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The Secret To Succesully Simulate An Attack With Gremlin To Test Kubernetes

by Sudip SenguptaNovember 3rd, 2020

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The Secret To Succesully Simulate An Attack With Gremlin To Test Kubernetes is published by Sudip Sengupta. Gremlin is a leading software company focusing on chaos-test in the market. It also has a tool similar to Chaos Monkey which is more customized to test the system with random loads or scheduled shutdowns. This tutorial helps to produce the requirements and create a scenario to'simulate an attack with Gremlin. We will use a running EKS cluster and two applications deployed to EKS. We are creating the cluster named gremlin-eksctl with three EC2 nodes.

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featured image - The Secret To Succesully Simulate An Attack With Gremlin To Test Kubernetes

Gremlin is a leading software company focusing on chaos-test in the market. It also has a tool similar to Chaos Monkey which belongs to Netflix, but is more customized to test the system with random loads or scheduled shutdowns. In the article below we will be testing a simple Kubernetes cluster running on EKS with Chaos Test.

Why is Chaos Test Important?

Chaos Engineering is used to improve system resilience. Gremlin’s “Failure as a Service” helps to find weaknesses in the system before problems occur.

Overview

To successfully experience Chaos Engineering with Gremlin, firstly we have two requirements: a running EKS cluster and two applications deployed to EKS. This tutorial helps to produce the requirements and create a scenario to 'simulate an attack with Gremlin'.

Step 1 - Prepare Cloud9 IDE
Step 2 - Create an EKS cluster using eksctl
Step 3 - Deploy Kubernetes Dashboard
Step 4 - Install Gremlin using Helm
Step 5 - Deploy a Microservice Demo Application
Step 6 - Run a Shutdown Container Attack using Gremlin

Prerequsities

1. An AWS account
2. A Gremlin account which can be registered from

Step 1 - Prepare Cloud9 IDE

Firstly, let's start to create the Cloud9 environment. Login to your AWS account and navigate Cloud9 to service page. Click on Get Started and type the name with anything, in this example we have chosen chaous gremlin. Keep all default settings as they are stated since it is needed only to reach EKS resources.

Wait for a while for the new console to build. Then close all terminals to open a new one.

To start creating the cluster, firstly check whether AWS CLI is installed or not with the command below:

Administrator:~/environment $ aws --version
aws-cli/1.17.5 Python/2.7.16 Linux/4.14.158-101.185.amzn1.x86_64 botocore/1.14.5
Administrator:~/environment $

Step 2 - Creating an EKS cluster using eksctl

1. We will use

eksctl

to create our EKS clusters.

curl --silent --location "//github.com/weaveworks/eksctl/releases/download/latest_release/eksctl_$(uname -s)_amd64.tar.gz" | tar xz -C /tmp


sudo mv -v /tmp/eksctl /usr/local/bin

2. Making

eksctl

executable

Administrator:~/environment $ sudo chmod +x /usr/local/bin/eksctl
Administrator:~/environment $

3. Confirming whether the

eksctl

command works:

Administrator:~ $ eksctl version
[ℹ]  version.Info{BuiltAt:"", GitCommit:"", GitTag:"0.13.0"}
Administrator:~ $

4. Below we are creating the cluster named gremlin-eksctl with three EC2 nodes. Just a word of warning - EKS can cost a lot so please do not forget to delete your resources after you have done with your failure test.

eksctl create cluster --name=gremlin-eksctll --nodes=3 --managed --alb-ingress-access --region=${AWS_REGION}

It might take around 15-30 minutes to get ready which you can cluster on the EKS service page.

Quit Tip - Fee of EKS is 0,20$/h and fee of EC2 with a m5.large instance type that EKS runs on is 0.096$/h. Estimation of total cost per day will be around 11-12$.

5. Checking the cluster whether it is working and getting its status. As expected, there is only one cluster created.

Administrator:~/environment $ eksctl get clusters
NAME            REGION
gremlin-eksctl  us-east-1
Administrator:~/environment $

6. Updating the

kubeconfig

file by giving the cluster name and region via AWS CLI tool.

