}}}\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!curl -i -d '{\"data\": {\"ndarray\":[[1.0, 2.0, 5.0]]}}'    -X POST http://localhost:8003/seldon/seldon/seldon-model/api/v1.0/predictions    -H \"Content-Type: application/json\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\r\n",
+      "  \"meta\": {\r\n",
+      "    \"requestPath\": {\r\n",
+      "      \"classifier\": \"seldonio/mock_classifier:1.6.0-dev\"\r\n",
+      "    }\r\n",
+      "  },\r\n",
+      "  \"data\": {\r\n",
+      "    \"names\": [\r\n",
+      "      \"proba\"\r\n",
+      "    ],\r\n",
+      "    \"ndarray\": [\r\n",
+      "        [\r\n",
+      "              0.43782349911420193\r\n",
+      "            ]\r\n",
+      "      ]\r\n",
+      "  }\r\n",
+      "}\r\n"
+     ]
+    }
+   ],
    "source": [
-    "r = sc.predict(gateway=\"ambassador\",transport=\"grpc\",deployment_name=\"model-long-timeout\")\n",
-    "print(r)"
+    "!cd ../executor/proto && grpcurl -d '{\"data\":{\"ndarray\":[[1.0,2.0,5.0]]}}' \\\n",
+    "         -rpc-header seldon:seldon-model -rpc-header namespace:seldon \\\n",
+    "         -plaintext \\\n",
+    "         -proto ./prediction.proto  0.0.0.0:8003 seldon.protos.Seldon/Predict"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "seldondeployment.machinelearning.seldon.io \"seldon-model\" deleted\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!kubectl delete -f resources/model_long_timeouts.json"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -333,7 +553,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.6.8"
   },
   "varInspector": {
    "cols": {
diff --git a/operator/controllers/seldondeployment_controller.go b/operator/controllers/seldondeployment_controller.go
index 984f366cc5..a490b5700e 100644
--- a/operator/controllers/seldondeployment_controller.go
+++ b/operator/controllers/seldondeployment_controller.go
@@ -1648,6 +1648,14 @@ func (r *SeldonDeploymentReconciler) Reconcile(req ctrl.Request) (ctrl.Result, e
 		return ctrl.Result{}, err
 	}
 
+	// Required for foreground deletion (e.g. ArgoCD does it)
+	if !instance.ObjectMeta.DeletionTimestamp.IsZero() {
+		// If Deletion Tiemstamp is set it means object is being deleted.
+		// We should take no action in this situation.
+		log.Info("Deletion timestamp is set. Doing nothing.")
+		return ctrl.Result{}, nil
+	}
+
 	// Check if we are not namespaced and should ignore this as its in a namespace managed by another operator
 	if r.Namespace == "" {
 		ns := &corev1.Namespace{}
diff --git a/python/licenses/license.txt b/python/licenses/license.txt
index a47d4a9f1e..fc01200ae0 100644
--- a/python/licenses/license.txt
+++ b/python/licenses/license.txt
@@ -1733,7 +1733,7 @@ Apache Software License
 
 
 grpcio-reflection
-1.33.2
+1.34.0
 Apache Software License
 
                                  Apache License
@@ -2111,9 +2111,9 @@ THE SOFTWARE.
 
 
 numpy
-1.19.4
+1.18.5
 BSD
-Copyright (c) 2005-2020, NumPy Developers.
+Copyright (c) 2005-2019, NumPy Developers.
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without
diff --git a/python/licenses/license_info.csv b/python/licenses/license_info.csv
index 243709cae8..7b9ad436b3 100644
--- a/python/licenses/license_info.csv
+++ b/python/licenses/license_info.csv
@@ -22,7 +22,7 @@
 "google-pasta","0.2.0","Apache Software License"
 "grpcio","1.34.0","Apache Software License"
 "grpcio-opentracing","1.1.4","Apache Software License"
-"grpcio-reflection","1.33.2","Apache Software License"
+"grpcio-reflection","1.34.0","Apache Software License"
 "gunicorn","20.0.4","MIT License"
 "h5py","2.10.0","BSD License"
 "idna","2.10","BSD License"
@@ -30,7 +30,7 @@
 "itsdangerous","1.1.0","BSD License"
 "jaeger-client","4.3.0","Apache Software License"
 "jsonschema","3.2.0","MIT License"
-"numpy","1.19.4","BSD"
+"numpy","1.18.5","BSD"
 "oauthlib","3.1.0","BSD License"
 "opentracing","2.4.0","Apache Software License"
 "opt-einsum","3.3.0","MIT"
diff --git a/python/setup.py b/python/setup.py
index d15521edbf..f4165c064e 100644
--- a/python/setup.py
+++ b/python/setup.py
@@ -33,7 +33,7 @@
         "opentracing >= 2.2.0, < 2.5.0",
         "jaeger-client >= 4.1.0, < 4.4.0",
         "grpcio-opentracing >= 1.1.4, < 1.2.0",
-        "grpcio-reflection==1.33.2",
+        "grpcio-reflection==1.34.0",
         "PyYAML<5.4",
         "gunicorn >= 19.9.0, < 20.1.0",
         "setuptools >= 41.0.0",