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Angeles' code notepad

In

Terraform: Containers

Terraform and Docker

Managing Docker networks

  • environment: mkdir -p ~/terraform/docker/networks
  • example
    1. Crate new files required 
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      touch {variables.tf,image.tf,network.tf,main.tf}
    2. Edit variables.tf 
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      variable "mysql_root_password" {
          description = "The MySQL root password."
          default     = "P4sSw0rd0!"
      }

      variable "ghost_db_username" {
          description = "Ghost blog database username."
          default     = "root"
      }
            
      variable "ghost_db_name" {
          description = "Ghost blog database name."
          default     = "ghost"
      }
            
      variable "mysql_network_alias" {
          description = "The network alias for MySQL."
          default     = "db"
      }

      variable "ghost_network_alias" {
          description = "The network alias for Ghost"
          default     = "ghost"
      }

      variable "ext_port" {
          description = "Public port for Ghost"
          default     = "8080"
      }
    3. Edit image.tf 
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      resource "docker_image" "ghost_image" {
           name = "ghost:alpine"
      }

      resource "docker_image" "mysql_image" {
          name = "mysql:5.7"
      }
    4. Edit network.tf 
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      resource "docker_network" "public_bridge_network" {
          name   = "public_ghost_network"
          driver = "bridge"


      resource "docker_network" "private_bridge_network" {
          name     = "ghost_mysql_internal"
          driver   = "bridge"
          internal = true
      }
    5. Edit main.tf 
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      resource "docker_container" "mysql_container" {
        name  = "ghost_database"
        image = "${docker_image.mysql_image.name}"
        env   = [
            "MYSQL_ROOT_PASSWORD=${var.mysql_root_password}"
        ]
        networks_advanced {
            name    = "${docker_network.private_bridge_network.name}"
            aliases = ["${var.mysql_network_alias}"]
        }
      }

      # do not deploy ghost until you have the db ready
      resource "null_resource" "sleep" {
        depends_on = ["docker_container.mysql_container"]
        provisioner "local-exec" {
            command = "sleep 15s"
        }
      }

      resource "docker_container" "blog_container" {
        name  = "ghost_blog"
        image = "${docker_image.ghost_image.name}"
        depends_on = ["null_resource.sleep", "docker_container.mysql_container"]
        env   = [
            "database__client=mysql",
            "database__connection__host=${var.mysql_network_alias}",
            "database__connection__user=${var.ghost_db_username}",
            "database__connection__password=${var.mysql_root_password}",
            "database__connection__database=${var.ghost_db_name}"
        ]
        ports {
            internal = "2368"
            external = "${var.ext_port}"
        }
        networks_advanced {
            name    = "${docker_network.public_bridge_network.name}"
            aliases = ["${var.ghost_network_alias}"]
        }
        networks_advanced {
            name    = "${docker_network.private_bridge_network.name}"
            aliases = ["${var.ghost_network_alias}"]
        }
      }
    6. Work with Terraform 
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      terraform init
      terraform validate
      terraform plan -out=tfplan -var 'ext_port=8082'
      terraform apply tfplan

      # clean up
      terraform destroy -auto-approve -var 'ext_port=8082'

Managing Docker volumes

  • environment 
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    cp -r ~/terraform/docker/networks ~/terraform/docker/volumes
    cd ../volumes/
  • example
    1. Edit volumes.tf 
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      resource "docker_volume" "mysql_data_volume" {
          name = "mysql_data"
      }
    2. Edit main.tf 
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      resource "docker_container" "mysql_container" {
          name  = "ghost_database"
          image = "${docker_image.mysql_image.name}"
          env   = [
              "MYSQL_ROOT_PASSWORD=${var.mysql_root_password}"
          ]
          volumes {
              volume_name    = "${docker_volume.mysql_data_volume.name}"
              container_path = "/var/lib/mysql"
          }
          networks_advanced {
              name    = "${docker_network.private_bridge_network.name}"
              aliases = ["${var.mysql_network_alias}"]
          }
      }

      resource "null_resource" "sleep" {
          depends_on = ["docker_container.mysql_container"]
          provisioner "local-exec" {
              command = "sleep 15s"
          }
      }

      resource "docker_container" "blog_container" {
          name  = "ghost_blog"
          image = "${docker_image.ghost_image.name}"
          depends_on = ["null_resource.sleep", "docker_container.mysql_container"]
          env   = [
              "database__client=mysql",
              "database__connection__host=${var.mysql_network_alias}",
              "database__connection__user=${var.ghost_db_username}",
              "database__connection__password=${var.mysql_root_password}",
              "database__connection__database=${var.ghost_db_name}"
          ]
          ports {
              internal = "2368"
              external = "${var.ext_port}"
          }
          networks_advanced {
              name    = "${docker_network.public_bridge_network.name}"
              aliases = ["${var.ghost_network_alias}"]
          }
          networks_advanced {
              name    = "${docker_network.private_bridge_network.name}"
              aliases = ["${var.ghost_network_alias}"]
          }
      }
    3. Work with Terraform 
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      terraform init
      terraform validate
      terraform plan -out=tfplan -var 'ext_port=8082'
      terraform apply tfplan
      # list Docker volumes
      docker volume inspect mysql_data
      # list the data in mysql_data
      sudo ls /var/lib/docker/volumes/mysql_data/_data

      # clean up
      terraform destroy -auto-approve -var 'ext_port=8082'

Creating swarm services

  • environment 
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    cp -r volumes/ services
    cd services
  • example
    1. Edit variables.tf 
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      variable "mysql_root_password" {
          description = "The MySQL root password."
          default     = "P4sSw0rd0!"
      }

      variable "ghost_db_username" {
          description = "Ghost blog database username."
          default     = "root"
      }

      variable "ghost_db_name" {
          description = "Ghost blog database name."
          default     = "ghost"
      }

      variable "mysql_network_alias" {
          description = "The network alias for MySQL."
          default     = "db"
      }

      variable "ghost_network_alias" {
          description = "The network alias for Ghost"
          default     = "ghost"
      }

      variable "ext_port" {
          description = "The public port for Ghost"
      }
    2. Edit images.tf 
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      resource "docker_image" "ghost_image" {
          name = "ghost:alpine"
      }

      resource "docker_image" "mysql_image" {
          name = "mysql:5.7"
      }
    3. Edit network.tf 
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      resource "docker_network" "public_bridge_network" {
          name   = "public_network"
          driver = "overlay"
      }

      resource "docker_network" "private_bridge_network" {
          name     = "mysql_internal"
          driver   = "overlay"
          internal = true
      }
    4. Edit volumes.tf 
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      resource "docker_volume" "mysql_data_volume" {
          name = "mysql_data"
      }
    5. Edit main.tf 
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      # you do not face issues for having the blog defined before db
      # as a swarm, they are on different machines
      resource "docker_service" "ghost-service" {
        name = "ghost"