Administrator:~/environment $ sudo aws eks --region us-east-1  update-kubeconfig --name gremlin-eksctl
Updated context arn:aws:eks:us-east-1:3:cluster/gremlin-eksctl in /root/.kube/config
Administrator:~/environment $

7. On checking we see 3 nodes in the cluster. Two of them are worker-nodes while the third is cluster management master-node.

Administrator:~/environment $ kubectl get nodes
NAME                            STATUS   ROLES    AGE   VERSION
ip-192-168-14-59.ec2.internal   Ready       59m   v1.14.7-eks-1861c5
ip-192-168-33-12.ec2.internal   Ready       58m   v1.14.7-eks-1861c5
ip-192-168-49-55.ec2.internal   Ready       58m   v1.14.7-eks-1861c5
Administrator:~/environment $

Step 3 - Deploying Kubernetes Dashboard

Next we would deploy the Kubernetes dashboard to Kubernetes cluster by using Heapster and InfluxDB. These two tools will help our sample application to be shown in the dashboard. We will start with deploying our Kubernetes dashboard as the first step.

Heapster

is a performance monitoring and metrics collection system compatible with Kubernetes (versions 1.0.6 and above). It allows for the collection of not only performance metrics about your workloads, pods, and containers, but also events and other signals generated by your cluster. The great thing about Heapster is that it is fully open source as part of the Kubernetes project, and supports a multitude of backends for persisting the data, including but , Influxdb, Elasticsearch, and Graphite.

InfluxDB

InfluxDB is a time series database designed to handle high volume of writing and query loads. 1. Deploying the Kubernetes Dashboard to your EKS cluster:

Administrator:~/environment $ kubectl apply -f //raw.githubusercontent.com/kubernetes/dashboard/v1.10.1/src/deploy/recommended/kubernetes-dashboard.yaml
secret/kubernetes-dashboard-certs created
serviceaccount/kubernetes-dashboard created
role.rbac.authorization.k8s.io/kubernetes-dashboard-minimal created
rolebinding.rbac.authorization.k8s.io/kubernetes-dashboard-minimal created
deployment.apps/kubernetes-dashboard created
service/kubernetes-dashboard created
Administrator:~/environment $

2. Firstly, access to cluster is given since it is deployed to our private cluster while we need to access it via a proxy. This can be done through Kube-Proxy as the preferred proxy tool. In your workspace, run the following command:

Administrator:~/environment $ kubectl proxy --port=8080 --address='0.0.0.0' --disable-filter=true &
[1] 336
Administrator:~/environment $ W0125 10:28:19.746961     336 proxy.go:140] Request filter disabled, your proxy is vulnerable to XSRF attacks, please be cautious
Starting to serve on [::]:8080

Administrator:~/environment $

3. Deploying Heapster:

Administrator:~/environment $  kubectl apply -f //raw.githubusercontent.com/kubernetes/heapster/master/deploy/kube-config/influxdb/heapster.yaml
serviceaccount/heapster created
deployment.extensions/heapster created
service/heapster created
Administrator:~/environment $

4. Deploying InfluxDB:

Administrator:~/environment $  kubectl apply -f //raw.githubusercontent.com/kubernetes/heapster/master/deploy/kube-config/influxdb/influxdb.yaml
deployment.extensions/monitoring-influxdb created
service/monitoring-influxdb created
Administrator:~/environment $

5. Creating Heapster cluster role binding for the Dashboard.

Administrator:~/environment $ kubectl apply -f //raw.githubusercontent.com/kubernetes/heapster/master/deploy/kube-config/rbac/heapster-rbac.yaml
clusterrolebinding.rbac.authorization.k8s.io/heapster created
Administrator:~/environment $

6. The next step is to create an

eks-admin

service account. It will let you connect to the Kubernetes Dashboard with

admin

permissions.

