In this tutorial you will deploy The Sock Shop to a cluster of three Ubuntu hosts running Docker and Kubernetes and then use Weave Cloud to visually troubleshoot and validate that the app is running as intended.
This tutorial takes approximately 25 minutes to complete.
- Part 2 describes how to configure Weave Cloud for continuous delivery
- Part 3 is a tutorial on how to monitor applications with Weave Cloud.
- Part 4 shows you how to secure your app using Kubernetes Network Policy and then enforce it with Weave Net.
All four of these tutorials use the Weaveworks microservices app, The Sock Shop.
A Video Overview
What You Will Use
Before You Begin
Before you begin, ensure the following installed:
- Docker and Docker Compose
- This tutorial also works with Docker for Mac
If You’re on a Mac
If you haven’t installed Docker for Mac before, follow the installation instructions on Docker website.
Once it’s running you will see in your menu bar.
Sign Up for Weave Cloud
To begin, sign up for Weave Cloud and deploy the Scope probes on your laptop.
After verifying that the app works as it should on your laptop, you’ll then install the Weave Cloud probes to production, set up a Kubernetes cluster and deploy the app it, and then compare production with the app on your laptop.
To sign up for Weave Cloud:
- Go to Weave Cloud
- Sign up using either a Github, or Google account or use an email address.
- Create a new instance, choose Docker as your platform and select your environment. This should print out a set of commands you should copy and execute in a terminal.
Launch the Scope Probes on Your Laptop
Launch the Scope probes using the commands you obtained when you created your instance in Weave Cloud.
They are going to look somewhat like this.
<cloud-token> is the token that appears on the settings page of your instance.
sudo curl -L git.io/scope -o /usr/local/bin/scope sudo chmod a+x /usr/local/bin/scope scope launch --service-token=<cloud-token>
Deploying the Socks Shop
To deploy The Socks Shop to your local machine:
1. Get the code:
git clone https://github.com/microservices-demo/microservices-demo.git
2. Change to the docker-compose directory:
3. Run the Sock Shop and display it in your browser:
docker-compose up -d
Note: If the shop doesn’t come up right away or it gives you an error like
ERROR: for edge-router Cannot start service edge-router: because of a port in use, try going to
http://127.0.0.1 in your browser.
Run a Load Test Against the Sock Shop
To fully appreciate the topology of this app in Weave Scope, you will need to first run a load on the app. This load test simulates users buying socks at the shop.
Run a load test with the following:
docker run -ti --rm --name=LOAD_TEST --net=dockercompose_default \ weaveworksdemos/load-test -h edge-router -r 100 -c 2
With the load test running, the topology in Weave Cloud begins to form where you can see the microservices communicating as socks are being selected and purchased.
With the load test running, search for the user-db container, and click on it to open the metrics panel. From the metrics panel that appears, click on the terminal icon to view the messages from the simulated users logging onto the site.
Deploying to “Production” on Kubernetes
This example uses Digital Ocean, but you can just as easily create three instances in AWS, Google Cloud Platform or Microsoft Azure or any other cloud provider.
1. Create Three Droplets in Digital Ocean
Sign up or log into Digital Ocean and create three Ubuntu instances with the following specifications:
- Ubunutu 16.04
- 4GB or more of RAM per instance
Note: do not select the Private networking option for your droplets. Selecting this option will prevent the setting up of the Kubernetes cluster to fail. See section Initialize the Master for more details.
2. Add a New Weave Cloud Instance
Sign up or log into Weave Cloud.
Create a new instance or rename the default instance in Weave Cloud](https://cloud.weave.works). Weave Cloud instances are the primary workspaces for your application and provides a view onto your cluster and the application that is running on it.
3. Set up a Kubernetes Cluster with kubeadm
Kubeadm is by far the simplest way to set up a Kubernetes cluster. With only a few commands, you can deploy a complete Kubernetes cluster with a resilient and secure container network onto the Cloud Provider of your choice in only a few minutes.
kubeadm is a command line tool that and is a part of Kubernetes 1.4 and greater.
kubeadm reference for information on all
kubeadm command-line options and for advice on automating
- Install a secure Kubernetes cluster
- Install Weave Net as a pod network so that application components (pods) can communicate with one another
- Install the Sock Shop, a demo microservices application
- View the result in Weave Cloud
4. Download and install kubelet, kubeadm and Docker
To begin SSH into the machine and become
root (for example, run
sudo su -). Then install the required binaries onto all three instances:
curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add - cat <<EOF > /etc/apt/sources.list.d/kubernetes.list deb http://apt.kubernetes.io/ kubernetes-xenial main EOF apt-get update
Next, install Docker. You can also use the official Docker packages instead of
docker.io that is referenced here.
apt-get install -y docker.io
And finally, install the Kubernetes packages:
apt-get install -y kubelet kubeadm kubectl kubernetes-cni
5. Initialize the Master
Note: Before making one of your machines a master,
kubeadmmust have been installed onto each of the nodes.
