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Tom Chauveau bdcb917943 Add kubernetes test for kind deployment

Signed-off-by: Tom Chauveau <tom.chauveau@epitech.eu>

2021-09-01 11:15:02 +02:00

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slug
/1007/kubernetes/

Deploy to Kubernetes with Dagger

This tutorial illustrates how to use Dagger to build, push and deploy Docker images to Kubernetes.

import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';

Prerequisites

For this tutorial, you will need a Kubernetes cluster.

Kind is a tool for running local Kubernetes clusters using Docker.

1. Install kind

Follow these instructions to install Kind.

Alternatively, on macOS using homebrew:

brew install kind

2. Start a local registry

docker run -d -p 5000:5000 --name registry registry:2

3. Create a cluster with the local registry enabled in containerd

cat <<EOF | kind create cluster --config=-
kind: Cluster
apiVersion: kind.x-k8s.io/v1alpha4
containerdConfigPatches:
- |-
  [plugins."io.containerd.grpc.v1.cri".registry.mirrors."localhost:5000"]
    endpoint = ["http://registry:5000"]
EOF

4. Connect the registry to the cluster network

docker network connect kind registry

This tutorial can be run against a GCP GKE cluster and GCR. You can follow this GCP documentation to create a GKE cluster. You will also need to create a kubeconfig .

This tutorial can be run against a AWS EKS cluster and ECR . You can follow this AWS documentation to create an EKS cluster. You will also need to create a kubeconfig.

Initialize a Dagger Workspace and Environment

(optional) Setup example app

You will need the local copy of the Dagger examples repository used in previous guides

git clone https://github.com/dagger/examples

Make sure that all commands are run from the todoapp directory:

cd examples/todoapp

(optional) Initialize a Cue module

This guide will use the same directory as the root of the Dagger workspace and the root of the Cue module, but you can create your Cue module anywhere inside the Dagger workspace.

cue mod init

Organize your package

Let's create a new directory for our Cue package:

mkdir kube

Deploy using Kubectl

Kubernetes objects are located inside the k8s folder:

ls -l k8s
# k8s
# ├── deployment.yaml
# └── service.yaml

# 0 directories, 2 files

As a starting point, let's deploy them manually with kubectl:

kubectl apply -f k8s/
# deployment.apps/todoapp created
# service/todoapp-service created

Verify that the deployment worked:

kubectl get deployments
# NAME      READY   UP-TO-DATE   AVAILABLE   AGE
# todoapp   1/1     1            1           10m

kubectl get service
# NAME              TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)        AGE
# todoapp-service   NodePort    10.96.225.114   <none>        80:32658/TCP   11m

The next step is to transpose it in Cue. Before continuing, clean everything:

kubectl delete -f k8s/
# deployment.apps "todoapp" deleted
# service "todoapp-service" deleted

Create a basic plan

Create a file named todoapp.cue and add the following configuration to it.

This defines a todoApp variable containing the Kubernetes objects used to create a todoapp deployment. It also references a kubeconfig value defined below:

The following config.cue defines:

kubeconfig a generic value created to embed this string kubeconfig value

The below config.cue defines:

kubeconfig a generic value created to embbed this gke.#KubeConfig value
gcpConfig: connection to Google using alpha.dagger.io/gcp
gkeConfig: transform a gcpConfig to a readable format for kubernetes.#Resources.kubeconfig using alpha.dagger.io/gcp/gke

package main

import (
 "alpha.dagger.io/gcp"
 "alpha.dagger.io/gcp/gke"
)

// Value created for generic reference of `kubeconfig` in `todoapp.cue`
kubeconfig: gkeConfig.kubeconfig

// gcpConfig used for Google connection
gcpConfig: gcp.#Config

// gkeConfig used for deployment
gkeConfig: gke.#KubeConfig & {
 // config field references `gkeConfig` value to set in once
 config: gcpConfig
}

The below config.cue defines:

kubeconfig, a generic value created to embbed this eksConfig.kubeconfig value
awsConfig, connection to Amazon using alpha.dagger.io/aws
eksConfig, transform a awsConfig to a readable format for kubernetes.#Resources.kubeconfig using alpha.dagger.io/aws/eks

package main

import (
 "alpha.dagger.io/aws"
 "alpha.dagger.io/aws/eks"
)

