Kubernetes Deployment with Terraform

Kubernetes Deployment with Terraform

2019-02-14 0 Par seuf

Terraform is a very powerfull tool for creating compute, network, storage ressource on every public cloud provider. It have a declarative language, so what you write is what you get. For example if you remove a compte server from your terraform config file, the next time you apply your configuration, the server will be destroyed.

Terraform comes with a lot of providers, from major cloud providers to Gitlab project management, Postgresql database, or DNS providers. There is also a list of community maintained providers.

Usually, to deploy stuff in a kubrnetes you will do a kubectl configuration file with all your resources, or use a Helm chart. By default, Helm chart is not really secure, every one who have access to your tiller pod will be able to deploy a chart in your cluster. That’s why we chose to avoid using helm charts and use Terraform instead.

Terraform provides a Kubernetes providers that allow you to create kubrnetes Objects in your kubernetes cluster :

  • namespace
  • configMap
  • secrets
  • deployments
  • services
  • etc..
  • etc..

Unfortunatly the official kubernetes providers does not provides all the resources like ingress or cluster roles. That’s why we chose to use the fork of this provider available here : https://github.com/sl1pm4t/terraform-provider-kubernetes/tree/custom/kubernetes

To install Terraform on your computer, just download the latest binary on the Terraform.io website, copy it to your $PATH (/usr/local/bin) and make it executable. Usually Terraform can download and install officials plugins directly when you do a terraform init. For the forked Kubernetes provider we have to install it manually like this :

mkdir ~/.terraform.d/plugins/linux_amd64 -p &&
rm -rf .terraform &&
wget https://github.com/sl1pm4t/terraform-provider-kubernetes/releases/download/v1.3.0-custom/terraform-provider-kubernetes_v1.3.0-custom_linux_amd64.zip -O kubernetes.zip &&
unzip -o kubernetes.zip -d ~/.terraform.d/plugins/linux_amd64/ &&
rm -f kubernetes.zip &&
terraform init

Grafana

So, now we have installed Terraform and the required Kubernetes provider plugin, let’s deploy a Grafana in a dedicated monitoring Namespace :

# Namespace
resource "kubernetes_namespace" "monitoring" {
  metadata {
    annotations {
      name = "monitoring"
    }
    name = "monitoring"
  }
}
# Secret
resource "kubernetes_secret" "grafana-secret" {
  metadata {
    name      = "grafana-secret"
    namespace = "${kubernetes_namespace.monitoring.metadata.0.name}"
  }
  data {
    "grafana-root-password" = "${file("${path.module}/monitoring/grafana-root-password")}"
    "datasources.yml" = "${file("${path.module}/monitoring/grafana/datasources.yml")}"
    "dashboards.yml"  = "${file("${path.module}/monitoring/grafana/dashboards.yml")}"
  }
  type = "Opaque"
}

resource "kubernetes_config_map" "grafana-dashboards" {
  metadata {
    name      = "grafana-dashboards"
    namespace = "${kubernetes_namespace.monitoring.metadata.0.name}"
  }

  data {
    "my-dashboard.json"                   = "${file("${path.module}/monitoring/grafana/my-dashboard.json")}"
  }
}

# Peristent volume Claim
resource "kubernetes_persistent_volume_claim" "grafana-pv-claim" {
  metadata {
    name      = "grafana-pv-claim"
    namespace = "${kubernetes_namespace.monitoring.metadata.0.name}"
  }

  spec {
    resources {
      requests {
        storage = "5Gi"
      }
    }

    access_modes = ["ReadWriteOnce"]
  }
}

# Deployment
resource "kubernetes_deployment" "grafana" {
  metadata {
    name      = "grafana"
    namespace = "${kubernetes_namespace.monitoring.metadata.0.name}"

    labels {
      app = "grafana"
    }
  }

  spec {
    replicas = "1"
    selector {
      app = "grafana"
    }

    strategy {
      type = "Recreate"
    }

    template {
      metadata {
        labels {
          app  = "grafana"
          name = "grafana"
        }
      }

      spec {
        container {
          image = "mirror.gcr.io/grafana/grafana:latest"
          name  = "grafana"