The master is the machine where the “control plane” components run, including
etcd (the cluster database) and the API server (which the
kubectl CLI communicates with).
All of these components run in pods started by
Keep in mind that you can’t run
kubeadm init twice without tearing down the cluster, see Tear Down for more information.
To initialize the master, pick one of the machines on which you previously installed
kubeadm and run:
Initialization of the master may take a few minutes.
This autodetects the network interface and then advertises the master on it with the default gateway.
Note: If you want to use a different network interface, specify it with the
--api-advertise-addresses=<ip-address>flag when you run
Important! Special note on selecting different network interface:
When using a different network interface in Digital Ocean through the Private Network option for the droplets causes
the Kubernetes cluster set up to fail. For more information, see issue #203 of kubernetes/kubeadm. This can occur with
kubeadm and the default gateway that your droplets may receive at the moment of creation.
Until this issue is resolved, the default droplet networking settings must be enabled.
This means that all the nodes in your cluster will be open to the world and that they communicate between each other via Internet. Ensure that you understand the implications of such a set up. You can reinforce the security of your cluster by using
Refer to the kubeadm reference doc to read up on the flags
kubeadm init provides.
If the initialization is successful, the output should look similar to the following:
....some preflight checks and initialization Your Kubernetes master has initialized successfully! To start using your cluster, you need to run (as a regular user): sudo cp /etc/kubernetes/admin.conf $HOME/ sudo chown $(id -u):$(id -g) $HOME/admin.conf export KUBECONFIG=$HOME/admin.conf You should now deploy a pod network to the cluster. Run "kubectl apply -f [podnetwork].yaml" with one of the options listed at: http://kubernetes.io/docs/admin/addons/ You can now join any number of machines by running the following on each node as root: kubeadm join --token <token-id> <master-ip>
Make a record of the
kubeadm join command that
kubeadm init outputs. You will need this once it’s time to join the nodes. This token is used for mutual authentication between the master and any joining nodes.
This token is a secret, and so it’s important to keep it safe — anyone with this key can add authenticated nodes to your cluster.
(Optional) Scheduling Pods on the Master
By default, the cluster does not schedule pods on the master for security reasons. If you want to be able to schedule pods on the master, for example if you want a single-machine Kubernetes cluster for development, then run:
kubectl taint nodes --all dedicated-
The output will be:
node "test-01" tainted taint key="dedicated" and effect="" not found. taint key="dedicated" and effect="" not found.
This removes the “dedicated” taint from any nodes that have it, including the master node, meaning that the scheduler will then be able to schedule pods everywhere.
6. Set up the environment for Kubernetes
On the master run the following as a regular user:
sudo cp /etc/kubernetes/admin.conf $HOME/ sudo chown $(id -u):$(id -g) $HOME/admin.conf export KUBECONFIG=$HOME/admin.conf
7. Install Weave Net as the Pod Networking Layer
In this section, you will install a Weave Net pod network so that your pods can communicate with each other.
You must add Weave Net before deploying any applications to your cluster and before
kube-dns starts up.
Note: Install only one pod network per cluster. There are two versions of the Weave Net daemonset installer. One installs Weave Net to version 1.5 of the Kubernetes binaries and the other installs to 1.6.
If you’re running Kubernetes 1.5 (and less) install Weave Net by logging onto the master and running:
kubectl apply -f https://git.io/weave-kube
If you’re running Kubernetes 1.6 (and above), install Weave Net by logging onto the master and running:
kubectl apply -f "https://cloud.weave.works/k8s/net?k8s-version=$(kubectl version | base64 | tr -d '\n')"
The output will be:
serviceaccount "weave-net" created clusterrole "weave-net" created clusterrolebinding "weave-net" created daemonset "weave-net" created
Once a pod network is installed, confirm that it is working by ensuring that the
kube-dns pod is
kubectl get pods --all-namespaces
kube-dns pod is up and running, you can join all of the nodes to form the cluster.
8. Join Your Nodes to the Master
The nodes are where the workloads (containers and pods, etc) run.
Join the nodes to your cluster by running:
kubeadm join --token <token> <master-ip>
The above command, including the token and the master-ip, is output by
kubeadm init that you ran earlier.