// Value created for generic reference of `kubeconfig` in `todoapp.cue`
kubeconfig: eksConfig.kubeconfig

// awsConfig for Amazon connection
awsConfig: aws.#Config

// eksConfig used for deployment
eksConfig: eks.#KubeConfig & {
 // config field references `gkeConfig` value to set in once
 config: awsConfig
}

Setup the environment

Create a new environment

Now that your Cue package is ready, let's create an environment to run it:

dagger new 'kube' -p kube

Configure the environment

Before we can bring up the deployment, we need to provide the kubeconfig input declared in the configuration. Otherwise, Dagger will complain about a missing input:

dagger up -e kube
# 5:05PM ERR system | required input is missing    input=kubeconfig
# 5:05PM ERR system | required input is missing    input=manifest
# 5:05PM FTL system | some required inputs are not set, please re-run with `--force` if you think it's a mistake    missing=0s

You can inspect the list of inputs (both required and optional) using dagger input list:

dagger input list -e kube
# Input              Value                Set by user  Description
# kubeconfig         string               false        set with `dagger input text kubeconfig -f "$HOME"/.kube/config -e kube`
# manifest           dagger.#Artifact     false        input: source code repository, must contain a Dockerfile set with `dagger input dir manifest ./k8s -e kube`
# todoApp.namespace  *"default" | string  false        Kubernetes Namespace to deploy to
# todoApp.version    *"v1.19.9" | string  false        Version of kubectl client

dagger input list -e kube
# Input                  Value                Set by user  Description
# gcpConfig.region       string               false        GCP region
# gcpConfig.project      string               false        GCP project
# gcpConfig.serviceKey   dagger.#Secret       false        GCP service key
# manifest               dagger.#Artifact     false        input: source code repository, must contain a Dockerfile set with `dagger input dir manifest ./k8s -e kube`
# gkeConfig.clusterName  string               false        GKE cluster name
# gkeConfig.version      *"v1.19.9" | string  false        Kubectl version
# todoApp.namespace      *"default" | string  false        Kubernetes Namespace to deploy to
# todoApp.version        *"v1.19.9" | string  false        Version of kubectl client

dagger input list -e kube
# Input                  Value                Set by user  Description
# awsConfig.region       string               false        AWS region
# awsConfig.accessKey    dagger.#Secret       false        AWS access key
# awsConfig.secretKey    dagger.#Secret       false        AWS secret key
# manifest               dagger.#Artifact     false        input: source code repository, must contain a Dockerfile set with `dagger input dir manifest ./k8s -e kube`
# eksConfig.clusterName  string               false        EKS cluster name
# eksConfig.version      *"v1.19.9" | string  false        Kubectl version
# todoApp.namespace      *"default" | string  false        Kubernetes Namespace to deploy to
# todoApp.version        *"v1.19.9" | string  false        Version of kubectl client

Let's provide the missing inputs:

# we'll use the "$HOME"/.kube/config created by `kind`
dagger input text kubeconfig -f "$HOME"/.kube/config -e kube

# Add as an artifact the k8s folder
dagger input dir manifest ./k8s -e kube

# Add as an artifact the k8s folder
dagger input dir manifest ./k8s -e kube

# Add Google credentials
dagger input text gcpConfig.project <PROJECT> -e kube
dagger input text gcpConfig.region <REGION> -e kube
dagger input secret gcpConfig.serviceKey -f <PATH TO THE SERVICEKEY.json> -e kube

#  Add GKE clusterName
dagger input text gkeConfig.clusterName <GKE CLUSTER NAME> -e kube

# Add as an artifact the k8s folder
dagger input dir manifest ./k8s -e kube

# Add Amazon credentials
dagger input text awsConfig.region <REGION> -e kube
dagger input secret awsConfig.accessKey <ACCESS KEY> -e kube
dagger input secret awsConfig.secretKey <SECRET KEY> -e kube