        task_spec {
          container_spec {
            image = "${docker_image.ghost_image.name}"
            env {
              database__client               = "mysql"
              database__connection__host     = "${var.mysql_network_alias}"
              database__connection__user     = "${var.ghost_db_username}"
              database__connection__password = "${var.mysql_root_password}"
              database__connection__database = "${var.ghost_db_name}"
            }
          }
          networks = [
            "${docker_network.public_bridge_network.name}",
            "${docker_network.private_bridge_network.name}"
          ]
        }

        endpoint_spec {
          ports {
            target_port    = "2368"
            published_port = "${var.ext_port}"
          }
        }
      }

      resource "docker_service" "mysql-service" {
        name = "${var.mysql_network_alias}"
        task_spec {
          container_spec {
            image = "${docker_image.mysql_image.name}"
            env {
              MYSQL_ROOT_PASSWORD = "${var.mysql_root_password}"
            }

            # volumes as mounts
            mounts = [
              {
                target = "/var/lib/mysql"
                source = "${docker_volume.mysql_data_volume.name}"
                type   = "volume"
              }
            ]
          }
          networks = ["${docker_network.private_bridge_network.name}"]
        }
      }
    6. Work with Terraform 
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          terraform init
          terraform validate
          terraform plan -out=tfplan -var 'ext_port=8082'
          terraform apply tfplan
          docker service ls
          docker container ls

      s    # clean up
          terraform destroy -auto-approve -var 'ext_port=8082'

Using secrets

  • store sensitive data, encrypted with Base64
  • environment: secrets
  • example

    1. Encode the password with Base64

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      echo 'p4sSWoRd0!' | base64

    2. Edit variables.tf

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      variable "mysql_root_password" {
          default     = "cDRzU1dvUmQwIQo="
      }

      variable "mysql_db_password" {
          default     = "cDRzU1dvUmQwIQo="
      }

    3. Create ``image.tf 

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      resource "docker_image" "mysql_image" {
          name = "mysql:5.7"
      }

    4. Edit secrets.tf

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      resource "docker_secret" "mysql_root_password" {
          name = "root_password"
          data = "${var.mysql_root_password}"
      }

      resource "docker_secret" "mysql_db_password" {
          name = "db_password"
          data = "${var.mysql_db_password}"
      }

    5. Edit networks.tf

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      resource "docker_network" "private_overlay_network" {
          name     = "mysql_internal"
          driver   = "overlay"
          internal = true
      }

    6. Edit volumes.tf

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      resource "docker_volume" "mysql_data_volume" {
          name = "mysql_data"
      }

    7. Edit main.tf

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      resource "docker_service" "mysql-service" {
        name = "mysql_db"

        task_spec {
          container_spec {
            image = "${docker_image.mysql_image.name}"
        
            secrets = [
              {
                secret_id   = "${docker_secret.mysql_root_password.id}"
                secret_name = "${docker_secret.mysql_root_password.name}"
                file_name   = "/run/secrets/${docker_secret.mysql_root_password.name}"
              },
              {
                secret_id   = "${docker_secret.mysql_db_password.id}"
                secret_name = "${docker_secret.mysql_db_password.name}"
                file_name   = "/run/secrets/${docker_secret.mysql_db_password.name}"
              }
            ]

            env {
              MYSQL_ROOT_PASSWORD_FILE = "/run/secrets/${docker_secret.mysql_root_password.name}"
              MYSQL_DATABASE           = "mydb"
              MYSQL_PASSWORD_FILE      = "/run/secrets/${docker_secret.mysql_db_password.name}"
            }
          
            mounts = [
              {
                target = "/var/lib/mysql"
                source = "${docker_volume.mysql_data_volume.name}"
                type   = "volume"
              }
            ]
          }
          networks = [
            "${docker_network.private_overlay_network.name}"
          ]
        }
      }

    8. Work with Terraform

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      terraform init
      terraform validate
      terraform plan -out=tfplan
      terraform apply tfplan
      # find the MySQL container
      docker container ls
      # log into the MySQL container
      docker container exec -it [CONTAINER_ID] /bin/bash
      # access MySQL
      mysql -u root -p

      # clean up
      terraform destroy -auto-approve

Terraform and Kubernetes

Setting up Kubernetes master and installing Terraform

  1. Edit kube-config.yml 
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    apiVersion: kubeadm.k8s.io/v1beta1
    kind: ClusterConfiguration
    kubernetesVersion: "v1.13.5"
    networking:
      podSubnet: 10.244.0.0/16
    apiServer:
      extraArgs:
        service-node-port-range: 8000-31274
  2. Initialize Kubernetes 
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    sudo kubeadm init --config kube-config.yml
    # copy admin.conf to your home directory
    mkdir -p $HOME/.kube
    sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
    sudo chown $(id -u):$(id -g) $HOME/.kube/config
    # install Flannel
    sudo kubectl apply -f https://raw.githubusercontent.com/coreos/flannel/master/Documentation/kube-flannel.yml

    # untaint the Kubernetes Master
    kubectl taint nodes --all node-role.kubernetes.io/master-
  3. Install Terraform 0.11.13 on the Swarm manager 
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    sudo curl -O https://releases.hashicorp.com/terraform/0.11.13/terraform_0.11.13_linux_amd64.zip
    sudo unzip terraform_0.11.13_linux_amd64.zip -d /usr/local/bin/
    # check it
    terraform version

Creating a pod

  • environment: ~/terraform/pod
  • example

    1. Edit main.tf

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        resource "kubernetes_pod" "ghost_alpine" {
          metadata {
            name = "ghost-alpine"
          }

        spec {
          host_network = "true"
          container {
            image = "ghost:alpine"
            name  = "ghost-alpine"
          }
        }
      }

    2. Work with Terraform

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      terraform init
      terraform validate
      terraform plan
      terraform apply -auto-approve
      # check pods
      kubectl get pods

      # clean up
      terraform destroy -auto-approve

Creating a pod and service

  • environment ~/terraform/service
  • example
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      resource "kubernetes_service" "ghost_service" {
        metadata {
          name = "ghost-service"
        }
        spec {
          selector {
            app = "${kubernetes_pod.ghost_alpine.metadata.0.labels.app}"
          }
          port {
            port = "2368"
            target_port = "2368"
            node_port = "8081"
          }
          type = "NodePort"
        }
      }

      resource "kubernetes_pod" "ghost_alpine" {
        metadata {
          name = "ghost-alpine"
          labels {
            app = "ghost-blog"
          }
        }
        
        spec {
          container {
            image = "ghost:alpine"
            name  = "ghost-alpine"
            port  {
              container_port = "2368"
            }
          }
        }
      }
    2. Initialize Terraform 
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      terraform init
      terraform validate
      terraform plan
      terraform apply -auto-approve

