JHipster VS metrics-server

An easy way to get a pre-configured Keycloak instance is to use JHipster's jhipster-sample-app-oauth2 application. It gets updated with every JHipster release. You can clone it with the following command:

provider "auth0" { domain = "https://" debug = false } # Create a new Auth0 application for the JHipster app resource "auth0_client" "java_ms_client" { name = "JavaMicroservices" description = "Java Microservices Client Created Through Terraform" app_type = "regular_web" callbacks = ["http://localhost:8080/login/oauth2/code/oidc"] allowed_logout_urls = ["http://localhost:8080"] oidc_conformant = true jwt_configuration { alg = "RS256" } } # Configuring client_secret_post as an authentication method. resource "auth0_client_credentials" "java_ms_client_creds" { client_id = auth0_client.java_ms_client.id authentication_method = "client_secret_post" } # Create roles for the JHipster app resource "auth0_role" "admin" { name = "ROLE_ADMIN" description = "Administrator" } resource "auth0_role" "user" { name = "ROLE_USER" description = "User" } # Create an action to customize the authentication flow to add the roles and the username to the access token claims expected by JHipster applications. resource "auth0_action" "jhipster_action" { name = "jhipster_roles_claim" runtime = "node18" deploy = true code = <<-EOT /** * Handler that will be called during the execution of a PostLogin flow. * * @param {Event} event - Details about the user and the context in which they are logging in. * @param {PostLoginAPI} api - Interface whose methods can be used to change the behavior of the login. */ exports.onExecutePostLogin = async (event, api) => { const namespace = 'https://www.jhipster.tech'; if (event.authorization) { api.idToken.setCustomClaim(namespace + '/roles', event.authorization.roles); api.accessToken.setCustomClaim(namespace + '/roles', event.authorization.roles); } }; EOT supported_triggers { id = "post-login" version = "v3" } } # Attach the action to the login flow resource "auth0_trigger_actions" "login_flow" { trigger = "post-login" actions { id = auth0_action.jhipster_action.id display_name = auth0_action.jhipster_action.name } } # Create a test user. You can create more users here if needed resource "auth0_user" "test_user" { connection_name = "Username-Password-Authentication" name = "Jane Doe" email = "[email protected]" email_verified = true password = "passpass$12$12" # Don't set passwords like this in production! Use env variables instead. lifecycle { ignore_changes = [roles] } } resource "auth0_user_roles" "test_user_roles" { user_id = auth0_user.test_user.id roles = [auth0_role.admin.id, auth0_role.user.id] } output "auth0_webapp_client_id" { description = "Auth0 JavaMicroservices Client ID" value = auth0_client.java_ms_client.client_id } output "auth0_webapp_client_secret" { description = "Auth0 JavaMicroservices Client Secret" value = auth0_client_credentials.java_ms_client_creds.client_secret sensitive = true }

If you want a Spring backend with an Angular Frontend check out https://www.jhipster.tech. This is very nice for CRUD stuff.

Use https://www.jhipster.tech/

To test GitHub Actions, we need a new project which in this case I generated using JHipster with the configuration seen here:

exports.onExecutePostLogin = async (event, api) => { const namespace = 'https://www.jhipster.tech'; if (event.authorization) { api.idToken.setCustomClaim('preferred_username', event.user.email); api.idToken.setCustomClaim(`${namespace}/roles`, event.authorization.roles); api.accessToken.setCustomClaim(`${namespace}/roles`, event.authorization.roles); } }

What you maybe asking for is something like vaadin or jhipster which marries the front with the backend. (I don't like them tbh but it worth mentioning)

You can try this stack https://www.jhipster.tech with generator for mobile app https://github.com/jhipster/generator-jhipster-ionic.

The last one is mostly an observability stack with Prometheus, Metric server, and Prometheus adapter to have excellent insights into what is happening on the cluster. You can reuse the same stack for autoscaling by repurposing all the data collected for monitoring.

and the Metrics Server.

Metrics-server is installed by default on OVH, and has to be installed manually on AWS/EKS cluster.