To authenticate and use the Kubernetes Dashboard:

Administrator:~/environment $ kubectl apply -f //raw.githubusercontent.com/tammybutow/eks-aws/master/eks-admin-service-account.yaml
serviceaccount/eks-admin created
clusterrolebinding.rbac.authorization.k8s.io/eks-admin created
Administrator:~/environment $

7. To access the Kubernetes Dashboard:

a- In your Cloud9 environment, click Tools > Preview > Preview Running Application to open the Dashboard URL.

b- Append the following to the end of the URL:

/api/v1/namespaces/kube-system/services/https:kubernetes-dashboard:/proxy/

8. Open a new Terminal tab on Cloud9 and enter the following:

aws eks get-token --cluster-name gremlin-eksctl | jq -r '.status.token'

9. Select Token and then copy the output of the command above and paste it to the text field as shown below:

Step 4 - Installing Gremlin using Helm

1. Download your Gremlin certificates:Start by signing-in to your Gremlin account. If you don't have one, create an account .

Navigate to and click on your Team. Click the Download button to download and save certificates to your local drive. Please note that the downloaded certificate.zip contains both a public-key certificate and a matching private key.

Unzip the certificate.zip and save it to your Gremlin folder on your desktop. Rename your certificate as gremlin.cert and key files as gremlin.key.

2. Creating Gremlin Namespace:

Administrator:~/environment $ kubectl create namespace gremlin
namespace/gremlin created
Administrator:~/environment $

Create a Kubernetes Secret for your certificate and private key, copy gremlin.cert and gremlin.key to Cloud9. A quick tip is to create these by the Vim Editor instead of copying from your local computer.

Administrator:~/environment $ kubectl create secret generic gremlin-team-cert \
> \--namespace=gremlin  \
> \--from-file=/home/ec2-user/environment/gremlin.cert \
> \--from-file=/home/ec2-user/environment/gremlin.key
secret/gremlin-team-cert created
Administrator:~/environment $

Check the files on Dashboard whether they are deployed.

3. Installation with Helm

The simplest way of installing the Gremlin client on your Kubernetes cluster is to use Helm. Once Helm is installed and configured, the next steps will be to add the Gremlin repo and to install the client.

A. Installing Helm source code and making it executable:

Administrator:~/environment $ curl //raw.githubusercontent.com/kubernetes/helm/master/scripts/get > get_helm.sh
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100  7164  100  7164    0     0  45630      0 --:--:-- --:--:-- --:--:-- 45341
Administrator:~/environment $ 
Administrator:~/environment $ chmod +x get_helm.sh
Administrator:~/environment $ 
Administrator:~/environment $ ./get_helm.sh
Downloading //get.helm.sh/helm-v2.16.1-linux-amd64.tar.gz
Preparing to install helm and tiller into /usr/local/bin
helm installed into /usr/local/bin/helm
tiller installed into /usr/local/bin/tiller
Run 'helm init' to configure helm.
Administrator:~/environment $

B. Configuring Helm to access with RBAC

Helm relies on a service called Tiller which requires special permission on the Kubernetes cluster, for which we will need to build a Service Account for using Tiller. Next step is to then apply this RBAC to the cluster.

C. Creating a new service account:

Administrator:~/environment $ cat < ~/environment/rbac.yaml
> ---
> apiVersion: v1
> kind: ServiceAccount
> metadata:
>   name: tiller
>   namespace: kube-system
> ---
> apiVersion: rbac.authorization.k8s.io/v1beta1
> kind: ClusterRoleBinding
> metadata:
>   name: tiller
> roleRef:
>   apiGroup: rbac.authorization.k8s.io
>   kind: ClusterRole
>   name: cluster-admin
> subjects:
>   - kind: ServiceAccount
>     name: tiller
>     namespace: kube-system
> EoF
Administrator:~/environment $

D. Applying configurations:

Administrator:~/environment $ kubectl apply -f ~/environment/rbac.yaml
serviceaccount/tiller created
clusterrolebinding.rbac.authorization.k8s.io/tiller created
Administrator:~/environment $

E. Installing Tiller for Helm:

Tiller

A companion server component,

tiller

, that runs on your Kubernetes cluster, listens for commands from

helm

, and handles the configuration and deployment of software releases on the cluster.