      # check it
      kubectl get pods
      kubectl get services

      # clean up
      terraform destroy -auto-approve

Creating a deployment

  • environment: ~/terraform/deployment
  • example
    1. Edit main.tf 
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      resource "kubernetes_service" "ghost_service" {
        metadata {
          name = "ghost-service"
        }
        spec {
          selector {
            app = "${kubernetes_deployment.ghost_deployment.spec.0.template.0.metadata.0.labels.app}"
          }
          port {
            port        = "2368"
            target_port = "2368"
            node_port   = "8080"
          }
          
          type = "NodePort"
        }
      }

      resource "kubernetes_deployment" "ghost_deployment" {
        metadata {
          name = "ghost-blog"
        }
        
        spec {
          replicas = "1"
          
          selector {
            match_labels {
              app = "ghost-blog"
            }
          }
          
          template {
            metadata {
              labels {
                app = "ghost-blog"
              }
            }
            
            spec {
              container {
                name  = "ghost"
                image = "ghost:alpine"
                port {
                  container_port = "2368"
                }
              }
            }
          }
        }
      }
    2. Working with Terraform 
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      terraform init
      terraform validate
      terraform plan
      terraform apply -auto-approve

      # check it
      kubectl get deployments
      kubectl get pods
      kubectl delete pod [POD_ID]
       
      # clean up
      terraform destroy -auto-approve

In

Terraform: Introduction

Definition

  • Terraform = tool for building infrastructure
  • Allow simple control versopm
    • opensource
    • enterprise (collaboration, governance)
  • Features
    • Infrastructire as Code (IaC)
      • idempotent
      • high level syntax (Hashicorp)
      • easily resusable
    • Execution plans
      • intents of deploy
      • help ensure eveything in development is intentional
    • Resource graph
      • illustrates all cahnges and dependecies
  • Uses
    • Hybrid clouds
      • cloud agnostic
      • allows deployment to multiple providers simultaneously
    • Mult-tier architecture
      • allows deployment of several layers of architecture
      • usually able to automatically deploy in the correct order
    • Software-defined networking
      • able to deploy network architecture as well
  • Terraform is high-level infrastructire orchestration tool
    • Puppet, Chef, Ansible for configuration management
      • Providers that can tell this tools to perform CM duties

Setting up Docker Installing Terraform

  1. Prerequisires

    • Update the operating system and uninstall older versions 
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      sudo yum update -y
      sudo yum remove -y docker \
                        docker-client \
                        docker-client-latest \
                        docker-common \
                        docker-latest \
                        docker-latest-logrotate \
                        docker-logrotate \
                        docker-engine

  2. Install Docker CE

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    # install utils
    sudo yum install -y yum-utils \
    device-mapper-persistent-data \
    lvm2
    # add docker repo
    sudo yum-config-manager \
    --add-repo \
    https://download.docker.com/linux/centos/docker-ce.repo
    # install docker CE and enable it
    sudo yum -y install docker-ce
    sudo systemctl start docker && sudo systemctl enable docker
    # add user to docker group
    sudo usermod -aG docker cloud_user
    # test installation
    docker --version

  3. Configuring Swarm Manager node

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    docker swarm init --advertise-addr [PRIVATE_IP]

  4. Configure the Swarm Worker node

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    docker swarm join --token [TOKEN] [PRIVATE_IP]:2377

  5. Verify the Swarm cluster

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    docker node ls

  6. Install Terraform 0.11.13 on the Swarm manager

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    sudo curl -O https://releases.hashicorp.com/terraform/0.11.13/terraform_0.11.13_linux_amd64.zip
    sudo yum install -y unzip
    sudo unzip terraform_0.11.13_linux_amd64.zip -d /usr/local/bin/
    # test it
    terraform version

Deploying infrastructure with Terraform: basics

Terraform commands

  • Common commands

    Command Action
    apply Builds or changes infrastructure
    console Interactive console for Terraform interpolations
    destroy Destroys Terraform-managed infrastructure
    fmt Rewrites configuration files to canonical format
    get Downloads and installs modules for the configuration
    graph Creates a visual graph of Terraform resources
    import Imports existing infrastructure into Terraform
    init Initializes a new or existing Terraform configuration
    output Reads an output from a state file
    plan Generates and shows an execution plan
    providers Prints a tree of the providers used in the configuration
    push Uploads this Terraform module to Terraform Enterprise to run
    refresh Updates local state file against real resources
    show Inspects Terraform state or plan
    taint Manually marks a resource for recreation
    untaint Manually unmarks a resource as tainted
    validate Validates the Terraform files
    version Prints the Terraform version
    workspace Workspace management

  • Set up the environment

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    mkdir -p terraform/basics
    cd terraform/basics

  • Create a Terraform script

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    • main.tf contents 
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      # Download the latest Ghost image
      resource "docker_image" "image_id" {
          name = "ghost:latest"
      }

  • Initialize Terraform

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    terraform init

  • Validate the Terraform file

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    terraform validate

  • List providers in the folder

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    ls .terraform/plugins/linux_amd64/

  • List providers used in the configuration

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    terraform providers

  • Terraform Plan

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    terraform plan
    • useful flags
      • -out=path: Writes a plan file to the given path. This can be used as input to the “apply” command.
      • -var 'foo=bar': Set a variable in the Terraform configuration. This flag can be set multiple times.

  • Terraform Apply

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    # you should confirm
    terraform apply
    • useful flags
      • -auto-approve: This skips interactive approval of plan before applying
      • -var 'foo=bar': This sets a variable in the Terraform configuration. It can be set multiple times.

  • List the Docker images

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    docker image ls

  • Terraform Show

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    terraform show

  • Terraform Destroy

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    # you should confirm
    terraform destroy
    • useful flags
      • -auto-approve: Skip interactive approval of plan before applying.

