Progressive Delivery Masterclass

Learn how build a full progressive delivery example, which separates delivery from release management and progressively rolls out a new release and does targeted rollbacks via adjusting targeting rules on the fly.

The application

This is a very simple node.js application which simply changes text based on a feature flag

OpenFeature

The example uses OpenFeature to write feature management code in a vendor agnostic way

OpenTelemetry

OpenTelemetry is used for traces and metrics.

Keptn

The Keptn Lifecycle Toolkit is used for validating the delivery of new artifacts.

Setup a Kind Cluster with nginx ingress controller

Create Kind Cluster which exposes Port 80 and 443

kind create cluster --config ./cluster/kind-cluster.yaml

Install NGINX Ingress controller

kubectl apply -f https://raw.githubusercontent.com/kubernetes/ingress-nginx/main/deploy/static/provider/kind/deploy.yaml

kubectl wait --namespace ingress-nginx \
  --for=condition=ready pod \
  --selector=app.kubernetes.io/component=controller \
  --timeout=90s

Apply ingress.yaml to expose the application via http://127.0.0.1.nip.io

kubectl apply -f manifests/ingress.yaml

Install Keptn Lifecycle Controller

helm repo add klt https://charts.lifecycle.keptn.sh &&
helm repo update &&
helm upgrade --install keptn klt/klt --version v0.2.5 --namespace keptn-lifecycle-toolkit-system --create-namespace --wait

Afterwards, we can configure KLT to send OpenTelemetry data to a collector applying the following manifest, assuming the collector is installed in the default namespace.

kubectl apply -f - <<EOF
apiVersion: options.keptn.sh/v1alpha1
kind: KeptnConfig
metadata:
  name: keptnconfig-sample
spec:
  OTelCollectorUrl: 'otel-collector:4317'
  keptnAppCreationRequestTimeoutSeconds: 30
EOF

Install Prometheus and Grafana

The following command sets up the CRDs necessary for the Prometheus Operator to work.

kubectl apply --server-side -f manifests/platform/prometheus-grafana/setup &&
kubectl wait --for=condition=Established --all CustomResourceDefinition --namespace=monitoring

Once the resources are available, we can install the Prometheus resources and Grafana. The following command also pre-configure Grafana with dashboards to visualize traces and metrics exposed by KLT.

kubectl apply -f manifests/platform/prometheus-grafana/ &&
kubectl wait --for=condition=available deployment/prometheus-operator -n monitoring --timeout=120s &&
kubectl wait --for=condition=available deployment/prometheus-adapter -n monitoring --timeout=120s &&
kubectl wait --for=condition=available deployment/kube-state-metrics -n monitoring --timeout=120s &&
kubectl wait --for=condition=available deployment/grafana -n monitoring --timeout=120s

flagD

The application uses flag as a feature evaluation engine. flagD will automatically get injected using the OpenFeature operator

Install Cert Manager

kubectl apply -f https://github.com/cert-manager/cert-manager/releases/download/v1.10.1/cert-manager.yaml &&
kubectl wait --for=condition=Available=True deploy --all -n 'cert-manager'

Install Helm Release

helm repo add openfeature https://open-feature.github.io/open-feature-operator/ &&
helm repo update &&
helm upgrade --install openfeature openfeature/open-feature-operator

Upgrading

helm upgrade --install openfeature openfeature/open-feature-operator

GitOps

Install ArgoCD

kubectl create namespace argocd
kubectl apply -n argocd -f https://raw.githubusercontent.com/argoproj/argo-cd/stable/manifests/install.yaml

Get your initial password

argocd admin initial-password -n argocd

Port Forward

kubectl port-forward svc/argocd-server -n argocd 8080:443

pichlermarc/progressiveDelivery-masterclass