Flagger Install on EKS App Mesh

This guide walks you through setting up Flagger and AWS App Mesh on EKS.

App Mesh

The App Mesh integration with EKS is made out of the following components:

  • Kubernetes custom resources
    • mesh.appmesh.k8s.aws defines a logical boundary for network traffic between the services
    • virtualnode.appmesh.k8s.aws defines a logical pointer to a Kubernetes workload
    • virtualservice.appmesh.k8s.aws defines the routing rules for a workload inside the mesh
  • CRD controller - keeps the custom resources in sync with the App Mesh control plane
  • Admission controller - injects the Envoy sidecar and assigns Kubernetes pods to App Mesh virtual nodes
  • Telemetry service - Prometheus instance that collects and stores Envoy's metrics

Create a Kubernetes cluster

In order to create an EKS cluster you can use eksctl. Eksctl is an open source command-line utility made by Weaveworks in collaboration with Amazon.

On MacOS you can install eksctl with Homebrew:

brew tap weaveworks/tap
brew install weaveworks/tap/eksctl

Create an EKS cluster:

eksctl create cluster --name=appmesh \
--region=us-west-2 \
--nodes 3 \
--node-volume-size=120 \

The above command will create a two nodes cluster with App Mesh IAM policy attached to the EKS node instance role.

Verify the install with:

kubectl get nodes

Install Helm

Install the Helm command-line tool:

brew install kubernetes-helm

Create a service account and a cluster role binding for Tiller:

kubectl -n kube-system create sa tiller

kubectl create clusterrolebinding tiller-cluster-rule \
--clusterrole=cluster-admin \

Deploy Tiller in the kube-system namespace:

helm init --service-account tiller

You should consider using SSL between Helm and Tiller, for more information on securing your Helm installation see docs.helm.sh.

Enable horizontal pod auto-scaling

Install the Horizontal Pod Autoscaler (HPA) metrics provider:

helm upgrade -i metrics-server stable/metrics-server \
--namespace kube-system \
--set args[0]=--kubelet-preferred-address-types=InternalIP

After a minute, the metrics API should report CPU and memory usage for pods. You can very the metrics API with:

kubectl -n kube-system top pods

Install the App Mesh components

Create the appmesh-system namespace:

kubectl create ns appmesh-system

Apply the App Mesh CRDs:

kubectl apply -k github.com/aws/eks-charts/stable/appmesh-controller//crds

Add the EKS repository to Helm:

helm repo add eks https://aws.github.io/eks-charts

Install the App Mesh CRD controller:

helm upgrade -i appmesh-controller eks/appmesh-controller \
--wait --namespace appmesh-system

Install the App Mesh admission controller and create a mesh called global:

helm upgrade -i appmesh-inject eks/appmesh-inject \
--wait --namespace appmesh-system \
--set mesh.create=true \
--set mesh.name=global

Verify that the global mesh is active:

kubectl describe mesh

  Mesh Condition:
    Status:                True
    Type:                  MeshActive

In order to collect the App Mesh metrics that Flagger needs to run the canary analysis, you'll need to setup a Prometheus instance to scrape the Envoy sidecars.

Install the App Mesh Prometheus:

helm upgrade -i appmesh-prometheus eks/appmesh-prometheus \
--wait --namespace appmesh-system

Install Flagger and Grafana

Add Flagger Helm repository:

helm repo add flagger https://flagger.app

Install Flagger's Canary CRD:

kubectl apply -f https://raw.githubusercontent.com/weaveworks/flagger/master/artifacts/flagger/crd.yaml

Deploy Flagger in the appmesh-system namespace:

helm upgrade -i flagger flagger/flagger \
--namespace=appmesh-system \
--set crd.create=false \
--set meshProvider=appmesh \
--set metricsServer=http://appmesh-prometheus:9090

You can enable Slack or MS Teams notifications with:

helm upgrade -i flagger flagger/flagger \
--reuse-values \
--namespace=appmesh-system \
--set slack.url=https://hooks.slack.com/services/YOUR/SLACK/WEBHOOK \
--set slack.channel=general \
--set slack.user=flagger

Flagger comes with a Grafana dashboard made for monitoring the canary analysis. Deploy Grafana in the appmesh-system namespace:

helm upgrade -i flagger-grafana flagger/grafana \
--namespace=appmesh-system \
--set url=http://appmesh-prometheus:9090

You can access Grafana using port forwarding:

kubectl -n appmesh-system port-forward svc/flagger-grafana 3000:80

Now that you have Flagger running you can try the App Mesh canary deployments tutorial.