  • Re-list the Docker images

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    docker image ls

  • Using a plan

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    terraform plan -out=tfplan

  • Applying a plan:

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    terraform apply tfplan

  • Show the Docker Image resource:

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    terraform show

HashiCorp Configuration Language (HCL)

  • Terraform code files (.tf and .tf.json)

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    resource "aws_instance" "example" {
        ami = "abc123"
        network_interface {
            # ...
        }
    }

  • Syntax reference

    Type Syntax
    Single line comments # this is a comment
    Multi-line comments /* This is a comment*/
    Assign values key = value
    Strings "This is a String"
    Strings interpolation ${var.foo}.
    Numbers 10 # assumed as base 10
    Boolean true, false
    Lists of primitive types ["foo", "bar", "baz"]
    Maps { "foo": "bar", "bar": "baz" }

  • Style Conventions

    • Indent two spaces for each nesting level
    • With multiple arguments, align their equals signs
    • Setup the environment 
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      cd terraform/basics

  • Deploying a container using Terraform

    1. Redeploy the Ghost image 
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      terraform apply
    2. Open main.tf: 
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      # Download the latest Ghost image
      resource "docker_image" "image_id" {
          name = "ghost:latest"
      }
            
      # Start the Container
      resource "docker_container" "container_id" {
          name  = "ghost_blog"
          image = "${docker_image.image_id.latest}"
          ports {
              internal = "2368"
              external = "80"
          }
      }
    3. Validate main.tf, plan and apply 
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      terraform validate
      terraform plan
      terraform apply
      #check
      docker container ls
    4. Check Ghost on browser (http:://[SWAM_MANAGER_IP])

  • Cleaning up the environment

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    terraform destroy

Tainting and updating resources

  • Terraform commands:

    • taint: Manually mark a resource for recreation 
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    • untaint: Manually unmark a resource as tainted 
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      terraform untaint [NAME]

  • Updating resources

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      # Download the latest Ghost image
      resource "docker_image" "image_id" {
          name = "ghost:alpine"
      }

      # Start the Container
      resource "docker_container" "container_id" {
          name  = "ghost_blog"
          image = "${docker_image.image_id.latest}"
          ports {
              internal = "2368"
              external = "80"
          }
      }
    • script 
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      terraform validate
      terraform plan
      terraform apply
      # list containers
      docker container ls
      # check Ghost image
      docker image ls | grep [IMAGE]

  • Cleaning up the environment

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    # reset
    terraform destroy
    # list the Docker images
    docker image ls
    # remove the Ghost blog image
    docker image rm ghost:latest

Terraform console and output

  • Terraform commands:

    • console: Interactive console for Terraform interpolations

  • Working with the Terraform console

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    # Redeploy image and container
    terraform apply
    terraform show
    terraform console
    # Type the following in the console to get the container's name
    docker_container.container_id.name
    # Type the following in the console to get the container's IP
    docker_container.container_id.ip_address
    # Break out of the Terraform console by using Ctrl+C
    terraform destroy

  • Output the name and IP of the container

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      # Download the latest Ghost Image
      resource "docker_image" "image_id" {
          name = "ghost:latest"
      }

      # Start the Container
      resource "docker_container" "container_id" {
          name  = "blog"
          image = "${docker_image.image_id.latest}"
          ports {
              internal = "2368"
              external = "80"
          }
      }

      # Output the IP Address of the Container
      output "ip_address" {
          value       = "${docker_container.container_id.ip_address}"
          description = "The IP for the container."
      }

      # Output the Name of the Container
      output "container_name" {
          value       = "${docker_container.container_id.name}"
          description = "The name of the container."
      }
    • Script 
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      terraform validate
      # apply changes to get the output
      terraform apply
      # clean up
      terraform destroy

Input variables

  • Definition

    • Parameters for a Terraform file
    • A variable block configures a single input variable for a Terraform module
    • Each block declares a single variable.

  • Syntax

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    variable [NAME] {
        [OPTION] = "[VALUE]"
    }

  • Arguments (between { })

    Optional parameters Value
    type defines the type of the variable (string, list or map)
    default default value. If not provided, Terraform will raise an error if a value is not provided by the caller
    description human-friendly description for the variable

  • Using variables during an apply

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    terraform apply -var 'foo=bar'

  • Example with main.tf contents

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    # Define variables
    variable "image_name" {
        description = "Image for container."
        default     = "ghost:latest"
    }

    variable "container_name" {
        description = "Name of the container."
        default     = "blog"
    }

    variable "int_port" {
        description = "Internal port for container."
        default     = "2368"
    }

    variable "ext_port" {
        description = "External port for container."
        default     = "80"
    }
      
    # Download the latest Ghost Image
    resource "docker_image" "image_id" {
        name = "${var.image_name}"
    }
      
    # Start the Container
    resource "docker_container" "container_id" {
        name  = "${var.container_name}"
        image = "${docker_image.image_id.latest}"
        ports {
            internal = "${var.int_port}"
            external = "${var.ext_port}"
        }
    }
      
    # Output the IP Address of the Container
    output "ip_address" {
        value       = "${docker_container.container_id.ip_address}"
        description = "The IP for the container."
    }

    output "container_name" {
        value       = "${docker_container.container_id.name}"
        description = "The name of the container."
    }
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    terraform validate
    terraform plan
    # apply using the variable
    terraform apply -var 'ext_port=8080'
    # change the container name:
    terraform apply -var 'container_name=ghost_blog' -var 'ext_port=8080'
    # reset
    terraform destroy -var 'ext_port=8080'

Breaking out our variables and outputs

  1. Edit variables.tf 
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    #Define variables
    variable "container_name" {
        description = "Name of the container."
        default     = "blog"
    }
    variable "image_name" {
        description = "Image for container."
        default     = "ghost:latest"
    }
    variable "int_port" {
        description = "Internal port for container."
        default     = "2368"
    }
    variable "ext_port" {
        description = "External port for container."
        default     = "80"
    }
  2. Edit main.tf: 
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    # Download the latest Ghost Image
    resource "docker_image" "image_id" {
        name = "${var.image_name}"
    }

    # Start the Container
    resource "docker_container" "container_id" {
        name  = "${var.container_name}"
        image = "${docker_image.image_id.latest}"
        ports {
            internal = "${var.int_port}"
            external = "${var.ext_port}"
        }
    }
  3. Edit outputs.tf: 
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    #Output the IP Address of the Container
    output "ip_address" {
        value       = "${docker_container.container_id.ip_address}"
        description = "The IP for the container."
    }

    output "container_name" {
        value       = "${docker_container.container_id.name}"
        description = "The name of the container."
    }
  4. Script 
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    terraform validate
    # plan and apply
    terraform plan -out=tfplan -var container_name=ghost_blog
    terraform apply tfplan
    # clean up
    terraform destroy -auto-approve -var container_name=ghost_blog

Maps and lookups

  • Map: specify different environment variables based on conditions
  • Example
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      #Define variables
      variable "env" {
          description = "env: dev or prod"
      }
      variable "image_name" {
          type        = "map"
          description = "Image for container."
          default     = {
              dev  = "ghost:latest"
              prod = "ghost:alpine"
          }
      }
      variable "container_name" {
          type        = "map"
          description = "Name of the container."
          default     = {
              dev  = "blog_dev"
              prod = "blog_prod"
          }
      }

      variable "int_port" {
        description = "Internal port for container."
        default     = "2368"
      }
      variable "ext_port" {
          type        = "map"
          description = "External port for container."
          default     = {
              dev  = "8081"
              prod = "80"
          }
      }
    2. Edit main.tf 
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      # Download the latest Ghost Image
      resource "docker_image" "image_id" {
          name = "${lookup(var.image_name, var.env)}"
      }

