Blue and Green Deployment in real-life

Suppose we have a PaymentService:v1.0.0 (that is called Blue) running on our kubernetes cluster:

From here, the new version PaymentService:v1.1.0 (that is called Green) is deployed next to the old version without affecting its:

The new version of the application is deployed and can be tested for functionality and performance.

Once the testing results are successful, application traffic is switched from blue to green:

Let’s try it now!

What is Argo Rollouts?

Argo Rollouts is a Kubernetes controller and set of CRDs which provide advanced deployment capabilities such as blue-green, canary, canary analysis, experimentation, and progressive delivery features to Kubernetes.

We use Terraform and an argo terraform module that I have implemented in order to deploy Argo products.

Terraform-Argo-Module

modules/kubernetes_modules/argo/argo_rollouts.tf

resource "helm_release" "argo_rollouts" {

  for_each = var.argo_rollouts != null ? toset(["devops"]) : toset([])
  
  name       = var.argo_rollouts.name  

  repository = "https://argoproj.github.io/argo-helm"
  chart      = "argo-rollouts"
  version    = var.argo_rollouts.version
  namespace  = "argo-rollouts"
  create_namespace = true 


  dynamic "set" {
    for_each = var.argo_rollouts.sets

    content {
        name = set.key 
        value = set.value  
    }
  }

  values = var.argo_rollouts.values 
}

modules/kubernetes_modules/argo/variables.tf

variable "argo_rollouts" {

    type = object({
        name = string 
        sets = optional(map(string), {})
        values = optional(set(string), [])
        version = optional(string)

    })

    default = null
}

Blue Green Example Project

examples/bluegreen/main.tf

module "argo" {

    source = "../../modules/kubernetes_modules/argo"

    argo_rollouts = {
        name = "lupass"
        version = "2.31.0"

        values = [
            yamlencode(
                {
                    dashboard = {
                        enabled = true 
                        service = {
                            type = "LoadBalancer"
                        }
                    }
                }
            )
        ]
    }
}

Remember to define providers.tf in order to use kubernetes and helm providers and to connect to your cluster.

provider "kubernetes" {
  config_path    = "~/.kube/config"

}

provider "helm" {
  kubernetes {
    config_path = "~/.kube/config"
  }
}

Running terraform apply, we deploy Argo Rollouts on our target cluster.

Deploy Application to test blue green deployment

To obtain the advanced deployments capabilities, we need to specify our Application Manifest via Argo Rollout CRD: Rollout. It is the same of Kubernetes deployments plus a strategy block with which you can define your deployment strategy:



resource "kubernetes_namespace" "my_app" {

    metadata  {
        name = "my-app"
    }
}

resource "kubernetes_manifest" "super_hello" {

  manifest = {
    apiVersion = "argoproj.io/v1alpha1"
    kind = "Rollout"
    metadata = {
      name = "super-hello"
      namespace = kubernetes_namespace.my_app.metadata.0.name 

    }

    spec = {
        replicas = 3
        revisionHistoryLimit = 6
        selector = {
            matchLabels = {
                "app" = "super-hello"
            }
        }
        template = {
            metadata = {
                labels = {
                    "app" = "super-hello"
                }
            }
            spec = {
                containers = [
                    {
                        name = "super-hello"
                        image = "ghcr.io/gbaeke/super:1.0.2"
                        env = [
                            {
                                name = "WELCOME"
                                value = "VERSION V2"
                            }
                        ]
                        imagePullPolicy = "Always"
                        resources = {
                            requests = {
                                memory = "128Mi"
                                cpu = "50m"
                            }
                            limits = {
                                memory = "128Mi"
                                cpu = "50m"
                            }
                        }
                        readinessProbe = {
                            httpGet = {
                                path = "/healthz"
                                port = "8080"
                                initialDelaySeconds = 3
                                periodSeconds = 3
                            }
                        }
                    }
                ]
            }
        }
        strategy = {
            blueGreen = {
                activeService = kubernetes_service_v1.blue_green_prod.metadata.0.name
                previewService = kubernetes_service_v1.blue_green_preview.metadata.0.name
                autoPromotionEnabled = false 
            }
        }
    }


  }

  field_manager {
    force_conflicts = true 
  }

}

resource "kubernetes_service_v1" "blue_green_prod" {

    metadata {
        name = "super-hello-prod"
        namespace = kubernetes_namespace.my_app.metadata.0.name 
    }

    spec {
        selector = {
          "app" = "super-hello"    
        }

        port {
            port = 8088
            target_port = 8080
        }
        type = "LoadBalancer"
    }
  lifecycle {
        ignore_changes = [
            metadata.0.annotations["argo-rollouts.argoproj.io/managed-by-rollouts"],
            spec.0.selector["rollouts-pod-template-hash"],
        ]
    }
}


resource "kubernetes_service_v1" "blue_green_preview" {

    metadata {
        name = "super-hello-preview"
        namespace = kubernetes_namespace.my_app.metadata.0.name 
    }

    spec {
        selector = {
          "app" = "super-hello"    
        }

        port {
            port = 8089
            target_port = 8080
        }
        type = "LoadBalancer"
    }
  lifecycle {
        ignore_changes = [
            metadata.0.annotations["argo-rollouts.argoproj.io/managed-by-rollouts"],
            spec.0.selector["rollouts-pod-template-hash"],
        ]
    }
}

After that we have (for simplicity we draw only one pod in the image):

kubectl get all -n my-app

The SVC suer-hello-prod (and BalancerProd) is used for production traffic, instead of super-hello-preview (and Balancer Preview) that can be used in order to test future updates by Developers/Testers/SRE/...

If we do a HTTP GET request to BalancerProd:

curl http://192.168.93.140:8088 && echo
VERSION V2

And also it is exposed on preview side via BalancerPreview:

curl http://192.168.93.140:8089 && echo
VERSION V2

To see the status of our application , there is also

kubectl argo rollouts get rollout bluegreen-demo -n my-app — watch:

From Argo Rollout Dashboard UI:

Now, we update our manifest setting MESSAGE env variable with value “VERSION V3”

N.B: The image tag remains the same (1.0.2), but what we change is the MESSAGE that returns (from V2 to V3). But it’s the same if we change the tag version.

At this point, the Argo Rollout detect the changes and apply the strategy defined in the desired state of our Rollout Manifest.

As we can see, now we have this situation:

kubectl argo rollouts get rollout super-hello -n my-app — watch

Argo Rollouts Dashboard UI

k get all -n my-app

curl BalancerProd

 curl http://192.168.93.140:8088 && echo
VERSION V2

curl BalancerPreview

curl http://192.168.93.140:8089 && echo
VERSION V3

Once tested the functionality and the performance of super-hello:V3, we can promote the rollout and so switching to use super-hello:V3 in production:

> kubectl argo rollouts promote super-hello
rollout 'super-hello' promoted

So we have:

kubectl argo rollouts get

Argo Rollouts Dashboard UI

k get all -n my-app

curl BalancerProd

curl http://192.168.93.140:8088 && echo
VERSION V3

curl BalancerPreview

curl http://192.168.93.140:8089 && echo
VERSION V3

Finaly, the old super-hello:V2 is destroyed:

This way you can minimize downtime possibilities by ensuring service availability during updates. In contrast to blue-green deployments, there are canary deployments that allow a gradual upgrade between versions.

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Last updated 1 year ago