I have also installed metrics-server (though not sure whether that was required or not) using the following statement:kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/download/v0.3.6/components.yaml

For #2: There are MANY solutions but the simplest and easiest is https://github.com/kubernetes-sigs/metrics-server and then you can use kubectl top to view pods resource usage. If you want fancy graphs, long retention, alerting, analysis, etc. of resource metrics.. then you need to use something like new relic, data dog, or something open source but much more complex like prometheus/thanos/grafana.. or a managed SaaS version of those open source tools... also some k8s platforms like AWS, Spot.io, GKE, OpenShift, may have this stuff built in or turnkey

It's an autoscaler with a metrics server (so I don't need to install 2 different tools).

Sure, here's an example of how to configure the Kubernetes Metrics Server along with the Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) configurations we provided earlier. The Metrics Server is a Kubernetes add-on that provides resource utilization metrics for pods and nodes, which are used by the HPA and VPA to determine when and how to scale an application. First, you'll need to install the Metrics Server into your Kubernetes cluster. You can do this by running the following command: kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml Once the Metrics Server is installed, you can configure your HPA and VPA to use it for metrics by adding the following annotation to your deployment: apiVersion: apps/v1 kind: Deployment metadata: name: my-app annotations: autoscaling.alpha.kubernetes.io/metrics-provider: "metrics-server" With this annotation in place, the HPA and VPA will use the Metrics Server to obtain CPU and memory utilization metrics for your pods and nodes. Here's an updated example of the HPA configuration we provided earlier, with the addition of the Metrics Server configuration: apiVersion: autoscaling/v2beta2 kind: HorizontalPodAutoscaler metadata: name: my-app-hpa spec: scaleTargetRef: apiVersion: apps/v1 kind: Deployment name: my-app minReplicas: 1 maxReplicas: 10 metrics: - type: Resource resource: name: cpu targetAverageUtilization: 50 - type: Resource resource: name: memory targetAverageUtilization: 80 In this example, we've added a second metric to the HPA configuration that targets memory utilization at 80%. Here's an updated example of the VPA configuration we provided earlier, with the addition of the Metrics Server configuration: apiVersion: autoscaling.k8s.io/v1 kind: VerticalPodAutoscaler metadata: name: my-app-vpa spec: targetRef: apiVersion: apps/v1 kind: Deployment name: my-app updatePolicy: updateMode: "Off" resourcePolicy: containerPolicies: - containerName: "*" minAllowed: cpu: 50m memory: 256Mi maxAllowed: cpu: 500m memory: 1Gi metrics: - type: Resource resource: name: cpu target: type: Utilization averageUtilization: 50 - type: Resource resource: name: memory target: type: Utilization averageUtilization: 80 In this example, we've added two metrics to the VPA configuration that target CPU and memory utilization, with target average utilization of 50% and 80% respectively. I hope this helps you configure the Metrics Server, HPA, and VPA for your application in Kubernetes!

Id go for k3s then install metrics-server, then you can deploy some hpa’s

# Create EKS Cluster with version 1.23 eksctl create cluster -f eks-cluster.yaml # Output like below shows cluster has been successfully created 2022-12-30 16:26:46 [ℹ] kubectl command should work with "/home/ec2-user/.kube/config", try 'kubectl get nodes' 2022-12-30 16:26:46 [✔] EKS cluster "ca-demo" in "us-west-2" region is ready # Deploy the Metric server kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml # Output of the above command looks something like below - serviceaccount/metrics-server created clusterrole.rbac.authorization.k8s.io/system:aggregated-metrics-reader created clusterrole.rbac.authorization.k8s.io/system:metrics-server created rolebinding.rbac.authorization.k8s.io/metrics-server-auth-reader created clusterrolebinding.rbac.authorization.k8s.io/metrics-server:system:auth-delegator created clusterrolebinding.rbac.authorization.k8s.io/system:metrics-server created service/metrics-server created deployment.apps/metrics-server created apiservice.apiregistration.k8s.io/v1beta1.metrics.k8s.io created

