Manage Kubernetes Resources via Terraform

Kubernetes (K8S) is an open-source workload scheduler with focus on containerized applications. You can use the Terraform Kubernetes provider to interact with resources supported by Kubernetes.

In this tutorial, you will learn how to interact with Kubernetes using Terraform, by scheduling and exposing a NGINX deployment on a Kubernetes cluster.

The final Terraform configuration files used in this tutorial can be found in the Deploy NGINX on Kubernetes via Terraform GitHub repository.

»Why deploy with Terraform?

While you could use kubectl or similar CLI-based tools to manage your Kubernetes resources, using Terraform has the following benefits:

• Unified Workflow - If you are already provisioning Kubernetes clusters with Terraform, use the same configuration language to deploy your applications into your cluster.

• Full Lifecycle Management - Terraform doesn't only create resources, it updates, and deletes tracked resources without requiring you to inspect the API to identify those resources.

• Graph of Relationships - Terraform understands dependency relationships between resources. For example, if a Persistent Volume Claim claims space from a particular Persistent Volume, Terraform won't attempt to create the claim if it fails to create the volume.

»Prerequisites

The tutorial assumes some basic familiarity with Kubernetes and kubectl.

It also assumes that you are familiar with the usual Terraform plan/apply workflow. If you're new to Terraform itself, refer first to the Getting Started tutorial.

For this tutorial, you will need an existing Kubernetes cluster. If you don't have a Kubernetes cluster, you can use kind to provision a local Kubernetes cluster or provision one on a cloud provider.

$ brew install kind

$ curl https://raw.githubusercontent.com/hashicorp/learn-terraform-deploy-nginx-kubernetes-provider/master/kind-config.yaml --output kind-config.yaml

$ kind create cluster --name terraform-learn --config kind-config.yaml
Creating cluster "terraform-learn" ...
 ✓ Ensuring node image (kindest/node:v1.17.0) 🖼
 ✓ Preparing nodes 📦
 ✓ Writing configuration 📜
 ✓ Starting control-plane 🕹️
 ✓ Installing CNI 🔌
 ✓ Installing StorageClass 💾
Set kubectl context to "kind-terraform-learn"
You can now use your cluster with:

kubectl cluster-info --context kind-terraform-learn

Have a nice day! 👋

$ kind get clusters
terraform-learn

$ kubectl cluster-info --context kind-terraform-learn
Kubernetes master is running at https://127.0.0.1:32769
KubeDNS is running at https://127.0.0.1:32769/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy

To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'.

»Configure the provider

Before you can schedule any Kubernetes services using Terraform, you need to configure the Terraform Kubernetes provider.

There are many ways to configure the Kubernetes provider. We recommend them in the following order (most recommended first, least recommended last):

1. Use cloud-specific auth plugins (for example, eks get-token, az get-token, gcloud config)
2. Use oauth2 token
3. Use TLS certificate credentials
4. Use kubeconfig file by setting both config_path and config_context
5. Use username and password (HTTP Basic Authorization)

Follow the instructions in the kind or cloud provider tabs to configure the provider to target a specific Kubernetes cluster. The cloud provider tabs will configure the Kubernetes provider using cloud-specific auth tokens.

Create a directory named learn-terraform-deploy-nginx-kubernetes and navigate into it.

$ mkdir learn-terraform-deploy-nginx-kubernetes

$ cd learn-terraform-deploy-nginx-kubernetes

terraform {
  required_providers {
    kubernetes = {
      source = "hashicorp/kubernetes"
    }
  }
}

variable "host" {
  type = string
}

variable "client_certificate" {
  type = string
}

variable "client_key" {
  type = string
}

variable "cluster_ca_certificate" {
  type = string
}

provider "kubernetes" {
  host = var.host

  client_certificate     = var.client_certificate
  client_key             = var.client_key
  cluster_ca_certificate = var.cluster_ca_certificate
}

$ kubectl config view --minify --flatten --context=kind-terraform-learn
apiVersion: v1
clusters:
- cluster:
    certificate-authority-data: LS0tLS1CRU...
    server: https://127.0.0.1:32768
  name: kind-terraform-learn
contexts:
- context:
    cluster: kind-terraform-learn
    user: kind-terraform-learn
  name: kind-terraform-learn
current-context: kind-terraform-learn
kind: Config
preferences: {}
users:
- name: kind-terraform-learn
  user:
    client-certificate-data: LS0tLS1CRU...
    client-key-data: LS0tLS1CRU...