          liveness_probe {
            tcp_socket {
              port = 3000
            }

            failure_threshold     = 3
            initial_delay_seconds = 3
            period_seconds        = 10
            success_threshold     = 1
            timeout_seconds       = 2
          }

          readiness_probe {
            tcp_socket {
              port = 3000
            }

            failure_threshold     = 1
            initial_delay_seconds = 10
            period_seconds        = 10
            success_threshold     = 1
            timeout_seconds       = 2
          }

          resources {
            limits {
              cpu    = "200m"
              memory = "256M"
            }
          }

          port {
            name           = "http"
            container_port = 3000
            protocol       = "TCP"
          }

          env = [
            {
              name = "GF_SECURITY_ADMIN_PASSWORD"

              value_from {
                secret_key_ref {
                  key  = "grafana-root-password"
                  name = "${kubernetes_secret.grafana-secret.metadata.0.name}"
                }
              }
            },
            {
              name  = "GF_INSTALL_PLUGINS"
              value = "grafana-clock-panel,grafana-simple-json-datasource,grafana-piechart-panel"
            },
            {
              name  = "GF_PATH_PROVISIONING"
              value = "/etc/grafana/provisioning"
            },
          ]

          volume_mount {
            mount_path = "/var/lib/grafana"
            name       = "grafana-volume"
          }

          volume_mount {
            mount_path = "/etc/grafana/provisioning/datasources/"
            name       = "grafana-config-datasources"
          }

          volume_mount {
            mount_path = "/etc/grafana/provisioning/dashboards/"
            name       = "grafana-config-dashboards"
          }

          volume_mount {
            mount_path = "/etc/grafana/dashboards"
            name       = "grafana-dashboards"
          }
        }

        volume {
          name = "grafana-volume"
          persistent_volume_claim {
            claim_name = "${kubernetes_persistent_volume_claim.grafana-pv-claim.metadata.0.name}"
          }
        }

        volume {
          name = "grafana-config-datasources"
          secret {
            secret_name = "grafana-secret"
            items {
              key  = "datasources.yml"
              path = "datasources.yml"
            }
          }
        }

        volume {
          name = "grafana-config-dashboards"
          secret {
            secret_name = "grafana-secret"
            items {
              key  = "dashboards.yml"
              path = "dashboards.yml"
            }
          }
        }

        volume {
          name = "grafana-dashboards"
          config_map {
            name = "grafana-dashboards"
          }
        }

        # Must be set for persistent volume permissions
        # See http://docs.grafana.org/installation/docker/#user-id-changes
        security_context {
          fs_group = "472"
        }
      }
    }
  }
}

# Service
resource "kubernetes_service" "grafana" {
  metadata {
    name      = "grafana"
    namespace = "${kubernetes_namespace.monitoring.metadata.0.name}"
  }
  spec {
    selector {
      app = "grafana"
    }
    port {
      name        = "http"
      port        = 3000
      protocol    = "TCP"
      target_port = 3000
    }
  }
}

# Ingress
resource "kubernetes_ingress" "grafana" {
  metadata {
    annotations {
      "kubernetes.io/ingress.class"                 = "traefik"
    }
    name      = "grafana"
    namespace = "${kubernetes_namespace.monitoring.metadata.0.name}"
  }
  spec {
    rule {
      host = "grafana.aperogeek.fr"
      http {
        path {
          backend {
            service_name = "${kubernetes_service.grafana.metadata.0.name}"
            service_port = 3000
          }
        }
      }
    }
  }
}

As you can see, the Terraform syntax is quite the same as kubectl yaml, you just have to transform CamelCase into snake_case 😉

I’ve created a Kubernetes secret which contain the grafana root password (from a file on my disk), and the Grafana provisioning datasources and yaml configuration.

There is also a configMap where I load all my dashboards from a directory. (I’ve put only one example here), so when my Grafana starts, all my dashboards and datasources are already present !

After that, There is a classic Kubernetes deployment which mount the previously created secret and configmap in volumes.

Finally to reach my web interface, I’ve added a service and and ingress with the lovely Traefik Ingress Controller .