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docs: simplify and clarify digital ocean docs

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Update Talos install guide for the Digital Ocean cloud platform.

Signed-off-by: Steve Francis <steve.francis@talos-systems.com>
Signed-off-by: Tim Jones <tim.jones@siderolabs.com>
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Steve Francis 2023-01-26 21:59:47 -08:00 committed by Tim Jones
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63
website/content/v1.3/talos-guides/install/cloud-platforms/digitalocean.md
View File

@ -5,25 +5,32 @@ aliases:
- ../../../cloud-platforms/digitalocean
---
## Creating a Cluster via the CLI
## Creating a Talos Linux Cluster on Digital Ocean via the CLI
In this guide we will create an HA Kubernetes cluster with 1 worker node.
In this guide we will create an HA Kubernetes cluster with 1 worker node, in the NYC region.
We assume an existing [Space](https://www.digitalocean.com/docs/spaces/), and some familiarity with DigitalOcean.
If you need more information on DigitalOcean specifics, please see the [official DigitalOcean documentation](https://www.digitalocean.com/docs/).
### Create the Image
First, download the DigitalOcean image from a Talos release.
Extract the archive to get the `disk.raw` file, compress it using `gzip` to `disk.raw.gz`.
Download the DigitalOcean image `digital-ocean-amd64.raw.gz` from the [latest Talos release](https://github.com/siderolabs/talos/releases/latest/).
>Note: the minimum version of Talos required to support Digital Ocean is v1.3.3.
Using an upload method of your choice (`doctl` does not have Spaces support), upload the image to a space.
(It's easy to drag the image file to the space using DigitalOcean's web console.)
*Note:* Make sure you upload the file as `public`.
Now, create an image using the URL of the uploaded image:
```bash
export REGION=nyc3
doctl compute image create \
--region $REGION \
--image-description talos-digital-ocean-tutorial \
--image-url https://talos-tutorial.$REGION.digitaloceanspaces.com/disk.raw.gz \
--image-url https://$SPACENAME.$REGION.digitaloceanspaces.com/digital-ocean-amd64.raw.gz \
Talos
```
@ -41,6 +48,8 @@ doctl compute load-balancer create \
--forwarding-rules entry_protocol:tcp,entry_port:443,target_protocol:tcp,target_port:6443
```
Note the returned ID of the load balancer.
We will need the IP of the load balancer.
Using the ID of the load balancer, run:
@ -48,38 +57,37 @@ Using the ID of the load balancer, run:
doctl compute load-balancer get --format IP <load balancer ID>
```
Save it, as we will need it in the next step.
Note that it may take a few minutes before the load balancer is provisioned, so repeat this command until it returns with the IP address.
### Create the Machine Configuration Files
#### Generating Base Configurations
Using the DNS name of the loadbalancer created earlier, generate the base configuration files for the Talos machines:
Using the IP address (or DNS name, if you have created one) of the loadbalancer, generate the base configuration files for the Talos machines.
Also note that the load balancer forwards port 443 to port 6443 on the associated nodes, so we should use 443 as the port in the config definition:
```bash
$ talosctl gen config talos-k8s-digital-ocean-tutorial https://<load balancer IP or DNS>:<port>
$ talosctl gen config talos-k8s-digital-ocean-tutorial https://<load balancer IP or DNS>:443
created controlplane.yaml
created worker.yaml
created talosconfig
```
At this point, you can modify the generated configs to your liking.
Optionally, you can specify `--config-patch` with RFC6902 jsonpatch which will be applied during the config generation.
### Create the Droplets
#### Validate the Configuration Files
#### Create a dummy SSH key
> Although SSH is not used by Talos, DigitalOcean requires that an SSH key be associated with a droplet during creation.
> We will create a dummy key that can be used to satisfy this requirement.
```bash
$ talosctl validate --config controlplane.yaml --mode cloud
controlplane.yaml is valid for cloud mode
$ talosctl validate --config worker.yaml --mode cloud
worker.yaml is valid for cloud mode
doctl compute ssh-key create --public-key "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDbl0I1s/yOETIKjFr7mDLp8LmJn6OIZ68ILjVCkoN6lzKmvZEqEm1YYeWoI0xgb80hQ1fKkl0usW6MkSqwrijoUENhGFd6L16WFL53va4aeJjj2pxrjOr3uBFm/4ATvIfFTNVs+VUzFZ0eGzTgu1yXydX8lZMWnT4JpsMraHD3/qPP+pgyNuI51LjOCG0gVCzjl8NoGaQuKnl8KqbSCARIpETg1mMw+tuYgaKcbqYCMbxggaEKA0ixJ2MpFC/kwm3PcksTGqVBzp3+iE5AlRe1tnbr6GhgT839KLhOB03j7lFl1K9j1bMTOEj5Io8z7xo/XeF2ZQKHFWygAJiAhmKJ dummy@dummy.local" dummy
```
### Create the Droplets
Note the ssh key ID that is returned - we will use it in creating the droplets.