# Add EKS clustername
dagger input text eksConfig.clusterName <EKS CLUSTER NAME> -e kube

Deploying

Now is time to deploy to Kubernetes.

dagger up -e kube
# deploy | computing
# deploy | #26 0.700 deployment.apps/todoapp created
# deploy | #27 0.705 service/todoapp-service created
# deploy | completed    duration=1.405s

Let's verify if the deployment worked:

kubectl get deployments
# NAME    READY   UP-TO-DATE   AVAILABLE   AGE
# todoapp   1/1     1            1           1m

Before continuing, cleanup deployment:

kubectl delete -f k8s/
# deployment.apps "todoapp" deleted
# service "todoapp-service" deleted

Building, pushing, and deploying Docker images

Rather than deploying an existing (todoapp) image, we're going to build a Docker image from the source, push it to a registry, and update the Kubernetes configuration.

Update the plan

Let's see how to deploy an image locally and push it to the local cluster

kube/todoapp.cue faces these changes:

repository, source code of the app to build. It needs to have a Dockerfile
registry, URI of the registry to push to
image, build of the image
remoteImage, push an image to the registry
kustomization, apply kustomization to image

Let's see how to leverage GCR and GKE packages.

The two files have to be edited to do so.

kube/config.cue configuration has following change:

definition of a new ecrCreds value that contains ecr credentials for remote image push to GCR

package main

import (
 "alpha.dagger.io/gcp"
 "alpha.dagger.io/gcp/gcr"
 "alpha.dagger.io/gcp/gke"
)

// Value created for generic reference of `kubeconfig` in `todoapp.cue`
kubeconfig: gkeConfig.kubeconfig

// gcpConfig used for Google connection
gcpConfig: gcp.#Config

// gkeConfig used for deployment
gkeConfig: gke.#KubeConfig & {
 // config field references `gkeConfig` value to set in once
 config: gcpConfig
}

// gcrCreds used for remote image push
gcrCreds: gcr.#Credentials & {
 // config field references `gcpConfig` value to set in once
  config: gcpConfig
}

kube/todoapp.cue, on the other hand, faces these changes:

repository, source code of the app to build. It needs to have a Dockerfile
registry, URI of the registry to push to
image, build of the image
remoteImage, push an image to the registry
kustomization, apply kustomization to image

package main

import (
  "encoding/yaml"

  "alpha.dagger.io/dagger"
  "alpha.dagger.io/docker"
  "alpha.dagger.io/kubernetes"
  "alpha.dagger.io/kubernetes/kustomize"
)

// input: source code repository, must contain a Dockerfile
// set with `dagger input dir repository . -e kube`
repository: dagger.#Artifact & dagger.#Input

// GCR registry to push images to
registry: string & dagger.#Input
tag:      "test-gcr"

// source of Kube config file.
// set with `dagger input dir manifest ./k8s -e kube`
manifest: dagger.#Artifact & dagger.#Input

// Declarative name
todoApp: {
  // Build an image from the project repository
  image: docker.#Build & {
    source: repository
  }

  // Push the image to a remote registry
  remoteImage: docker.#Push & {
    target: "\(registry):\(tag)"
    source: image
    auth: {
      username: gcrCreds.username
      secret:   gcrCreds.secret
    }
  }

  // Update the image of the deployment to the deployed image
  kustomization: kustomize.#Kustomize & {
    source:        manifest

    // Convert CUE to YAML.
    kustomization: yaml.Marshal({
      resources: ["deployment.yaml", "service.yaml"]

      images: [{
        name:    "public.ecr.aws/j7f8d3t2/todoapp"
        newName: remoteImage.ref
      }]
    })
  }

  // Value created for generic reference of `kubeconfig` in `todoapp.cue`
  kubeSrc: kubernetes.#Resources & {
    "kubeconfig": kubeconfig
    source:     kustomization
  }
}

Let's see how to leverage ECR and EKS packages.