      # Start the Container
      resource "docker_container" "container_id" {
          name  = "${lookup(var.container_name, var.env)}"
          image = "${docker_image.image_id.latest}"
          ports {
              internal = "${var.int_port}"
              external = "${lookup(var.ext_port, var.env)}"
          }
      }
    3. Validate it and deploy 
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      terraform validate
      terraform plan -out=tfdev_plan -var env=dev
      terraform apply tfdev_plan
      # plan the prod deploy
      terraform plan -out=tfprod_plan -var env=prod
      # use environment variables
      export TF_VAR_env=prod
      terraform console
      # execute a lookup
      lookup(var.ext_port, var.env)
      # exit the console:
      unset TF_VAR_env

Terraform Workspaces

  • Terraform commands

    Command Type Action
    workspace Command New, list, select and delete Terraform workspaces
    delete Subcommand delete a workspace
    list Subcommand list Workspaces
    new Subcommand create a new workspace
    select Subcommand select a workspace
    show Subcommand show the name of the current workspace

  • Example

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    cd terraform/basics
    # dev workspace
    terraform workspace new dev
    terraform plan -out=tfdev_plan -var env=dev
    terraform apply tfdev_plan

    # prod workspace
    terraform workspace new prod
    terraform plan -out=tfprod_plan -var env=prod
    terraform apply tfprod_plan

    # default workspace
    terraform workspace select default

    # find what workspace we are using now
    terraform workspace show
    # select a workspace
    terraform workspace select dev

    # clean up
    terraform destroy -var env=dev
    terraform workspace select prod
    terraform destroy -var env=prod

Null resources and Local-exec

  • null_resource resource implements the standard resource lifecycle but takes no further action
  • local-exec provisioner invokes a local executable after a resource is created
  1. Edit main.tf 
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    # Download the latest Ghost Image
    resource "docker_image" "image_id" {
        name = "${lookup(var.image_name, var.env)}"
    }

    # Start the Container
    resource "docker_container" "container_id" {
        name  = "${lookup(var.container_name, var.env)}"
        image = "${docker_image.image_id.latest}"
        ports {
            internal = "${var.int_port}"
            external = "${lookup(var.ext_port, var.env)}"
        }
    }

    resource "null_resource" "null_id" {
        provisioner "local-exec" {
            command = "echo ${docker_container.container_id.name}:${docker_container.container_id.ip_address} >> container.txt"
        }
    }
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    # reinitialize
    terraform init
    terraform validate
    terraform plan -out=tfplan -var env=dev
    terraform apply tfplan
    # view container info
    cat container.txt
    # clean up
    terraform destroy -auto-approve -var env=dev

Terraform modules

  • Module: container for multiple resource

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    # setup environment for root module
    mkdir -p modules/image
    mkdir -p modules/container
    # files for image
    cd ~/terraform/basics/modules/image
    touch main.tf variables.tf outputs.tf
    # files for container module
    cd ~/terraform/basics/modules/container
    touch main.tf variables.tf outputs.tf

Image module

  • environment: ``~/terraform/basics/modules/image`
  • example
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      # Download the Image
      resource "docker_image" "image_id" {
          name = "${var.image_name}"
      }
    2. Edit variables.tf 
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      variable "image_name" {
          description = "Name of the image"
      }
    3. Edit outputs.tf 
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      output "image_out" {
          value       = "${docker_image.image_id.latest}"
      }
    4. Initialize Terraform: 
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      terraform init
      terraform plan -out=tfplan -var 'image_name=ghost:alpine'
      terraform apply -auto-approve tfplan
      # clean up
      terraform destroy -auto-approve -var 'image_name=ghost:alpine'

Container module

  • environment: ~/terraform/basics/modules/container
  • example: breaking out the container code into it’s own module
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      # Start the Container
      resource "docker_container" "container_id" {
          name  = "${var.container_name}"
          image = "${var.image}"
          ports {
              internal = "${var.int_port}"
              external = "${var.ext_port}"
          }
      }
    2. Edit variables.tf 
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      #Define variables
      variable "container_name" {}
      variable "image" {}
      variable "int_port" {}
      variable "ext_port" {}
    3. Edit outputs.tf 
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      #Output the IP Address of the Container
      output "ip" {
          value = "${docker_container.container_id.ip_address}"
      }

      output "container_name" {
          value = "${docker_container.container_id.name}"
      }
    4. Script 
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      terraform init
      terraform plan -out=tfplan -var 'container_name=blog' -var 'image=ghost:alpine' -var 'int_port=2368' -var 'ext_port=80'
      terraform apply tfplan

Root module

  • environment: ~/terraform/basics/modules/
  • example: refactor the root module to use the image and container modules we created previously
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      # Download the image
      module "image" {
          source = "./image"
          image_name  = "${var.image_name}"
      }

      # Start the container
      module "container" {
          source             = "./container"
          image              = "${module.image.image_out}"
          container_name     = "${var.container_name}"
          int_port           = "${var.int_port}"
          ext_port           = "${var.ext_port}"
      }
    2. Edit variables.tf 
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      #Define variables
      variable "container_name" {
          description = "Name of the container."
          default     = "blog"
      }
      variable "image_name" {
          description = "Image for container."
          default     = "ghost:latest"
      }
      variable "int_port" {
          description = "Internal port for container."
          default     = "2368"
      }
      variable "ext_port" {
          description = "External port for container."
          default     = "80"
      }
    3. Edit outputs.tf 
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      # Output the IP Address of the Container
      output "ip" {
          value = "${module.container.ip}"
      }

      output "container_name" {
          value = "${module.container.container_name}"
      }
    4. Script 
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      terraform init
      terraform plan -out=tfplan
      terraform apply tfplan
      # clean up
      terraform destroy -auto-approve