When the node has successfully joined, the output should look as follows:
preflight] Running pre-flight checks [tokens] Validating provided token [discovery] Created cluster info discovery client, requesting info from "http://126.96.36.199:9898/cluster-info/v1/?token-id=ad23e7" [discovery] Cluster info object received, verifying signature using given token [discovery] Cluster info signature and contents are valid, will use API endpoints [https://188.8.131.52:6443] [bootstrap] Trying to connect to endpoint https://184.108.40.206:6443 [bootstrap] Detected server version: v1.6.0 [bootstrap] Successfully established connection with endpoint "https://220.127.116.11:6443" [csr] Created API client to obtain unique certificate for this node, generating keys and certificate signing request [csr] Received signed certificate from the API server: Issuer: CN=kubernetes | Subject: CN=system:node:node-02 | CA: false Not before: 2017-02-20 20:33:00 +0000 UTC Not After: 2018-02-20 20:33:00 +0000 UTC [csr] Generating kubelet configuration [kubeconfig] Wrote KubeConfig file to disk: "/etc/kubernetes/kubelet.conf" Node join complete: * Certificate signing request sent to master and response received. * Kubelet informed of new secure connection details. Run 'kubectl get nodes' on the master to see this machine join.
kubectl get nodes on the master to display a cluster with the number of machines as you created.
(Optional) Control Your Cluster From Machines Other Than The Master
In order to get
kubectl on your laptop to talk to your cluster (as an example), copy the
kubeconfig file from your master to your laptop:
scp root@<master ip>:/etc/kubernetes/admin.conf . kubectl --kubeconfig ./admin.conf get nodes
8. Install and Launch the Weave Cloud Agents
yaml file listed below installs all of the Weave Cloud probes to a DaemonSet and launches them to your cluster.
From the master:
kubectl apply -f \ "https://cloud.weave.works/k8s.yaml?t=<cloud-token>&k8s-version=$(kubectl version | base64 | tr -d '\n')"
<cloud-token> is found in the settings dialog on Weave Cloud. The above command may also be cut and pasted from the setup screens in Weave Cloud.
If you mistyped or copied and pasted the command incorrectly, you can remove the DaemonSet with:
kubectl delete ns weave
Return to Weave Cloud, and click Explore and then Pods to display the Kubernetes cluster in your instance. Ensure that the All Namespaces filter is enabled from the left-hand corner.
For the next few steps, keep the instance open on Explore to watch the Sock Shop containers spin up in the cluster.
9. Install the Sock Shop onto Kubernetes
To put your cluster through its paces, install the sample microservices application, Socks Shop. Learn more about the sample microservices app by referring to the microservices-demo README.
To install the Sock Shop, run the following:
kubectl create namespace sock-shop git clone https://github.com/microservices-demo/microservices-demo cd microservices-demo kubectl apply -n sock-shop -f deploy/kubernetes/manifests
Click on Explore and then Pod and enable the sock-shop namespace filter from the bottom left-hand corner.
It takes several minutes to download and start all of the containers. Watch the output of
kubectl get pods -n sock-shop to see that all of the containers are successfully running.
Or view the containers as they get created in Weave Cloud.
10. View the Sock Shop in Your Browser
Find the port that the cluster allocated for the front-end service by running:
kubectl describe svc front-end -n sock-shop
The output should look like:
Name: front-end Namespace: sock-shop Labels: name=front-end Selector: name=front-end Type: NodePort IP: 100.66.88.176 Port: <unset> 80/TCP NodePort: <unset> 31869/TCP Endpoints: <none> Session Affinity: None
Launch the Sock Shop in your browser by going to the IP address of any of your node machines in your browser, and by specifying the NodePort. So for example,
http://<master_ip>:<pNodePort>. You can find the IP address of the machines in the DigitalOcean dashboard.
In the example above, the NodePort was
If there is a firewall, make sure it exposes this port to the internet before you try to access it.
11. Create a Load on the Sock Shop
To fully appreciate the topology of the Sock Shop in Weave Scope, you’ll have to create a load on the app.
View the Sock Shop in your app with
<host-ip:[port number]>is the IP of the master and the port number you see when you run
kubectl describe svc front-end -n sock-shop.
With the Sock Shop displayed in the browser, log in to the application with
password. Select a few pairs of socks, put them inot the shopping cart, proceed to checkout and then return to Weave Cloud.
Click on the Containers view where you will see the app begin to take shape with lines appearing between each service.
Unless you are continuing onto another guide, or you are using the cluster for your own app, you may want to tear down the Sock Shop and the Kubernetes cluster you created.
To uninstall the socks shop, run
kubectl delete namespace sock-shopon the master.
To uninstall Kubernetes on the machines, you can delete the machines you created for this tutorial, and then start over
To uninstall a daemon set run
kubectl delete ds <agent-name>.
Recreating the Cluster: Starting Over
Note: If you made an error during the install instructions, it is recommended that you delete the entire cluster and begin again.
1. Reset the cluster to the local state:
systemctl start kubelet on each of the nodes.
3. Re-initialize the master by
kubeadm init on the master.
4. Then join the nodes to the master with:
kubeadm join --token <token> <master-ip>
Tear Down on Your laptop
To remove the Sock Shop from your laptop, run:
docker-compose -f deploy/docker-compose/docker-compose.yml down
In this tutorial you learned how to verify an app deployed to your laptop with the same tools (Weave Scope) used when your app is deployed to a Kubernetes cluster.
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