The two files have to be edited to do so.

kube/config.cue configuration has following change:

definition of a new ecrCreds value that contains ecr credentials for remote image push to ECR

package main

import (
 "alpha.dagger.io/aws"
 "alpha.dagger.io/aws/eks"
 "alpha.dagger.io/aws/ecr"
)

// Value created for generic reference of `kubeconfig` in `todoapp.cue`
kubeconfig: eksConfig.kubeconfig

// awsConfig for Amazon connection
awsConfig: aws.#Config

// eksConfig used for deployment
eksConfig: eks.#KubeConfig & {
 // config field references `awsConfig` value to set in once
 config: awsConfig
}

// ecrCreds used for remote image push
ecrCreds: ecr.#Credentials & {
 // config field references `awsConfig` value to set in once
  config: awsConfig
}

kube/todoapp.cue, on the other hand, faces these changes:

repository, source code of the app to build. It needs to have a Dockerfile
registry, URI of the registry to push to
image, build of the image
remoteImage, push an image to the registry
kustomization, apply kustomization to image

package main

import (
  "encoding/yaml"

  "alpha.dagger.io/dagger"
  "alpha.dagger.io/docker"
  "alpha.dagger.io/kubernetes"
  "alpha.dagger.io/kubernetes/kustomize"
)

// input: source code repository, must contain a Dockerfile
// set with `dagger input dir repository . -e kube`
repository: dagger.#Artifact & dagger.#Input

// ECR registry to push images to
registry: string & dagger.#Input
tag:      "test-ecr"

// source of Kube config file.
// set with `dagger input dir manifest ./k8s -e kube`
manifest: dagger.#Artifact & dagger.#Input

todoApp: {
  // Build an image from the project repository
  image: docker.#Build & {
    source: repository
  }

  // Push the image to a remote registry
  remoteImage: docker.#Push & {
    target: "\(registry):\(tag)"
    source: image
    auth: {
      username: ecrCreds.username
      secret:   ecrCreds.secret
    }
  }

  // Update the image of the deployment to the deployed image
  kustomization: kustomize.#Kustomize & {
    source:        manifest

    // Convert CUE to YAML.
    kustomization: yaml.Marshal({
      resources: ["deployment.yaml", "service.yaml"]

      images: [{
        name:    "public.ecr.aws/j7f8d3t2/todoapp"
        newName: remoteImage.ref
      }]
    })
  }

  // Value created for generic reference of `kubeconfig` in `todoapp.cue`
  kubeSrc: kubernetes.#Resources & {
    "kubeconfig": kubeconfig
    source:     kustomization
  }
}

Connect the Inputs

Next, we'll provide the two new inputs, repository and registry.

# A name after `localhost:5000/` is required to avoid error on push to the local registry
dagger input text registry "localhost:5000/kind" -e kube

# Add todoapp (current folder) to repository value
dagger input dir repository . -e kube

Next, we'll provide the two new inputs, repository and registry.

# Add registry to export built image to
dagger input text registry <URI> -e kube

# Add todoapp (current folder) to repository value
dagger input dir repository . -e kube

Next, we'll provide the two new inputs, repository and registry.

# Add registry to export built image to
dagger input text registry <URI> -e kube

# Add todoapp (current folder) to repository value
dagger input dir repository . -e kube

Bring up the changes

dagger up -e kube
# 4:09AM INF manifest | computing
# 4:09AM INF repository | computing
# ...
# 4:09AM INF todoApp.kubeSrc | #37 0.858 service/todoapp-service created
# 4:09AM INF todoApp.kubeSrc | #37 0.879 deployment.apps/todoapp created
# Output                      Value                                                                                                              Description
# todoApp.remoteImage.ref     "localhost:5000/kind:test-kind@sha256:cb8d92518b876a3fe15a23f7c071290dfbad50283ad976f3f5b93e9f20cefee6"            Image ref
# todoApp.remoteImage.digest  "sha256:cb8d92518b876a3fe15a23f7c071290dfbad50283ad976f3f5b93e9f20cefee6"                                          Image digest

Let's verify if the deployment worked:

kubectl get deployments
# NAME      READY   UP-TO-DATE   AVAILABLE   AGE
# todoapp   1/1     1            1           50s

Before continuing, cleanup deployment:

kubectl delete -f k8s/
# deployment.apps "todoapp" deleted
# service "todoapp-service" deleted

CUE Kubernetes manifest

This section will convert Kubernetes YAML manifest from k8s directory to CUE to take advantage of the language features.