# terraform.tfvars

host                   = "https://127.0.0.1:32768"
client_certificate     = "LS0tLS1CRUdJTiB..."
client_key             = "LS0tLS1CRUdJTiB..."
cluster_ca_certificate = "LS0tLS1CRUdJTiB..."

After configuring the provider, run terraform init to download the latest version and initialize your Terraform workspace.

$ terraform init

»Schedule a deployment

Add the following to your kubernetes.tf file. This Terraform configuration will schedule a NGINX deployment with two replicas on your Kubernetes cluster, internally exposing port 80 (HTTP).

resource "kubernetes_deployment" "nginx" {
  metadata {
    name = "scalable-nginx-example"
    labels = {
      App = "ScalableNginxExample"
    }
  }

  spec {
    replicas = 2
    selector {
      match_labels = {
        App = "ScalableNginxExample"
      }
    }
    template {
      metadata {
        labels = {
          App = "ScalableNginxExample"
        }
      }
      spec {
        container {
          image = "nginx:1.7.8"
          name  = "example"

          port {
            container_port = 80
          }

          resources {
            limits = {
              cpu    = "0.5"
              memory = "512Mi"
            }
            requests = {
              cpu    = "250m"
              memory = "50Mi"
            }
          }
        }
      }
    }
  }
}

You may notice the similarities between the Terraform configuration and Kubernetes configuration YAML file.

Apply the configuration to schedule the NGINX deployment.

$ terraform apply

Once the apply is complete, verify the NGINX deployment is running.

$ kubectl get deployments
NAME                     READY   UP-TO-DATE   AVAILABLE   AGE
scalable-nginx-example   2/2     2            2           15s

»Schedule a Service

There are multiple Kubernetes services you can use to expose your NGINX to users.

If your Kubernetes cluster is hosted locally on kind, you will expose your NGINX instance via NodePort to access your instance. This exposes the service on each node's IP at a static port, allowing you to access the service from outside the cluster at <NodeIP>:<NodePort>.

If your Kubernetes cluster is hosted on a cloud provider, you will expose your NGINX instance via LoadBalancer to access your instance. This exposes the service externally using a cloud provider's load balancer.

Notice how the Kubernetes Service resource block dynamically assigns the selector to the Deployment's label. This avoids common bugs due to mismatched service label selectors.

resource "kubernetes_service" "nginx" {
  metadata {
    name = "nginx-example"
  }
  spec {
    selector = {
      App = kubernetes_deployment.nginx.spec.0.template.0.metadata[0].labels.App
    }
    port {
      node_port   = 30201
      port        = 80
      target_port = 80
    }

    type = "NodePort"
  }
}

$ terraform apply

$ kubectl get services
NAME            TYPE        CLUSTER-IP    EXTERNAL-IP   PORT(S)        AGE
kubernetes      ClusterIP   10.96.0.1     <none>        443/TCP        2m53s
nginx-example   NodePort    10.96.55.64   <none>        80:30201/TCP   76s

»Scale the deployment

You can scale your deployment by increasing the replicas field in your configuration. Change the number of replicas in your Kubernetes deployment from 2 to 4.

resource "kubernetes_deployment" "nginx" {
  # ...

  spec {
    replicas = 4

    # ...
  }

  # ...
}

Apply the change to scale your deployment.

$ terraform apply

Once the apply is complete, verify the NGINX deployment has four replicas.

$ kubectl get deployments
NAME                     READY   UP-TO-DATE   AVAILABLE   AGE
scalable-nginx-example   4/4     4            4           4m48s

»Clean up your workspace

Remember to destroy any resources you created once you're done with this tutorial.

Running terraform destroy will de-provision the NGINX deployment and service you created in this tutorial.

$ terraform destroy

If you are using a kind Kubernetes cluster, run the following command to delete it.

$ kind delete cluster --name terraform-learn

»Next steps

In this tutorial, you configured the Terraform Kubernetes provider and used it to schedule, expose and scale an NGINX instance.

To discover additional capabilities, visit the Terraform Kubernetes Provider Registry Documentation Page.

For a more in-depth Kubernetes example, Deploy Consul and Vault on a Kubernetes Cluster using Run Triggers (this tutorial is GKE based).