This is a Terraform module for deploying Kubernetes on Equinix Metal with node pools of mixed architecture--x86 and ARM- devices, and pools of GPU devices, via the node_pool and gpu_node_pool modules for managing Kubernetes nodes.
This module can be found on the Terraform Registry at https://registry.terraform.io/modules/equinix/multiarch-k8s/metal/latest.
This project configures your cluster with:
- MetalLB using Equinix Metal elastic IPs.
The only required variables are auth_token (your Equinix Metal API key), count_x86 (the number of x86 devices), and count_arm (ARM devices).
Other options include secrets_encryption ("yes" configures your controller with encryption for secrets--this is disabled by default), and fields like facility and metro (the Equinix Metal location to deploy to) and plan_x86 or plan_arm (to determine the server type of these architectures) can be specified as well. Refer to vars.tf for a complete catalog of tunable options.
This module can be used by cloning the GitHub repo and making any Terraform configuration changes fit your use-case, or the module can be used as-is.
An alternative to using git clone, with the same affect of copying all of the Terraform config files into an empty directory, is terraform init -from-module=equinix/multiarch-k8s/metal".
The following steps assume that you've chosen to use the module directly, taking advantage of the input and output variables published in the Terraform Registry.
A sample invocation of setting up this module can be found in examples/main.tf.
Store the values of these two required variables in terraform.tfvars:
# terraform.tfvars are used by default
# Do not check this into to source control
auth_token = "your Equinix Metal API Token"
project_id = "your Equinix Metal Project ID"Run terraform init and the providers and modules will be fetched and initialized.
Tokens for cluster authentication for your node pools to your control plane must be created before instantiating the other modules. An example of creating a new token can be found in examples/token.tf.
This is not enabled by default, however, setting control_plane_node_count to any non-0 value will provision a stacked control plane node and join the cluster as a master. This requires ssh_private_key_path be set in order to complete setup; this is used only locally to distribute certificates.
Instantiating a new controller pool just requires a new instance of the controller_pool module, as seen in examples/controller_pool.tf.
To instantiate a new node pool after initial spinup, add a second module defining the pool using the node pool module like this as seen in examples/new_node_pool.tf.
In this example, the label is green (rather than the initial pool, blue) and then, generate a new kube_token (ensure the module name matches the kube_token field in the spec above, i.e. kube_token_2) by defining this in 1-provider.tf (or anywhere before the node_pool instantiation):
Generate your new token:
terraform apply -target=module.kube_token_2On your controller, add your new token, and then apply the new node pool:
terraform apply -target=module.node_pool_greenAt which point, you can either destroy the old pool, or taint/evict pods, etc. once this new pool connects.
The gpu_node_pool module provisions and configures GPU nodes for use with your Kubernetes cluster. The module definition requires count_gpu (defaults to "0"), and plan_gpu (defaults to g2.large). See examples/gpu_node_pool.tf for usage.
and upon applying your GPU pool:
terraform apply -target=module.node_pool_gpu_greenYou can manage this pool discretely from your mixed-architecture pools created with the node_pool module above.
This project can configure your CNI and storage providers. The workloads map variable contains the default release of Calico for cni, and includes Ceph and OpenEBS. These values can be overridden in your terraform.tfvars.
To use a different CNI, update cni_cidr to your desired network range, and cni_workloads to a comma-separated list of URLs, for example:
cni_workloads = "https://projectcalico.docs.tigera.io/archive/v3.24/manifests/tigera-operator.yaml,https://projectcalico.docs.tigera.io/archive/v3.24/manifests/custom-resources.yaml"These will be also written to $HOME/workloads.json on the cluster control-plane node.
To define custom workloads upon deploy, use the extra key in your workloads map in terraform.tfvars:
{
cni_cidr = "192.168.0.0/16"
cni_workloads = "https://docs.projectcalico.org/manifests/tigera-operator.yaml,https://docs.projectcalico.org/manifests/custom-resources.yaml"
ceph_common = "https://raw.githubusercontent.com/rook/rook/release-1.0/cluster/examples/kubernetes/ceph/common.yaml"
ceph_operator = "https://raw.githubusercontent.com/rook/rook/release-1.0/cluster/examples/kubernetes/ceph/operator.yaml"
ceph_cluster_minimal = "https://raw.githubusercontent.com/rook/rook/release-1.0/cluster/examples/kubernetes/ceph/cluster-minimal.yaml"
ceph_cluster = "https://raw.githubusercontent.com/rook/rook/release-1.0/cluster/examples/kubernetes/ceph/cluster.yaml"
open_ebs_operator = "https://openebs.github.io/charts/openebs-operator-1.2.0.yaml"
metallb_namespace = "https://raw.githubusercontent.com/google/metallb/v0.9.3/manifests/namespace.yaml"
metallb_release = "https://raw.githubusercontent.com/google/metallb/v0.9.3/manifests/metallb.yaml"
ingress_controller = "https://raw.githubusercontent.com/containous/traefik/v1.7/examples/k8s/traefik-ds.yaml"
nvidia_gpu = "https://raw.githubusercontent.com/NVIDIA/k8s-device-plugin/1.0.0-beta4/nvidia-device-plugin.yml"
...for example:
...
extra = "https://raw.githubusercontent.com/openshift-evangelists/kbe/main/specs/deployments/d09.yaml"
}with each subsequent workload URL separated by a comma within that string, to be applied at the end of the bootstrapping process.