For a more advanced example, see the official CUE Kubernetes tutorial

Convert Kubernetes objects to CUE

First, let's create re-usable definitions for the deployment and the service to remove a lot of boilerplate and repetition.

Let's define a re-usable #Deployment definition in kube/deployment.cue.

package main

// Deployment template containing all the common boilerplate shared by
// deployments of this application.
#Deployment: {
  // Name of the deployment. This will be used to label resources automatically
  // and generate selectors.
  name: string

  // Container image.
  image: string

  // 80 is the default port.
  port: *80 | int

  // 1 is the default, but we allow any number.
  replicas: *1 | int

  // Deployment manifest. Uses the name, image, port and replicas above to
  // generate the resource manifest.
  manifest: {
    apiVersion: "apps/v1"
    kind:       "Deployment"
    metadata: {
      "name": name
      labels: app: name
    }
    spec: {
      "replicas": replicas
      selector: matchLabels: app: name
      template: {
        metadata: labels: app: name
        spec: containers: [{
          "name":  name
          "image": image
          ports: [{
            containerPort: port
          }]
        }]
      }
    }
  }
}

Indeed, let's also define a re-usable #Service definition in kube/service.cue.

package main

// Service template containing all the common boilerplate shared by
// services of this application.
#Service: {
  // Name of the service. This will be used to label resources automatically
  // and generate selector.
  name: string

  // NodePort is the default service type.
  type: *"NodePort" | "LoadBalancer" | "ClusterIP" | "ExternalName"

  // Ports where the service should listen
  ports: [string]: number

  // Service manifest. Uses the name, type and ports above to
  // generate the resource manifest.
  manifest: {
    apiVersion: "v1"
    kind:       "Service"
    metadata: {
      "name": "\(name)-service"
      labels: app: name
    }
    spec: {
      "type": type
        "ports": [
          for k, v in ports {
            "name": k
            port:   v
          },
        ]
        selector: app: name
    }
  }
}

Generate Kubernetes manifest

Now that you have generic definitions for your Kubernetes objects. You can use them to get back your YAML definition without having boilerplate nor repetition.

Create a new definition named #AppManifest that will generate the YAML in kube/manifest.cue.

package main

import (
  "encoding/yaml"
)

// Define and generate kubernetes deployment to deploy to kubernetes cluster
#AppManifest: {
  // Name of the application
  name: string

  // Image to deploy to
  image: string

  // Define a kubernetes deployment object
  deployment: #Deployment & {
    "name": name
    "image": image
  }

  // Define a kubernetes service object
  service: #Service & {
    "name": name
    ports: "http": deployment.port
  }

  // Merge definitions and convert them back from CUE to YAML
  manifest: yaml.MarshalStream([deployment.manifest, service.manifest])
}

Update manifest

You can now remove the manifest input in kube/todoapp.cue and instead use the manifest created by #AppManifest.

kube/todoapp.cue configuration has following changes:

removal of unused imported encoding/yaml and kustomize packages.
removal of manifest input that is doesn't need anymore.
removal of kustomization to replace it with #AppManifest definition.
Update kubeSrc to use manifest field instead of source because we don't send Kubernetes manifest of dagger.#Artifact type anymore.

package main

import (
  "alpha.dagger.io/dagger"
  "alpha.dagger.io/docker"
  "alpha.dagger.io/kubernetes"
)

// input: source code repository, must contain a Dockerfile
// set with `dagger input dir repository . -e kube`
repository: dagger.#Artifact & dagger.#Input

// Registry to push images to
registry: string & dagger.#Input
tag:      "test-kind"

// Todoapp deployment pipeline
todoApp: {
  // Build the image from repositoru artifact
  image: docker.#Build & {
    source: repository
  }

  // Push image to registry
  remoteImage: docker.#Push & {
    target: "\(registry):\(tag)"
    source: image
  }

  // Generate deployment manifest
  deployment: #AppManifest & {
    name:  "todoapp"
    image: remoteImage.ref
  }

