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+# Deploying Kubeless Functions using Kubernetes API
+
+Apart from using the `kubeless` CLI, it is possible to deploy Kubeless Functions directly using the Kubernetes API and creating Function objects. A minimal Function might look like:
+
+```yaml
+apiVersion: kubeless.io/v1beta1
+kind: Function
+metadata:
+  name: get-python
+  namespace: default
+spec:
+  runtime: python2.7
+  timeout: "180"
+  handler: helloget.foo
+  deps: ""
+  checksum: sha256:d251999dcbfdeccec385606fd0aec385b214cfc74ede8b6c9e47af71728f6e9a
+  function-content-type: text
+  function: |
+    def foo(event, context):
+        return "hello world"
+```
+
+The fields that a Function specification can contain are:
+
+ - Runtime: Runtime ID and version that the function will use. It should match one of the availables in the [Kubeless configuration](/docs/function-controller-configuration).
+ - Timeout: Maximum timeout for the given function. After that time, the function execution will be terminated.
+ - Handler: Pair of `<file_name>.<function_name>`. When using `zip` in `function-content-type` the `<file_name>` will be used to find the file with the function to expose. In other case it will be used just as a final file name. `<function_name>` is used to select the function to run from the exported functions of `<file_name>`. This field is mandatory and should match with an exported function.
+ - Deps: Dependencies of the function. The format of this field will depend on the runtime, e.g. a `package.json` for NodeJS functions or a `Gemfile` for Ruby.
+ - Checksum: SHA256 of the function content.
+ - Function content type: Content type of the function. Current supported values are `zip` or `text`. If the content is encoded in base64 the suffix `+base64` should be added.
+ - Function: Function content.
+
+Apart from the basic parameters, it is possible to add the specification of a `Deployment`, a `Service` or an `Horizontal Pod Autoscaler` that Kubeless will use to generate them.
+
+## Custom Deployment
+
+It is possible to specify a [`Deployment` spec](https://kubernetes.io/docs/concepts/workloads/controllers/deployment/#creating-a-deployment) in the Function spec that will be merged with default values set by the Kubeless controller. It is not necessary to specify all the fields of the deployment, just the fields you are interested on overwriting. For example:
+
+```yaml
+apiVersion: kubeless.io/v1beta1
+kind: Function
+metadata:
+  name: get-python
+...
+spec:
+...
+  deployment:
+    spec:
+      template:
+        spec:
+          containers:
+          - env:
+            - name: FOO
+              value: bar
+            name: ""
+            resources:
+              limits:
+                cpu: 100m
+                memory: 100Mi
+              requests:
+                cpu: 100m
+                memory: 100Mi
+            volumeMounts:
+            - mountPath: /my_secret
+              name: my-secret-vol
+          volumes:
+          - name: my-secret-vol
+            secret:
+              secretName: my-secret
+```
+
+Would create a function with the environment variable `FOO`, using CPU and memory limits and mounting the secret `my-secret` as a volume. Note that you can also specify a default template for a Deployment spec in the [controller configuration](/docs/function-controller-configuration).
+
+## Custom Service
+
+As with a deployment, it is possible to specify custom values for a [Service](https://kubernetes.io/docs/concepts/services-networking/service). This would be an example:
+
+```yaml
+apiVersion: kubeless.io/v1beta1
+kind: Function
+metadata:
+  name: get-python
+...
+spec:
+...
+  service:
+    clusterIP: None
+    ports:
+    - name: http-function-port
+      port: 9090
+      protocol: TCP
+      targetPort: 9090
+    selector:
+      created-by: kubeless
+      function: get-python
+    type: ClusterIP
+```
+
+The example above will create a headless service running in the port 9090.
+
+## Horizontal Pod Autoscaler
+
+For configuring the [autoscale feature](/docs/autoscaling) it is possible to attach an [Horizontal Pod Autoscaler](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/) to a function:
+
+```yaml
+apiVersion: kubeless.io/v1beta1
+kind: Function
+metadata:
+  name: get-python
+...
+spec:
+...
+  horizontalPodAutoscaler:
+    apiVersion: autoscaling/v2beta1
+    kind: HorizontalPodAutoscaler
+    metadata:
+      name: get-python
+      namespace: default
+    spec:
+      maxReplicas: 3
+      metrics:
+      - resource:
+          name: cpu
+          targetAverageUtilization: 70
+        type: Resource
+      minReplicas: 1
+      scaleTargetRef:
+        apiVersion: apps/v1beta1
+        kind: Deployment
+        name: get-python
+```
+
+The above specification will create a Horizontal Pod Autoscaler using CPU metrics.