### TODOS
 ➜ [Create a HA production ready cluster with Kubespray](#create-kubespray-cluster)

 ➜ [Deploy the demo microservice](#deploy-demo-microservice)

 ➜ [Setup and run Gremlin](#setup-and-run-gremlin)

### Requirements
- Kubernetes/kubectl 
- Python3
- pip3
- VirtualBox 
- [Gremlin account](https://app.gremlin.com/signup)

### Create Kubespray Cluster

Note: This repo uses [kubespray](https://github.com/kubernetes-sigs/kubespray) and this demo [microservice](https://github.com/GoogleCloudPlatform/microservices-demo)

1. clone the repo and cd into it 
   
   ```BASH
    https://github.com/kubernetes-sigs/kubespray.git
    cd kubespray 
   ```
2. Install dependencies
   
    ```BASH
    pip3 install -r requirements.txt
    ```  

3. Bring up vagrant (this can take awhile)
   
    ```BASH
    vagrant up
    ```
4. Setup access to the cluster globally
   
    ```BASH
    #modify: group_vars/k8s-cluster/k8s-cluster.yml to
    kubeconfig_localhost: true
    #navigate to artifacts directory
    #/inventory/sample/artifacts
    cp admin.conf ~/.kube/config
    ```
5. Check nodes are up
    ```BASH
    kubectl get nodes

    kubectl get pods --all-namespaces
    ```


### Deploy Demo Microservice

1. Navigate to the base directory `/gremlin`

2. Create a namespace for the microservice 
   
    ```BASH
    kubectl create namespace sock-shop
    ```
3. Deploy it
    ```BASH
    kubectl apply -f sock-shop.yaml
    ```
4. Check pods are running
   
    ```BASH 
    kubectl get pods --namespace sock-shop
    #or
    kubectl get pods --namespace sock-shop --watch
    ```
5. Get front-end deployment port info
   
   ```BASH
   kubectl get deploy front-end -n sock-shop -o jsonpath='{.spec.template.spec.containers[?(@.name == "front-end")].ports[0].containerPort}'

   kubectl port-forward deploy/front-end -n sock-shop 3000:8079
   ```
### Setup and run Gremlin

1. Once logged in get the team id and secret key from the [Teams page]([Setup](https://app.gremlin.com/settings/teams)) and download


2. Install the Gremlin client with helm
   
   ```BASH
    #NOTE:first change the env variables to match your team credentials
    helm repo add gremlin https://helm.gremlin.com
    ```
3. Create a namespace for the client

    ```BASH
    kubectl create namespace gremlin
    ```
4. Run to install (replace credentials)

   ```BASH
   export GREMLIN_TEAM_ID=<team-id>
   export GREMLIN_CLUSTER_ID=<cluster-di> #can be anything
   export GREMLIN_TEAM_SECRET=<team-scale>

   helm install gremlin gremlin/gremlin \
    --namespace gremlin \
    --set gremlin.secret.managed=true \
    --set gremlin.secret.type=secret \
    --set gremlin.secret.teamID=$GREMLIN_TEAM_ID \
    --set gremlin.secret.clusterID=$GREMLIN_CLUSTER_ID \
    --set gremlin.secret.teamSecret=$GREMLIN_TEAM_SECRET
   ```
5. In gremlin you can check and run attacks from the intuitive dashboard
   
   ```BASH
   https://app.gremlin.com/clients/hosts
   ```
    ### or use the [API](https://app.gremlin.com/api#/attacks/createhttps://app.gremlin.com/api#/attacks/create)

6. Clean up
   
    ```BASH
    helm uninstall -n gremlin gremlin
    vagrant halt
    vagrant destroy -f
    kubectl config use-context docker-desktop
    ```

### Resources

[Official Gremlin docs](https://www.gremlin.com/community/tutorials/how-to-install-and-use-gremlin-with-kubernetes/)