In

Setting up a Kubernetes cluster with docker

Configure the Kubernetes cluster

1 master, 3 worker nodes

  1. In Node 1, add the Kubernetes repo to /etc/yum.repos.d. 
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    cat << EOF > /etc/yum.repos.d/kubernetes.repo
  2. Install the repo 
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    [kubernetes]
    name=Kubernetes
    baseurl=https://packages.cloud.google.com/yum/repos/kubernetes-el7-x86_64
    enabled=1
    gpgcheck=1
    repo_gpgcheck=1
    gpgkey=https://packages.cloud.google.com/yum/doc/yum-key.gpg
    https://packages.cloud.google.com/yum/doc/rpm-package-key.gpg
    exclude=kube*
    EOF
  3. Disable SELinux 
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    setenforce 0
  4. Install Kubernetes, enable and start kubelet 
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    # use a version to be more stable
    yum install -y kubelet-1.11.3 kubeadm-1.11.3 kubectl-1.11.3 --disableexcludes=kubernetes
    systemctl enable kubelet && systemctl start kubelet
  5. Set up the bridge network 
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    cat <<EOF > /etc/sysctl.d/k8s.conf
    net.bridge.bridge-nf-call-ip6tables = 1
    net.bridge.bridge-nf-call-iptables = 1
    EOF
    # reload so changes take effect
    sysctl --system
  6. Initialize the master node, and set the code network CIDR and start using cluster 
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    kubeadm init --pod-network-cidr=10.244.0.0/16 --kubernetes-version=v1.11.3
    # start using the cluster
    mkdir -p $HOME/.kube
    sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
    sudo chown $(id -u):$(id -g)$HOME/.kube/config
  7. Install Flannel (for networking settings) on the master node 
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    kubectl apply -f https://raw.githubusercontent.com/coreos/flannel/v0.9.1/Documentation/kube-flannel.yml
  8. Repeat Steps 1-5 in your Node 2 and Node 3 terminals
  9. In your Node 1 terminal window, run the following command 
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    kubeadmin token create --print-join-command
    # copy the command to join
  10. Paste the previous result command and run it in your Node 2 and Node 3 terminal, and then check everything went ok
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    kubectl get nodes
    # 3 nodes
    # 2 with role "none"
    # 1 with role "master"

Create a Pod

  1. Create the pod.yml file and edit it 
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    apiVersion: v1
    kind: Pod
    metadata:
      name: nginx-pod-demo
      labels:
        app: nginx-demo
    spec:
      containers:
        - image: nginx:latest
          name: nginx-demo
          ports:
          - containerPort: 80
          imagePullPolicy: Always
  2. Create the pod 
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    kubectl create -f pod.yml
    # check them
    kubectl get pods

Create the service

  1. Create the service.yml file and edit it 
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    kind: Service
    apiVersion: v1
    metadata:
      name: service-demo
    spec:
      selector:
        app: nginx-demo
      ports:
      - protocol: TCP
        port: 80
        targetPort: 80
      type: NodePort
  2. Create the service 
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    kubectl create -f service.yml
    # check it
    kubectl get services
  3. Browse to PUBLIC_IP_ADDRESS:SERVICE_PORT_NUMBER, check the Nginx welcome screen

Scaling pods in Kubernetes

Deploy

  1. Initialize Kubernetes cluster and install Flannel (see “Configure the Kubernetes cluster, steps 6,7”)
  2. Deploy (deployment.yml) 
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    kind: Deployment
    apiVersion: v1
    metadata:
      name: httpd-deployment
      labels:
        app: httpd
    spec:
      replicas: 3
      selector:
        matchLabels:
          app: httpd
        template:
        metadata:
          labels:
            app: httpd
        spec:
          containers:
            -name: httpd
              image: httpd:latest
              ports:
              - containerPort: 80
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    # deploy
    kubectl create -f deployment.yml
    # check it
    kubectl get pods
  3. Create the service.yml file and edit it 
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    kind: Service
    apiVersion: v1
    metadata:
      name: service-deployment
    spec:
      selector:
        app: httpd
      ports:
      - protocol: TCP
        port: 80
        targetPort: 80
      type: NodePort
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    # launch
    kubectl create -f service.yml
    # check it
    kubectl get pods

Scale the deployment

  1. Scale up to 5 replicas (deployment.yml) 
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    kind: Deployment
    apiVersion: v1
    metadata:
      name: httpd-deployment
      labels:
        app: httpd
    spec:
      replicas: 5
      selector:
        matchLabels:
          app: httpd
        template:
        metadata:
          labels:
            app: httpd
        spec:
          containers:
            -name: httpd
              image: httpd:latest
              ports:
              - containerPort: 80
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    kubectl apply -f deployment.yml
    # check it
    kubectl get pods
  2. Scale down to 2 replicas (edit deployment.yml) 
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    kind: Deployment
    apiVersion: v1
    metadata:
      name: httpd-deployment
      labels:
        app: httpd
    spec:
      replicas: 2
      selector:
        matchLabels:
          app: httpd
        template:
        metadata:
          labels:
            app: httpd
        spec:
          containers:
            -name: httpd
              image: httpd:latest
              ports:
              - containerPort: 80
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    kubectl apply -f deployment.yml
    # check it
    kubectl get pods

Creating a Helm chart

Creating an application using Helm

  1. Install Helm 
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    # get the install script
    curl https://raw.githubusercontent.com/helm/helm/master/scripts/get > /tmp/get_helm.sh
    # verify the download
    cat /tmp/get_helm.sh
    # modify the access permissions
    chmod 700 /tmp/get_helm.sh
    # Set the version to v2.8.2
    DESIRED_VERSION=v2.8.2 /tmp/get_helm.sh
    # init Helm
    helm init --wait
  2. Give Helm permission to work with Kubernetes 
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    kubectl --namespace=kube-system create clusterrolebinding add-on-cluster-admin --clusterrole=cluster-admin --serviceaccount=kube-system:default
    # check it
    helm ls

Create a Helm chart

  1. Create charts directory and create one chart 
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    mkdir charts
    cd charts
    # chart for httpd
    helm create httpd
    # check content
    cd httpd/
    ls
    # chart.yaml and values.yaml should exist
  2. Edit the values.yaml file:
    • Under image: change the repository to httpd. Change the tag to latest
    • Under service: change type to NodePort
    • httpd/values.yaml should look like this: 
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      replicaCount: 1

      image:
        repository: httpd
        tag: latest
        pullPolicy: IfNotPresent

      service:
        type: NodePort
        port: 80

      ingress:
        enabled: false
        annotations: {}
        path: /
        hosts:
          - chart-example.local
        tls: []

      resources: {}
      nodeSelector: {}
       
      tolerations: []

      affinity: {}

Create the application

  1. From the charts directory, install our application 
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    helm install --name my-httpd ./httpd/
    # copy the commands listed under the NOTES section of the output and paste them to run them
    # it should return the private IP address and port number of our application
  2. Check the pods 
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    # check pods
    kubectl get pods
    # you should see the pod that was created by Helm
  3. Check services
    kubectl get services
# locate the port number of my-httpd displayed in the output
  4. Browser to PUBLIC_IP_ADDRESS:SERVICE_PORT to check it works

In

Setting up dockerswarm (1 manager)

Initialize docker swarm

  1. Initialize the Docker swarm on manager node (SwarmServer1) 
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    docker swarm init
  2. Copy the docker swarm join command that is displayed for the next step (e.g. docker swarm join --token TOKEN IP_ADDRESS:2377)