  // Deploy the customized manifest to a kubernetes cluster
  kubeSrc: kubernetes.#Resources & {
    "kubeconfig": kubeconfig
    manifest:     deployment.manifest
  }
}

package main

import (
  "alpha.dagger.io/dagger"
  "alpha.dagger.io/docker"
  "alpha.dagger.io/kubernetes"
)

// input: source code repository, must contain a Dockerfile
// set with `dagger input dir repository . -e kube`
repository: dagger.#Artifact & dagger.#Input

// GCR registry to push images to
registry: string & dagger.#Input
tag:      "test-gcr"

// Todoapp deployment pipeline
todoApp: {
  // Build the image from repositoru artifact
  image: docker.#Build & {
    source: repository
  }

  // Push image to registry
  remoteImage: docker.#Push & {
    target: "\(registry):\(tag)"
    source: image
    auth: {
      username: gcrCreds.username
      secret:   gcrCreds.secret
    }
  }

  // Generate deployment manifest
  deployment: #AppManifest & {
    name:  "todoapp"
    image: remoteImage.ref
  }

  // Deploy the customized manifest to a kubernetes cluster
  kubeSrc: kubernetes.#Resources & {
    "kubeconfig": kubeconfig
    manifest:     deployment.manifest
  }
}

package main

import (
  "alpha.dagger.io/dagger"
  "alpha.dagger.io/docker"
  "alpha.dagger.io/kubernetes"
)

// input: source code repository, must contain a Dockerfile
// set with `dagger input dir repository . -e kube`
repository: dagger.#Artifact & dagger.#Input

// ECR registry to push images to
registry: string & dagger.#Input
tag:      "test-ecr"

// Todoapp deployment pipeline
todoApp: {
  // Build the image from repositoru artifact
  image: docker.#Build & {
    source: repository
  }

  // Push image to registry
  remoteImage: docker.#Push & {
    target: "\(registry):\(tag)"
    source: image
    auth: {
      username: ecrCreds.username
      secret:   ecrCreds.secret
    }
  }

  // Generate deployment manifest
  deployment: #AppManifest & {
    name:  "todoapp"
    image: remoteImage.ref
  }

  // Deploy the customized manifest to a kubernetes cluster
  kubeSrc: kubernetes.#Resources & {
    "kubeconfig": kubeconfig
    manifest:     deployment.manifest
  }
}

Remove unused input

Now that we manage our Kubernetes manifest in CUE, we don't need manifest anymore.

# Remove `manifest` input
dagger input unset manifest -e kube

Deployment

dagger up -e kube
# 4:09AM INF manifest | computing
# 4:09AM INF repository | computing
# ...
# 4:09AM INF todoApp.kubeSrc | #37 0.858 service/todoapp-service created
# 4:09AM INF todoApp.kubeSrc | #37 0.879 deployment.apps/todoapp created
# Output                      Value                                                                                                              Description
# todoApp.remoteImage.ref     "localhost:5000/kind:test-kind@sha256:cb8d91518b076a3fe15a33f7c171290dfbad50283ad976f3f5b93e9f33cefag7"            Image ref
# todoApp.remoteImage.digest  "sha256:cb8d91518b076a3fe15a33f7c171290dfbad50283ad976f3f5b93e9f33cefag7"                                          Image digest

Let's verify that the deployment worked:

kubectl get deployments
# NAME      READY   UP-TO-DATE   AVAILABLE   AGE
# todoapp   1/1     1            1           37s

Next Steps

Integrate Helm with Dagger:

Helm

28 KiB Raw Blame History

Deploy to Kubernetes with Dagger

Prerequisites

Initialize a Dagger Workspace and Environment

(optional) Setup example app

(optional) Initialize a Cue module

Organize your package

Deploy using Kubectl

Create a basic plan

Setup the environment

Create a new environment

Configure the environment

Deploying

Building, pushing, and deploying Docker images

Update the plan

Connect the Inputs

Bring up the changes

CUE Kubernetes manifest

Convert Kubernetes objects to CUE

Generate Kubernetes manifest

Update manifest

Remove unused input

Deployment

Next Steps

28 KiB

Raw Blame History