Update example READMEs following deployment PR (zenml-io#1555)

* update example READMEs

* add kubeflow docs page update

docs/book/component-gallery/orchestrators/kubeflow.md

@@ -159,7 +159,7 @@ To deploy the stack, run the following commands:
 # Pull the `k3d-modular` recipe to your local system
 zenml stack recipe pull k3d-modular
 # Deploy the stack using the ZenML CLI:
-zenml stack recipe deploy k3d-modular -i kubeflow -i minio --no-server
+zenml stack recipe deploy k3d-modular -o kubeflow -a minio --no-server
 # run the following command to import the resources as a ZenML stack, manually
 zenml stack import <STACK_NAME> -f <PATH_TO_THE_CREATED_STACK_CONFIG_YAML>
 # set the imported stack as the active stack

examples/kserve_deployment/README.md

@@ -103,11 +103,13 @@ To get a stack with KServe and potential other components, you can make use of Z
 Run the following command to deploy the local KServe stack:
 
 ```bash
-zenml stack recipe deploy k3d-modular --install kserve
+zenml stack recipe deploy k3d-modular -d kserve
 ```
 
 >**Note**:
-> This recipe comes with MLflow, Kubeflow and Minio enabled by default. If you want any other components like Seldon or Tekton, you can specify that using the `--install/-i` flag.
+> This recipe comes with MLflow, Kubeflow and Minio enabled by default. If you
+> want any other components like Seldon or Tekton, you can specify that using
+> the relevant flag (i.e. `-o` for orchestrators and so on).
 
 This will deploy a local Kubernetes cluster with KServe installed. 
 It will also generate a stack YAML file that you can import as a ZenML stack by running 

examples/kubeflow_pipelines_orchestration/README.md

@@ -132,7 +132,9 @@ pod.
 zenml stack recipe deploy k3d-modular
 ```
 >**Note**:
-> This recipe comes with MLflow, Kubeflow and Minio enabled by default. If you want any other components like KServe, Seldon or Tekton, you can specify that using the `--install/-i` flag.
+> This recipe comes with MLflow, Kubeflow and Minio enabled by default. If you
+> want any other components like Seldon or Tekton, you can specify that using
+> the relevant flag (i.e. `-o` for orchestrators and so on).
 
 #### 🏁 Deploy the stack using ZenML CLI
 
@@ -150,7 +152,7 @@ zenml stack recipe pull k3d-modular
 3. Deploy the stack using the ZenML CLI:
 
 ```shell
-zenml stack recipe deploy k3d-modular -i kubeflow -i minio --no-server
+zenml stack recipe deploy k3d-modular -o kubeflow -a minio --no-server
 ```
 
 > **Note**

examples/mlflow_registry/README.md

@@ -232,7 +232,9 @@ zenml stack recipe deploy k3d-modular
 ```
 
 >**Note**:
-> This recipe comes with MLflow, Kubeflow and Minio enabled by default. If you want any other components like KServe, Seldon or Tekton, you can specify that using the `--install/-i` flag.
+> This recipe comes with MLflow, Kubeflow and Minio enabled by default. If you
+> want any other components like Seldon or Tekton, you can specify that using
+> the relevant flag (i.e. `-o` for orchestrators and so on).
 
 This will deploy a local Kubernetes cluster with MLflow installed. 
 It will also generate a stack YAML file that you can import as a ZenML stack by running:

examples/mlflow_tracking/README.md

@@ -175,7 +175,9 @@ zenml stack recipe deploy k3d-modular
 ```
 
 >**Note**:
-> This recipe comes with MLflow, Kubeflow and Minio enabled by default. If you want any other components like KServe, Seldon or Tekton, you can specify that using the `--install/-i` flag.
+> This recipe comes with MLflow, Kubeflow and Minio enabled by default. If you
+> want any other components like Seldon or Tekton, you can specify that using
+> the relevant flag (i.e. `-o` for orchestrators and so on).
 
 This will deploy a local Kubernetes cluster with MLflow installed. 
 It will also generate a stack YAML file that you can import as a ZenML stack by running 

examples/seldon_deployment/README.md

@@ -82,14 +82,16 @@ To get a stack with Seldon Core and potential other components, you can make use
 Run the following command to deploy the local Seldon stack:
 
 ```bash
-zenml stack recipe deploy k3d-modular --install seldon
+zenml stack recipe deploy k3d-modular -d seldon
 ```
 
 >**Note**:
-> This recipe comes with MLflow, Kubeflow and Minio enabled by default. If you want any other components like KServe or Tekton, you can specify that using the `--install/-i` flag.
+> This recipe comes with MLflow, Kubeflow and Minio enabled by default. If you
+> want any other components like Seldon or Tekton, you can specify that using
+> the relevant flag (i.e. `-o` for orchestrators and so on).
 
-This will deploy a local Kubernetes cluster with Seldon installed. 
-It will also generate a stack YAML file that you can import as a ZenML stack by running 
+This will deploy a local Kubernetes cluster with Seldon installed.
+It will also generate a stack YAML file that you can import as a ZenML stack by running:
 
 ```bash
 zenml stack import -f <path-to-stack-yaml>

examples/tekton_pipelines_orchestration/README.md

@@ -74,11 +74,13 @@ To get a stack with Tekton Pipelines and potential other components, you can mak
 Run the following command to deploy the local Tekton Pipelines stack:
 
 ```bash
-zenml stack recipe deploy k3d-modular --install tekton
+zenml stack recipe deploy k3d-modular -o tekton
 ```
 
 >**Note**:
-> This recipe comes with MLflow, Kubeflow and Minio enabled by default. If you want any other components like KServe, or Seldon, you can specify that using the `--install/-i` flag.
+> This recipe comes with MLflow, Kubeflow and Minio enabled by default. If you
+> want any other components like Seldon or Tekton, you can specify that using
+> the relevant flag (i.e. `-o` for orchestrators and so on).
 
 This will deploy a local Kubernetes cluster with Tekton Pipelines installed. You can verify this by running `kubectl get pods` and checking if the Tekton Pipelines pods are running.
 It will also generate a stack YAML file that you can import as a ZenML stack by running