#### Create the Control Plane Nodes
Run the following commands, to give ourselves three total control plane nodes:
Run the following commands to create three control plane nodes:
```bash
doctl compute droplet create \
@ -89,7 +97,7 @@ doctl compute droplet create \
--enable-private-networking \
--tag-names talos-digital-ocean-tutorial-control-plane \
--user-data-file controlplane.yaml \
--ssh-keys <ssh key fingerprint> \
--ssh-keys <ssh key ID> \
talos-control-plane-1
doctl compute droplet create \
--region $REGION \
@ -98,7 +106,7 @@ doctl compute droplet create \
--enable-private-networking \
--tag-names talos-digital-ocean-tutorial-control-plane \
--user-data-file controlplane.yaml \
--ssh-keys <ssh key fingerprint> \
--ssh-keys <ssh key ID> \
talos-control-plane-2
doctl compute droplet create \
--region $REGION \
@ -107,12 +115,11 @@ doctl compute droplet create \
--enable-private-networking \
--tag-names talos-digital-ocean-tutorial-control-plane \
--user-data-file controlplane.yaml \
--ssh-keys <ssh key fingerprint> \
--ssh-keys <ssh key ID> \
talos-control-plane-3
```
> Note: Although SSH is not used by Talos, DigitalOcean still requires that an SSH key be associated with the droplet.
> Create a dummy key that can be used to satisfy this requirement.
Note the droplet ID returned for the first control plane node.
#### Create the Worker Nodes
@ -125,7 +132,7 @@ doctl compute droplet create \
--size s-2vcpu-4gb \
--enable-private-networking \
--user-data-file worker.yaml \
--ssh-keys <ssh key fingerprint> \
--ssh-keys <ssh key ID> \
talos-worker-1
```
@ -157,3 +164,9 @@ At this point we can retrieve the admin `kubeconfig` by running:
```bash
talosctl --talosconfig talosconfig kubeconfig .
```
We can also watch the cluster bootstrap via:
```bash
talosctl --talosconfig talosconfig health
```

63
website/content/v1.4/talos-guides/install/cloud-platforms/digitalocean.md
View File

@ -5,25 +5,32 @@ aliases:
- ../../../cloud-platforms/digitalocean
---
## Creating a Cluster via the CLI
## Creating a Talos Linux Cluster on Digital Ocean via the CLI
In this guide we will create an HA Kubernetes cluster with 1 worker node.
In this guide we will create an HA Kubernetes cluster with 1 worker node, in the NYC region.
We assume an existing [Space](https://www.digitalocean.com/docs/spaces/), and some familiarity with DigitalOcean.
If you need more information on DigitalOcean specifics, please see the [official DigitalOcean documentation](https://www.digitalocean.com/docs/).
### Create the Image
First, download the DigitalOcean image from a Talos release.
Extract the archive to get the `disk.raw` file, compress it using `gzip` to `disk.raw.gz`.
Download the DigitalOcean image `digital-ocean-amd64.raw.gz` from the [latest Talos release](https://github.com/siderolabs/talos/releases/latest/).
>Note: the minimum version of Talos required to support Digital Ocean is v1.3.3.
Using an upload method of your choice (`doctl` does not have Spaces support), upload the image to a space.
(It's easy to drag the image file to the space using DigitalOcean's web console.)
*Note:* Make sure you upload the file as `public`.
Now, create an image using the URL of the uploaded image:
```bash
export REGION=nyc3
doctl compute image create \
--region $REGION \
--image-description talos-digital-ocean-tutorial \
--image-url https://talos-tutorial.$REGION.digitaloceanspaces.com/disk.raw.gz \
--image-url https://$SPACENAME.$REGION.digitaloceanspaces.com/digital-ocean-amd64.raw.gz \
Talos
```
@ -41,6 +48,8 @@ doctl compute load-balancer create \
--forwarding-rules entry_protocol:tcp,entry_port:443,target_protocol:tcp,target_port:6443
```
Note the returned ID of the load balancer.
We will need the IP of the load balancer.
