docs: Adding blurb on cluster management (#837)

* Adding blurb on cluster management

* spelling tweak

* Adding GPU image

* Updating 2.7 version

* spelling and spacing

* moving image

* url

docs/civo/quick-start/cluster-management.mdx

@@ -8,3 +8,14 @@ image: "https://kubefirst.konstruct.io/docs/img/kubefirst.svg"
 import CLUSTERS from "../../common/clusters.mdx";
 
 <CLUSTERS />
+
+## GPU Clusters
+
+Kubefirst includes support for Graphical Processing Units (GPU). This capability provides Civo users who are have requirements with the capacity to run Kubefirst with performance for larger workloads.
+
+With a GPU cluster, deployment and scalability are easily managed for AI and Machine Learning through a simple setup and Kubefirst’s seamless scaling.
+
+- Requirements for this feature are Civo Cloud and Kubefirst. Refer to [our documentation here to install Kubefirst](./install/cli.mdx)  and you can select a GPU cluster as soon as Kubefirst is deployed.
+- Take advantage of high performance infrastructure with pricing starting at $0.79 per GPU/hour, for an NVIDIA GPU (H100, H200, A100, L40S) to manage demanding AI/ML workloads, including private AI and chat-based applications.
+
+![GPU cluster in Civo](../../../docs/img/civo/gpu-cluster.png)

versioned_docs/version-2.7/civo/quick-start/cluster-management.mdx

@@ -8,3 +8,14 @@ image: "https://kubefirst.konstruct.io/docs/img/kubefirst.svg"
 import CLUSTERS from "../../common/clusters.mdx";
 
 <CLUSTERS />
+
+## GPU Clusters
+
+Kubefirst includes support for Graphical Processing Units (GPU). This capability provides Civo users who are have requirements with the capacity to run Kubefirst with performance for larger workloads.
+
+With a GPU cluster, deployment and scalability are easily managed for AI and Machine Learning through a simple setup and Kubefirst’s seamless scaling.
+
+- Requirements for this feature are Civo Cloud and Kubefirst. Refer to [our documentation here to install Kubefirst](./install/cli.mdx)  and you can select a GPU cluster as soon as Kubefirst is deployed.
+- Take advantage of high performance infrastructure with pricing starting at $0.79 per GPU/hour, for an NVIDIA GPU (H100, H200, A100, L40S) to manage demanding AI/ML workloads, including private AI and chat-based applications.
+
+![GPU cluster in Civo](../../img/civo/gpu-cluster.png)

versioned_docs/version-2.7/common/deprovision.mdx

@@ -209,13 +209,15 @@ rm .env
 
 ### Console UI
 
-No matter is you created your new cluster, using the CLI directly (`kubefirst <cloud> create`) or by using the console UI (`kubefirst launch up`), Kubefirst will have created a k3d cluster in Docker. We call it the cluster 0, which is either used to display the Console UI, or to connect to our API and create your new Kubefirst cluster directly from the CLI. Since it's not needed anymore, you need to destroy it by running:
+As part of the provisioning process, a k3d cluster (k3s in Docker) is created in the machine. It contains the API and Console with which the CLI interacts. After the provisioning step is complete, you can safely delete this cluster.
+
+To do so, run the following command:
 
 ```shell
 kubefirst launch down
 ```
 
-This command will also reset any configurations files locally you can create new clusters.
+This command removes your `~/.k1/<cluster_name>` directory and the `~/.kubefirst` file.
 
 :::tip
 You don't have to wait till the deprovisioning to run this command: as soon as your cluster on the public cloud of your choice is created, you can get rid of cluster 0.