Your one-stop shop platform for GitOps CI/CD, Machine learning workflows, service mesh and observability

application	View
Deploy an EKS cluster using Terraform	README
Istio ingress gateway and secure service mesh	README
Argo CD	README
Argo events	README
Argo workflows	README
Prometheus and Grafana	Installed from Helm charts using Argo CD
MLflow	README
minio artifact storage	README
ngrok	README
task-tracker app (MERN stack demo)	README
sealed-secrets	Installed from Helm charts using Argo CD
Seldon-core	Installed from Helm charts using Argo CD

start local cluster using minikube

kubernetes version has to be less than 1.25 for seldon to work

kind create cluster --name kind-cluster --config kind.yaml --wait 5m

To delete the cluster:

kind delete cluster --name kind-cluster

When you run kubectl api-versions | grep beta you will see that autoscaling/v2beta1 is there and seldon won't complain.

Use argocd to deploy applications to our Kubernetes cluster

In a different project folder, clone the repo which has our ArgoCD project and application manifests

git clone git@github.com:davidfox87/argocd-production.git

Install projects and apps

kubectl apply -f projects.yaml
kubectl apply -f apps.yaml

deploy the secrets in the workflows namespace

Inside terraform-argocd/applications/argo-workflows/overlays/workflows/

./deploy_secrets

commit and push to github repo so argocd can manage sealedsecrets deployment. You need to add a .env file containing github access token

wait for everything to sync and be healthy in the argo-cd UI

The following screenshot shows the applications that argocd has deployed into our EKS cluster either from our own kustomize application manifests or third-party helm charts. argocd

do some admin

create argo-artifacts bucket called my-bucket create PVC by applying applications/argo-workflows/overlays/workflows/models/wine/base/pvc.yaml in workflows namespace

install argocli to submit workflows

argo submit -n workflows --watch train.yaml

check the deployment of the REST prediction service

kubectl get sdep -n workflows
kubectl -n workflows get sdep seldon-deployment-deploy-wine-clf-hhrxn -o json | jq .status

Send requests to prediction service

Locally we can port-forward to the istio-ingressgateway service and send requests to that:

kubectl port-forward -n istio-system svc/istio-ingressgateway 8080:80

Send requests to our prediction service

curl -X POST      -H 'Content-Type: application/json'  \
    -d '{"data": { "ndarray": [[1,2,3,4,5]]}}'   \
        http://localhost:8080/seldon/workflows/seldon-deployment-deploy-wine-clf-hhrxn/api/v1.0/predictions

{"data":{"names":["t:0","t:1","t:2","t:3","t:4"],"ndarray":[[1,2,3,4,5]]},"meta":{"requestPath":{"wine-clf":"foxy7887/wine-model:v10"}}}

look at the stats from the training run in MLFlow repo

kubectl port-forward service/mlflow-tracking-server 5555:5000 -n mlflow
http://localhost:5555

apply ingress object

The ingress object has a backend that points to istio-ingressgateway. Apply the object to the istio-system namespace:

kubectl apply -f istio-1-15/istio-resources/ingress.yaml -n istio-system

The AWS ALB Ingress Controller will create a TargetGroup to be used with the ALB The Gateway and VirtualService that will configure Envoy of the Istio Ingress Gateway to route traffic to the service of the application.

Map the domain name that is associated with ACM certificate to the ALB just spawned

Note this should be automated using Crossplane route53

Our true GitOps CI/CD platform

Please see MLOps.pdf for a full explanation of this platform and the problems it solves

davidfox87 / crossplane-eks-argocd-mlops

readme