Using the ID of the load balancer, run:
@ -48,38 +57,37 @@ Using the ID of the load balancer, run:
doctl compute load-balancer get --format IP <load balancer ID>
```
Save it, as we will need it in the next step.
Note that it may take a few minutes before the load balancer is provisioned, so repeat this command until it returns with the IP address.
### Create the Machine Configuration Files
#### Generating Base Configurations
Using the DNS name of the loadbalancer created earlier, generate the base configuration files for the Talos machines:
Using the IP address (or DNS name, if you have created one) of the loadbalancer, generate the base configuration files for the Talos machines.
Also note that the load balancer forwards port 443 to port 6443 on the associated nodes, so we should use 443 as the port in the config definition:
```bash
$ talosctl gen config talos-k8s-digital-ocean-tutorial https://<load balancer IP or DNS>:<port>
$ talosctl gen config talos-k8s-digital-ocean-tutorial https://<load balancer IP or DNS>:443
created controlplane.yaml
created worker.yaml
created talosconfig
```
At this point, you can modify the generated configs to your liking.
Optionally, you can specify `--config-patch` with RFC6902 jsonpatch which will be applied during the config generation.
### Create the Droplets
#### Validate the Configuration Files
#### Create a dummy SSH key
> Although SSH is not used by Talos, DigitalOcean requires that an SSH key be associated with a droplet during creation.
> We will create a dummy key that can be used to satisfy this requirement.
```bash
$ talosctl validate --config controlplane.yaml --mode cloud
controlplane.yaml is valid for cloud mode
$ talosctl validate --config worker.yaml --mode cloud
worker.yaml is valid for cloud mode
doctl compute ssh-key create --public-key "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDbl0I1s/yOETIKjFr7mDLp8LmJn6OIZ68ILjVCkoN6lzKmvZEqEm1YYeWoI0xgb80hQ1fKkl0usW6MkSqwrijoUENhGFd6L16WFL53va4aeJjj2pxrjOr3uBFm/4ATvIfFTNVs+VUzFZ0eGzTgu1yXydX8lZMWnT4JpsMraHD3/qPP+pgyNuI51LjOCG0gVCzjl8NoGaQuKnl8KqbSCARIpETg1mMw+tuYgaKcbqYCMbxggaEKA0ixJ2MpFC/kwm3PcksTGqVBzp3+iE5AlRe1tnbr6GhgT839KLhOB03j7lFl1K9j1bMTOEj5Io8z7xo/XeF2ZQKHFWygAJiAhmKJ dummy@dummy.local" dummy
```
### Create the Droplets
Note the ssh key ID that is returned - we will use it in creating the droplets.
#### Create the Control Plane Nodes
Run the following commands, to give ourselves three total control plane nodes:
Run the following commands to create three control plane nodes:
```bash
doctl compute droplet create \
@ -89,7 +97,7 @@ doctl compute droplet create \
--enable-private-networking \
--tag-names talos-digital-ocean-tutorial-control-plane \
--user-data-file controlplane.yaml \
--ssh-keys <ssh key fingerprint> \
--ssh-keys <ssh key ID> \
talos-control-plane-1
doctl compute droplet create \
--region $REGION \
@ -98,7 +106,7 @@ doctl compute droplet create \
--enable-private-networking \
--tag-names talos-digital-ocean-tutorial-control-plane \
--user-data-file controlplane.yaml \
--ssh-keys <ssh key fingerprint> \
--ssh-keys <ssh key ID> \
talos-control-plane-2
doctl compute droplet create \
--region $REGION \
@ -107,12 +115,11 @@ doctl compute droplet create \
--enable-private-networking \
--tag-names talos-digital-ocean-tutorial-control-plane \
--user-data-file controlplane.yaml \
--ssh-keys <ssh key fingerprint> \
--ssh-keys <ssh key ID> \
talos-control-plane-3
```
> Note: Although SSH is not used by Talos, DigitalOcean still requires that an SSH key be associated with the droplet.
> Create a dummy key that can be used to satisfy this requirement.
Note the droplet ID returned for the first control plane node.
#### Create the Worker Nodes
@ -125,7 +132,7 @@ doctl compute droplet create \
--size s-2vcpu-4gb \
--enable-private-networking \
--user-data-file worker.yaml \
--ssh-keys <ssh key fingerprint> \
--ssh-keys <ssh key ID> \
talos-worker-1
```
@ -157,3 +164,9 @@ At this point we can retrieve the admin `kubeconfig` by running:
```bash
talosctl --talosconfig talosconfig kubeconfig .
```
We can also watch the cluster bootstrap via:
```bash
talosctl --talosconfig talosconfig health
```