[Docs] Add prereqs (mlrun#2117)

docs/install/kubernetes.md

@@ -14,14 +14,15 @@
 ## Prerequisites
 
 - Access to a Kubernetes cluster. You must have administrator permissions in order to install MLRun on your cluster. For local installation 
-on Windows or Mac, [Docker Desktop](https://www.docker.com/products/docker-desktop) is recommended. MLRun fully supports k8s releases up to, and including, 1.21.
+on Windows or Mac, [Docker Desktop](https://www.docker.com/products/docker-desktop) is recommended. MLRun fully supports k8s releases 1.22 and 1.23.
 - The Kubernetes command-line tool (kubectl) compatible with your Kubernetes cluster is installed. Refer to the [kubectl installation 
 instructions](https://kubernetes.io/docs/tasks/tools/install-kubectl/) for more information.
-- Helm CLI is installed. Refer to the [Helm installation instructions](https://helm.sh/docs/intro/install/) for more information.
+- Helm 3.6 CLI is installed. Refer to the [Helm installation instructions](https://helm.sh/docs/intro/install/) for more information.
 - An accessible docker-registry (such as [Docker Hub](https://hub.docker.com)). The registry's URL and credentials are consumed by the applications via a pre-created secret.
+- Storage: 7Gi
 
-```{admonition} Note
-These instructions use `mlrun` as the namespace (`-n` parameter). You can choose a different namespace in your kubernetes cluster.
+``` {admonition} Note
+The MLRun kit resources (MLRun-API, MLRun-UI, Jupyter, and Nuclio) are configured initially with the default cluster/namespace resources limits. You can modify the resources from outside if needed.
 ```
 
 <a id="docker-desktop-installation"></a>
@@ -56,6 +57,10 @@ To learn about the various UI options and their usage, see:
 <a id="installing-the-chart"></a>
 ## Installing the chart
 
+```{admonition} Note
+These instructions use `mlrun` as the namespace (`-n` parameter). You can choose a different namespace in your kubernetes cluster.
+```
+
 Create a namespace for the deployed components:
 
 ```bash

docs/install/remote.md

@@ -22,15 +22,34 @@ You can write your code on a local machine while running your functions on a rem
 
 Before you begin, ensure that the following prerequisites are met:
 
-1. Install MLRun locally.
+1. Applications:
+   - Supports pip and conda 
+   - Recommended pip 22.x+
+   - Python 3.8   
 
-    You need to install MLRun locally and make sure the that the MLRun version you install is the same as the MLRun service version. Install  a specific version using the following command; replace the `<version>`  placeholder with the MLRun version number (e.g., `1.0.0`):
+2. Install MLRun locally.
+
+    You need to install MLRun locally. Make sure the that the MLRun version you install is the same as the MLRun service version. Install a specific version using the following command; replace the `<version>`  placeholder with the MLRun version number (e.g., `1.0.0`):
 
     ```sh
     pip install mlrun==<version>
     ```
-
-    If you already installed a previous version of MLRun, upgrade it by running:
+
+	There are a two `pip install` options:
+   - To install the requirements in the [requirements.txt](https://github.com/mlrun/mlrun/blob/development/requirements.txt), run:<br>
+     ```pip install mlrun```
+   - If you expect to connect to, or work with, cloud providers (Azure/Google Cloud/S3), you can install additional packages. 
+      This is not part of the regular requirements since not all users work with those platforms. Using this option reduces the 
+      dependencies and the size of the installation. The additional packages include:
+      - pip install mlrun[s3] # Install requirements for S3 
+      - pip install mlrun[azure-blob-storage] # install requirements for Azure blob storage
+      - pip install mlrun[google-cloud-storage] # install requirements for Google cloud storage
+
+      See the full list [here](https://github.com/mlrun/mlrun/blob/development/setup.py#L75).<br>
+      To install all extras, run:<br>
+      ```pip install mlrun[complete]```
+
+2. Alternatively, if you already installed a previous version of MLRun, upgrade it by running:
 
     ```sh
     pip install mlrun==<version> -u