Add additional nodes to the swarm

  1. Add worker nodes to the swarm (SwarmServer2 and SwarmServer3) using the command retrieved from the init 
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    docker swarm join --token TOKEN IP_ADDRESS:2377

Create a swarm service

  1. From the manager node (SwarmServer1), create a service to test your swarm configuration
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    docker service create --name weather-app --publish published=80,target=3000 --replicas=3 weather-app
    # verify it
    docker service ls
  2. Paste one of the public IP addresses of our worker nodes in a browser to view the weather app is also showing on the ‘worker nodes’

Backing up and restoring dockerswarm

Join the worker nodes to the swarm

  1. Follow the previous section “initilize and add”, so you get the manager and 2 workers up and running
  2. View the running services on swarm manager node 
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    docker service ls
    # check backup service is there, we will scale it
    docker service scale backup=3
    #  check by showing the service across our nodes
    docker service ps backup

Back up the swarm manager

  1. On the manager node: 
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    # stop service before
    systemctl stop docker
    # back up
    tar czvf swarm.tgz /var/lib/docker/swarm/

Restore the swarm on the backup manager

  1. Copy the swarm backup from the manager node to the backup manager 
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    # from manager node terminal
    scp swarm.tgz cloud_user@BACKUP_IP_ADDRESS:/home/cloud_user/
  2. Extract the backup file on backup server (4th server) 
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    cd /home/cloud_user
    tar xzvf swarm.tgz
    # copy the swarm directory
    /var/lib/docker/swarm
    cp -rf swarm/ /var/lib/docker/
    # restart the service
    systemctl restart docker
    # reinitialize the swarm
    docker swarm init --force-new-cluster
    # copy the swarm join command

Add the worker nodes to the restored cluster

  1. The 2 workers need to leave the first swarm and join the second one 
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    docker swarm leave
    # do not forget it should have the backup IP address
    docker swarm join --token $NEW_JOIN_TOKEN_HERE

Distribute the replicas across the swarm

  1. Check backup server is up and running 
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    docker service ls
    # check the service list
    docker service ps backup
    # you should see 3 replicas on backup manager
  2. Make sure our service is distributed across our swarm 
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    # scale things down to 1
    docker service scale backup=1
    # back up to 3
    docker service scale backup=3
    #check service again
    docker service ps backup
    # service should be up and running on all 3 nodes

Scaling a docker swarm service (2 managers)

Create a swarm

  1. Create a swarm manager (SwarmManager1) 
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    docker swarm init
    # copy the join command

Add worker nodes

  1. To each worker (e.g. 3 workers)
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    docker swarm join --token <TOKEN> <IP_ADDRESS:2377>

The Manager Token

  1. Generate the manager token on SwamManager1 node 
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    docker swarm join-token manager
    # This command is for when we want a manager node to join
  2. Add a second swam manager server SwamManager2 
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    docker swarm join --token <TOKEN> <IP_ADDRESS:2377>
  3. Check our work (from SwarmManager1) 
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    docker node ls
    # 5 nodes running
    # 3 workers
    # 1 MANAGER STATUS: leader (SwarmManager1)
    # 1 MANAGER STATUS: Reachable (SwarmManager2)

    ## ensure the managers are ONLY managers
    docker node update --availability drain <MANAGER1 ID>
    docker node update --availability drain <MANAGER2 ID>

Create a service

  1. Create a service, and replicate it three times (image httpd from DockerHub) 
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    docker service create --name httpd -p 80:80 --replicas 3 httpd
  2. Check what is running (from SwarmManager1) 
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    docker service ps httpd
    # shows 3 replicas, 1 on each worker

Scale a service up and down

  1. Scale the httpd service up to 5 
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    docker service scale httpd=5
    docker service ps httpd
    # check there are 5 now, managers are only managers
  2. Scale the httpd Service back down to 2 Nodes 
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    docker service scale httpd=2
    docker service ps httpd
    # check there are 2 now, managers are only managers

In

Prometheus (cAdvisor)

  • Prepare environment

    1. Create prometheus.yml in root’s home directory

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      scrape_configs:
      - job_name: cadvisor
      scrape_interval: 5s
      static_configs:
      - targets:
          - cadvisor:8080

    2. Create the Prometheus services via docker-compose.yml

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      version: '3'
      services:
          prometheus:
            image: prom/prometheus:latest
            container_name: prometheus
            ports:
              - 9090:9090
            command:
              - --config.file=/etc/prometheus/prometheus.yml
            volumes:
              - ./prometheus.yml:/etc/prometheus/prometheus.yml
             depends_on:
                - cadvisor
          cadvisor:
            image: google/cadvisor:latest
            container_name: cadvisor
            ports:
              - 8080:8080
            volumes:
              - /:/rootfs:ro
              - /var/run:/var/run:rw
              - /sys:/sys:ro
              - /var/lib/docker:/var/lib/docker:ro

    3. Start the environment

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      docker-compose up -d
      docker ps
      # The output should show four containers:
      # prometheus, cadvisor, nginx, and redis

    4. Viewing the Prometheus web interface (http://<IP_ADDRESS>:9090/graph/)

      • Top menu: status -> targets
      • Top menu: Graph -> Execute button -> find container_startup_time_second -> Execute
      • Queries: Above that Execute* button and related dropdown is a web form field where we can type different expressions. **rate(container_cpu_usage_seconds_total{name="redis"}[1m])and execute

  • cAdvisor

    • Instance (http://<IP_ADDRESS>:8080/containers/)
    • Individual containers (http://<IP_ADDRESS>:8080/docker/nginx/)

  • Stats in Docker. [[Ctrl]]+[[C]] to exit

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    # CPU and memory usage
    docker stats
    • Prettier stats via shell scripts
      1. Create a stats.sh file in /root 
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        nano ~/stats.sh
      2. Add this command to it 
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        docker stats --format "table {{.Name}} {{.ID}} {{.MemUsage}} {{.CPUPerc}}"
      3. Make it executable and run it 
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        chmod a+x stats.sh
        # Run it
        ./stats.sh

Grafana + Prometheus = alerting and monitoring

Setup

  1. Configure Docker via /etc/docker/daemon.json 
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    {
      "metrics-addr" : "0.0.0.0:9323",
      "experimental" : true
    }
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    # restart docker service
    systemctl restart docker
  2. Update Prometheus via /prometheus.yml 
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    scrape_configs:
      - job_name: prometheus
      scrape_interval: 5s
      static_configs:
      - targets:
        - prometheus:9090
        - node-exporter:9100
        - pushgateway:9091
        - cadvisor:8080
      