Administrator:~/environment $ helm init --service-account tiller
Creating /home/ec2-user/.helm 
Creating /home/ec2-user/.helm/repository 
Creating /home/ec2-user/.helm/repository/cache 
Creating /home/ec2-user/.helm/repository/local 
Creating /home/ec2-user/.helm/plugins 
Creating /home/ec2-user/.helm/starters 
Creating /home/ec2-user/.helm/cache/archive 
Creating /home/ec2-user/.helm/repository/repositories.yaml 
Adding stable repo with URL: //kubernetes-charts.storage.googleapis.com 
Adding local repo with URL: //127.0.0.1:8879/charts 
$HELM_HOME has been configured at /home/ec2-user/.helm.

Tiller (the Helm server-side component) has been installed into your Kubernetes Cluster.

Please note: by default, Tiller is deployed with an insecure 'allow unauthenticated users' policy.
To prevent this, run `helm init` with the --tiller-tls-verify flag.
For more information on securing your installation see: //docs.helm.sh/using_helm/#securing-your-helm-installation
Administrator:~/environment $

This will install tiller into the cluster and will give access to managed resources in your cluster. Please note the security policy alert as shown above, which you can feel free to ignore or follow as per your policy settings.

F. Activating bash-completion for Helm:

Administrator:~/environment $ helm completion bash >> ~/.bash_completion
Administrator:~/environment $ . /etc/profile.d/bash_completion.sh
Administrator:~/environment $ . ~/.bash_completion
Administrator:~/environment $

G. To run the Helm install, you will need your Gremlin Team ID. It can be found in the Gremlin app on the page, where you downloaded your certificates earlier. Click on your Team in the list. The ID you’re looking for can be found under Configuration as Team ID.

H. Export your Team ID as an

environment

variable:

Administrator:~/environment $ export GREMLIN_TEAM_ID=13ba2df0-5b0b-572c-a479-8136af79da66
Administrator:~/environment $

I. Next, export your cluster ID, by giving a name for your Kubernetes cluster.

Administrator:~/environment $ export GREMLIN_CLUSTER_ID=boraozkanchaos
Administrator:~/environment $

J. Now add the Gremlin Helm repo, and install Gremlin:

Administrator:~/environment $ helm repo add gremlin //helm.gremlin.com
"gremlin" has been added to your repositories
Administrator:~/environment $

Administrator:~/environment $ helm install gremlin/gremlin \
> \--namespace gremlin \
> \--name gremlin \
> \--set gremlin.teamID=$GREMLIN_TEAM_ID \
> \--set gremlin.clusterID=$GREMLIN_CLUSTER_ID
NAME:   gremlin
LAST DEPLOYED: Sat Jan 25 12:37:45 2020
NAMESPACE: gremlin
STATUS: DEPLOYED

RESOURCES:
==> v1/ClusterRole
NAME             AGE
gremlin-watcher  0s

==> v1/ClusterRoleBinding
NAME  AGE
chao  0s

==> v1/DaemonSet
NAME     AGE
gremlin  0s

==> v1/Deployment
NAME  AGE
chao  0s

==> v1/Pod(related)
NAME                   AGE
chao-698b9fbfb4-5thjp  0s
gremlin-425wv          0s
gremlin-krdlt          0s
gremlin-l252z          0s

==> v1/ServiceAccount
NAME  AGE
chao  0s


Administrator:~/environment $

Step 5 - Deploying a Microservice Demo Application

The demo environment we are going to deploy on to our EKS cluster is the 1. Clone repo of app source code:

Administrator:~/environment $ git clone //github.com/GoogleCloudPlatform/microservices-demo.git
Cloning into 'microservices-demo'...
remote: Enumerating objects: 30, done.
remote: Counting objects: 100% (30/30), done.
remote: Compressing objects: 100% (21/21), done.
remote: Total 2987 (delta 16), reused 16 (delta 7), pack-reused 2957
Receiving objects: 100% (2987/2987), 5.08 MiB | 38.24 MiB/s, done.
Resolving deltas: 100% (2039/2039), done.
Administrator:~/environment $

2. Change directory to the one just created:

Administrator:~/environment $ cd microservices-demo/
Administrator:~/environment/microservices-demo (master) $

