A microservice architecture created with JHipster. Uses Spring Cloud, Spring Boot, Angular, and MongoDB for a simple blog/store applications.
To run this app, you'll need to install Java 8, Node.js 6.11, Yarn, and Docker.
NOTE: If you're not on Mac or Windows, you may need to install Docker Compose as well.
-
Start the registry by running
./mvnw
in theregistry
directory. -
Install dependencies in the
blog
directory, build the UI, and run the Spring Boot app.yarn ./mvnw
-
Start MongoDB using Docker Compose in the
store
directory.docker-compose -f src/main/docker/mongodb.yml up
-
Install dependencies in the
store
directory, build the UI, and run the Spring Boot app.yarn ./mvnw
You should be able to see the blog
app at http://localhost:8080 and edit products (from the store
app)
You can use Docker Compose to start everything if you don't want to start applications manually with Maven.
-
Make sure Docker is running.
-
Build Docker images for the
blog
andstore
applications by running the following command in both directories../mvnw package -Pprod docker:build
-
Open a terminal, navigate to the
docker
directory of this project, and run the following command. If you have a lot of RAM on your machine, you might want to adjust Docker's default setting (2 GB).docker-compose up -d
TIP: Remove
-d
from the end of the command above if you want to see logs from all containers in the current window. -
Use Kitematic to view the ports and logs for the services deployed.
To create activity in JHipster Console's charts, you run the Gatling tests in the blog
and store
projects.
./mvnw gatling:execute
To remove all Docker containers, run the following commands or do it manually using Kitematic.
docker stop $(docker ps -a -q)
docker rm $(docker ps -a -q)
To find what's running on a port on macOS, use sudo lsof -i :9092 # checks port 9092
.
-
Install kubectl, VirtualBox, and Minikube.
-
Start Minikube using
minikube start
. -
To be able to work with the docker daemon, make sure Docker is running, then run the following command in your terminal:
eval $(minikube docker-env)
-
Create Docker images of the
blog
andstore
applications:./mvnw package -Pprod docker:build
-
Run the following commands in the
kubernetes
directory to deploy to Minikube.kubectl apply -f registry kubectl apply -f blog kubectl apply -f store
The deployment process can take several minutes to complete. Run
minikube dashboard
to see the deployed containers. You can also runkubectl get po -o wide --watch
to see the status of each pod. -
Run
minikube service blog
to view the blog application. You should be able to login and add blogs, entries, and products.
To remove all deployed containers, run the following command:
kubectl delete deployment --all
To stop Minikube, run minikube stop
.
NOTE: If you run minikube delete
and have trouble running minikube start
afterward, run rm -rf ~/.minikube
.
See this issue for more information.
-
Create a Google Cloud project at console.cloud.google.com.
-
Navigate to https://console.cloud.google.com/kubernetes/list to initialize the Container Engine for your project.
-
Install Google Cloud SDK and set project using:
gcloud config set project <project-name>
-
Create a cluster:
gcloud container clusters create <cluster-name> --machine-type=n1-standard-2 --scopes cloud-platform --zone us-west1-a
To see a list of possible zones, run
gcloud compute zones list
. -
Push the
blog
andstore
docker images to Docker Hub. You will need to create an account and rundocker login
to push your images. The images can be run from any directory.docker image tag blog mraible/blog docker push mraible/blog docker image tag store mraible/store docker push mraible/store
-
Run
kubectl
commands to deploy.kubectl apply -f registry kubectl apply -f blog kubectl apply -f store
-
Use port-forwarding to see the registry app locally.
kubectl port-forward jhipster-registry-0 8761:8761
-
Run
kubectl svc blog
to view the blog application on Google Cloud. -
Scale microservice apps as needed with
kubectl
:kubectl scale --replicas=3 deployment/store
To see a screencast of this process, watch this YouTube video.
If you know how to deploy this architecture to AWS, I'd love to hear about it! I tried in anger, but ultimately failed.