      - job_name: docker
        scrape_interval: 5s
        static_configs:
        - targets:
          # provide the private IP address of your instance
          - <PRIVATE_IP_ADDRESS>:9323
  3. Update Docker Compose (~/docker-compose.yml) 
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    version: '3'
    services:
      prometheus:
        image: prom/prometheus:latest
        container_name: prometheus
        ports:
          - 9090:9090
        command:
          - --config.file=/etc/prometheus/prometheus.yml
        volumes:
          - ./prometheus.yml:/etc/prometheus/prometheus.yml:ro
        depends_on:
          - cadvisor
      cadvisor:
        image: google/cadvisor:latest
        container_name: cadvisor
        ports:
          - 8080:8080
        volumes:
          - /:/rootfs:ro
          - /var/run:/var/run:rw
          - /sys:/sys:ro
          - /var/lib/docker/:/var/lib/docker:ro
      pushgateway:
        image: prom/pushgateway
        container_name: pushgateway
        ports:
          - 9091:9091
      node-exporter:
        image: prom/node-exporter:latest
        container_name: node-exporter
        restart: unless-stopped
        expose:
          - 9100
      grafana:
        image: grafana/grafana
        container_name: grafana
        ports:
          - 3000:3000
        environment:
          - GF_SECURITY_ADMIN_PASSWORD=password
        depends_on:
          - prometheus
          - cadvisor
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    # apply our changes and rebuild the environment
    docker-compose up -d
    docker ps
  4. Verify that all of our Prometheus targets are healthy
    • Browse http://PUBLIC_IP_ADDRESS:9090 -> Status -> Targets
  5. Check firewall configuration if you are using private IP 
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    firewall-cmd --add-port 9090/tcp

Configure Grafana

  1. Create a new Grafana data source

    • Browse http://PUBLIC_IP_ADDRESS:3000
    • Type “admin” for username and “password” for password. Click Log In.
    • Home Dashboard -> Add data source -> Name =”Prometheus”
      Type field = “Prometheus”
      URL = http://localhost:9090
    • Replace “localhost” in the URL with the private IP address (e.g. http://PRIVATE_IP_ADDRESS:9090)
    • Click Save & Test.

  2. Add the Docker Dashboard to Grafana

    • Click on ‘+’’ on the left side of the Grafana interface -> Import
    • Paste the JSON for Docker to Grafana into the ‘Or paste JSON field’-> Load. ON Import screen -> dropdown menu for Prometheus -> Prometheus data source we created earlier -> Import

  3. Add an email notification channel

    • Left sidebar -> bell icon -> Notification channels -> Add channel
      • Name = “Email”
      • Email addresses = yourMail@mail.com

  4. Create an Alert for CPU Usage

    • dashboard icon (left sidebar) -> Home -> Docker and system monitoring dashboard -> CPU Usage graph -> Edit
    • Metrics tab -> Add Query: sum(rate(process_cpu_seconds_total[1m])) * 100
    • Alert tab -> Create Alert -> Conditions -> query field: E**: IS ABOVE = “75” -> **Test Rule
    • Notifications (left sidebar) -> ‘+’’ icon next to Sent to -> Select Email Alerts
      • Message text box = “CPU usage is over 75%.”
      • Save, check the box next to Save current variables. description box = “Add alerting”. Save.

JSON for Docker to Grafana

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  "refresh": "5m",
  "schemaVersion": 16,
  "style": "dark",
  "tags": [],
  "templating": {
    "list": [
      {
        "allValue": ".+",
        "current": {},
        "datasource": "${DS_PROMETHEUS}",
        "hide": 0,
        "includeAll": true,
        "label": "Container Group",
        "multi": true,
        "name": "containergroup",
        "options": [],
        "query": "label_values(container_group)",
        "refresh": 1,
        "regex": "",
        "sort": 0,
        "tagValuesQuery": null,
        "tags": [],
        "tagsQuery": null,
        "type": "query",
        "useTags": false
      },
      {
        "auto": true,
        "auto_count": 50,
        "auto_min": "50s",
        "current": {
          "text": "auto",
          "value": "$__auto_interval_interval"
        },
        "datasource": null,
        "hide": 0,
        "includeAll": false,
        "label": "Interval",
        "multi": false,
        "name": "interval",
        "options": [
          {
            "selected": true,
            "text": "auto",
            "value": "$__auto_interval_interval"
          },
          {
            "selected": false,
            "text": "30s",
            "value": "30s"
          },
          {
            "selected": false,
            "text": "1m",
            "value": "1m"
          },
          {
            "selected": false,
            "text": "2m",
            "value": "2m"
          },
          {
            "selected": false,
            "text": "3m",
            "value": "3m"
          },
          {
            "selected": false,
            "text": "5m",
            "value": "5m"
          },
          {
            "selected": false,
            "text": "7m",
            "value": "7m"
          },
          {
            "selected": false,
            "text": "10m",
            "value": "10m"
          },
          {
            "selected": false,
            "text": "30m",
            "value": "30m"
          },
          {
            "selected": false,
            "text": "1h",
            "value": "1h"
          },
          {
            "selected": false,
            "text": "6h",
            "value": "6h"
          },
          {
            "selected": false,
            "text": "12h",
            "value": "12h"
          },
          {
            "selected": false,
            "text": "1d",
            "value": "1d"
          },
          {
            "selected": false,
            "text": "7d",
            "value": "7d"
          },
          {
            "selected": false,
            "text": "14d",
            "value": "14d"
          },
          {
            "selected": false,
            "text": "30d",
            "value": "30d"
          }
        ],
        "query": "30s,1m,2m,3m,5m,7m,10m,30m,1h,6h,12h,1d,7d,14d,30d",
        "refresh": 2,
        "type": "interval"
      },
      {
        "allValue": null,
        "current": {},
        "datasource": "${DS_PROMETHEUS}",
        "hide": 0,
        "includeAll": false,
        "label": "Node",
        "multi": true,
        "name": "server",
        "options": [],
        "query": "label_values(node_boot_time, instance)",
        "refresh": 1,
        "regex": "/([^:]+):.*/",
        "sort": 0,
        "tagValuesQuery": null,
        "tags": [],
        "tagsQuery": null,
        "type": "query",
        "useTags": false
      }
    ]
  },
  "time": {
    "from": "now-24h",
    "to": "now"
  },
  "timepicker": {
    "refresh_intervals": [
      "5s",
      "10s",
      "30s",
      "1m",
      "5m",
      "15m",
      "30m",
      "1h",
      "2h",
      "1d"
    ],
    "time_options": [
      "5m",
      "15m",
      "1h",
      "6h",
      "12h",
      "24h",
      "2d",
      "7d",
      "30d"
    ]
  },
  "timezone": "browser",
  "title": "Docker and system monitoring",
  "uid": "fTo9rH2ik",
  "version": 12
}
0%