3. Deploying the application:

Administrator:~/environment/microservices-demo (master) $ kubectl apply -f ./release/kubernetes-manifests.yaml
deployment.apps/emailservice created
service/emailservice created
deployment.apps/checkoutservice created
service/checkoutservice created
deployment.apps/recommendationservice created
service/recommendationservice created
deployment.apps/frontend created
service/frontend created
service/frontend-external created
deployment.apps/paymentservice created
service/paymentservice created
deployment.apps/productcatalogservice created
service/productcatalogservice created
deployment.apps/cartservice created
service/cartservice created
deployment.apps/loadgenerator created
deployment.apps/currencyservice created
service/currencyservice created
deployment.apps/shippingservice created
service/shippingservice created
deployment.apps/redis-cart created
service/redis-cart created
deployment.apps/adservice created
service/adservice created
Administrator:~/environment/microservices-demo (master) $

4. Wait until pods are in a ready state.

Administrator:~/environment/microservices-demo (master) $ kubectl get pods
NAME                                     READY   STATUS    RESTARTS   AGE
adservice-84449b8756-qj4sp               1/1     Running   0          4m57s
cartservice-6cbc9b899c-ww5rf             1/1     Running   0          4m58s
checkoutservice-56b48b77c8-fszpx         1/1     Running   0          4m58s
currencyservice-b9fcb4c98-hx9kq          1/1     Running   0          4m58s
emailservice-797cdcc76d-d257v            1/1     Running   0          4m58s
frontend-785c44fd98-zvgj4                1/1     Running   0          4m58s
loadgenerator-665c4ddb74-xwm8m           1/1     Running   3          4m58s
paymentservice-84d7bf956-fdgxr           1/1     Running   0          4m58s
productcatalogservice-5664f59f54-b5mk5   1/1     Running   0          4m58s
recommendationservice-7f9855d7c6-b2zv6   1/1     Running   0          4m58s
redis-cart-6448dcbdcc-97d55              1/1     Running   0          4m58s
shippingservice-6b6f49747d-svb5f         1/1     Running   0          4m58s
Administrator:~/environment/microservices-demo (master) $

5. Getting the frontend IP address:

Administrator:~/environment/microservices-demo (master) $ kubectl get svc frontend-external -o wide
NAME                TYPE           CLUSTER-IP       EXTERNAL-IP                                                              PORT(S)        AGE     SELECTOR
frontend-external   LoadBalancer   10.100.226.157   a0c9bed9a3f7111eab7c912c03cd100e-265884000.us-east-1.elb.amazonaws.com   80:30461/TCP   6m31s   app=frontend
Administrator:~/environment/microservices-demo (master) $

6. Visit the URL on your browser:

Step 6 - Running a Shutdown Container Attack using Gremlin

We are going to create our first Chaos Engineering experiment where we would validate the EKS reliability. Our hypothesis is, “After shutting down my cart service container, we will not suffer from downtime and EKS will give us a new one.”

Going back to the Gremlin UI, select Attacks from the menu on the left and select New Attack. We’re going to target a Kubernetes resource, so click on Kubernetes on the upper right.

Choose cartservice:

Choose State and Shutdown:

Attacking this pod with our Gremlin UI:

We will be shutting down the cartservice containers. As a test, we attacked twice and the cartservice pods restarted itself. Which signifies that it is working as expected. Note that it re-generates itself even when you attack to shut down your pods.

When we attacked our containers, the cluster resisted to failure and restarted itself, which symbolizes that our system is now resistant to failure. We have seen what happens when a failure occurs, in this example the failure is shutting down the pods. As a result, we understand that our cluster already has auto-scaling feature.

As a reminder; do not forget to delete your cluster and Cloud9 ide.

eksctl delete cluster --name=gremlin-eksctl

Conclusion

Congrats! You’ve installed an AWS EKS cluster, deployed the Kubernetes Dashboard, deployed a microservice demo application, installed the Gremlin agent as a daemon-set, and ran your first Chaos Engineering attack to validate Kubernetes reliability!

This article was originally published on .

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