bigData

Create Docker network

docker network create ehealth-net

Sensors

For sensors we used Go lang. And encapsulated them in Docker containers. Each Sensor is in a separate directory for better organize. In each directory there is a Dockerfile for the sensors so to create our containers.

Docker containers

To build your Docker container you need to move into the sensor directory.

For example:

cd Sensors/bodyTempSensor

Then you just need to build and run the Dockerfile

Run:

sudo docker build -t body-temp-app .

Perfect now you have your container image build on your Docker

Run this command to see your images:

sudo docker images

You will see something like this:

REPOSITORY               TAG       IMAGE ID       CREATED          SIZE
body-temp-app            latest    2d53db058525   8 minutes ago    842MB

If you see something like this that means you have your image.

To run your image you just need:

Run docker under network

sudo docker run --network=ehealth-net body-temp-app

Run rubbitMQ

docker run -d --name my-rabbitmq \
    --network ehealth-net \
    -p 5672:5672 \
    -p 15672:15672 \
    -e RABBITMQ_DEFAULT_USER=guest \
    -e RABBITMQ_DEFAULT_PASS=guest \
    rabbitmq:management

Run Python

sudo docker build -t ehealth-backend . sudo docker run -d --name ehealth-backend --network ehealth-net ehealth-backend

Argo Workflow and Kubernetes

First we need to instal minikube and then to install kubectl.

Install minikube: [https://minikube.sigs.k8s.io/docs/start/]

After installation of minikube you need to install kubectl

minikube kubectl -- get pods -A

Argo Workflow

Create Argocd namespace

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

Forward the port

kubectl get svc -n argocd

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

From this command you will see something like:

Forwarding from 127.0.0.1:8080 -> 8080

Now if you go to your browser and copy the 127.0.0.1:8080 you should be able to see the Argo Flow UI. From there you just need to add the user name and the password. The default username is: admin

For the password you need to:

kubectl -n argocd get secret argocd-initial-admin-secret -o yaml

And from this you will take the default hashed password for the admin user. So you need to decode this password.

echo RzUzVlp0V0daclJlZXJrRQ== | base64 --decode

sifisKoen/bigData