ubuntu@korifi:~$ kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/download/v0.6.2/components.yaml serviceaccount/metrics-server created clusterrole.rbac.authorization.k8s.io/system:aggregated-metrics-reader created clusterrole.rbac.authorization.k8s.io/system:metrics-server created rolebinding.rbac.authorization.k8s.io/metrics-server-auth-reader created clusterrolebinding.rbac.authorization.k8s.io/metrics-server:system:auth-delegator created clusterrolebinding.rbac.authorization.k8s.io/system:metrics-server created service/metrics-server created deployment.apps/metrics-server created apiservice.apiregistration.k8s.io/v1beta1.metrics.k8s.io created ubuntu@korifi:~$ kubectl get po,svc -A NAMESPACE NAME READY STATUS RESTARTS AGE cert-manager pod/cert-manager-74d949c895-w6gzm 1/1 Running 0 13m cert-manager pod/cert-manager-cainjector-d9bc5979d-jhr9m 1/1 Running 0 13m cert-manager pod/cert-manager-webhook-84b7ddd796-xw878 1/1 Running 0 13m kpack pod/kpack-controller-84cbbcdff6-nnhdn 1/1 Running 0 9m40s kpack pod/kpack-webhook-56c6b59c4-9zvlb 1/1 Running 0 9m40s kube-system pod/coredns-565d847f94-kst2l 1/1 Running 0 31m kube-system pod/coredns-565d847f94-rv8pn 1/1 Running 0 31m kube-system pod/etcd-kind-control-plane 1/1 Running 0 32m kube-system pod/kindnet-275pd 1/1 Running 0 31m kube-system pod/kube-apiserver-kind-control-plane 1/1 Running 0 32m kube-system pod/kube-controller-manager-kind-control-plane 1/1 Running 0 32m kube-system pod/kube-proxy-qw9fj 1/1 Running 0 31m kube-system pod/kube-scheduler-kind-control-plane 1/1 Running 0 32m kube-system pod/metrics-server-8ff8f88c6-69t9z 0/1 Running 0 4m21s local-path-storage pod/local-path-provisioner-684f458cdd-f6zqf 1/1 Running 0 31m metallb-system pod/controller-84d6d4db45-bph5x 1/1 Running 0 29m metallb-system pod/speaker-pcl4p 1/1 Running 0 29m projectcontour pod/contour-7b9b9cdfd6-h5jzg 1/1 Running 0 6m43s projectcontour pod/contour-7b9b9cdfd6-nhbq2 1/1 Running 0 6m43s projectcontour pod/contour-certgen-v1.23.2-hxh7k 0/1 Completed 0 6m43s projectcontour pod/envoy-v4xk9 2/2 Running 0 6m43s servicebinding-system pod/servicebinding-controller-manager-85f7498cf-xd7jc 2/2 Running 0 115s NAMESPACE NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE cert-manager service/cert-manager ClusterIP 10.96.153.49 9402/TCP 13m cert-manager service/cert-manager-webhook ClusterIP 10.96.102.82 443/TCP 13m default service/kubernetes ClusterIP 10.96.0.1 443/TCP 32m kpack service/kpack-webhook ClusterIP 10.96.227.201 443/TCP 9m40s kube-system service/kube-dns ClusterIP 10.96.0.10 53/UDP,53/TCP,9153/TCP 32m kube-system service/metrics-server ClusterIP 10.96.204.62 443/TCP 4m21s metallb-system service/webhook-service ClusterIP 10.96.186.139 443/TCP 29m projectcontour service/contour ClusterIP 10.96.138.58 8001/TCP 6m43s projectcontour service/envoy LoadBalancer 10.96.126.44 172.18.255.200 80:30632/TCP,443:30730/TCP 6m43s servicebinding-system service/servicebinding-controller-manager-metrics-service ClusterIP 10.96.147.189 8443/TCP 115s servicebinding-system service/servicebinding-webhook-service ClusterIP 10.96.14.224 443/TCP 115s