# Excercise - 5 In this section, you will re-create the guestbook application, but this time with more components in a multi-tier architecture. This application uses the `v2` version of the go application we used previously in the workshop as our web front end, and adds on 1) a Redis master for storage, 2) a replicated set of Redis slaves, and 3) a Python Flask application that calls the Watson Tone Analyzer service deployed in IBM Cloud. For all of these components, there are Kubernetes replication controllers, pods, and services. One of the main concerns with building a multi-tier application on Kubernetes, such as this one, is resolving dependencies between all of these seperately deployed components. In a multiple tier application, there are two primary ways that service dependencies can be resolved. The [`v2/guestbook/main.go`](https://github.com/IBM/cloudpakforapplications-appmod-workshop/tree/ebd6be7840f361e749fdba87cf5f9e52fccc6e58/workshop/generatedContent/v2/guestbook/main.go) code provides examples of each. For Redis, the master endpoint is discovered through environment variables. These environment variables are set when the Redis services are started, so the service resources need to be created before the guestbook replication controller starts the guestbook pods. For the analyzer service, an http request is made to a hostname, which allows for resource discovery at the time when the request is made. Consequently, we'll follow a specific order when creating the application components. First up, the Redis components will be created, then the guestbook application, and finally the analyzer microservice. ## Setup Continue by working in the web terminal. Change to the `v2` folder where the deployment files reside: ``` cd $HOME/digidevcon-iks/v2 ``` ## Create the Redis master pod Use the `redis-master-deployment.yaml` file to create a [replication controller](https://kubernetes.io/docs/concepts/workloads/controllers/replicationcontroller/) and Redis master [pod](https://kubernetes.io/docs/concepts/workloads/pods/pod-overview/). The pod runs a Redis key-value server in a container. Using a replication controller is the preferred way to launch long-running pods, even for 1 replica, so that the pod inherits benefits from the self-healing mechanism in Kubernetes (i.e. keeps the pods alive). 1. Use the [redis-master-deployment.yaml](https://github.com/IBM/cloudpakforapplications-appmod-workshop/tree/ebd6be7840f361e749fdba87cf5f9e52fccc6e58/workshop/generatedContent/v2/redis-master-deployment.yaml) file to create the Redis master deployment in your Kubernetes cluster: ``` kubectl create -f redis-master-deployment.yaml ``` ``` $ kubectl create -f redis-master-deployment.yaml deployment.apps/redis-master created ``` 2. To verify that the redis-master controller is up, list the deployment and replicaset you created in the cluster with the `kubectl get` command (if you don't specify a `--namespace`, the current project/namespace will be used): ``` kubectl get deploy ``` this will show the current deployments in the namespace ``` $ kubectl get deploy NAME READY UP-TO-DATE AVAILABLE AGE redis-master 1/1 1 1 15s ``` ``` kubectl get replicaset ``` this will show the current deployments in the namespace ``` $ kubectl get replicaset NAME DESIRED CURRENT READY AGE redis-master-7b7968db76 1 1 1 41s ``` Result: The deployment creates the replicaset, which then creates the single Redis master pod. 3. Verify that the redis-master pod is running, by listing the pods you created in cluster: ``` kubectl get pods ``` ``` $ kubectl get pods NAME READY STATUS RESTARTS AGE redis-master-7b7968db76-8mjqg 1/1 Running 0 67s ``` Result: You'll see a single Redis master pod (may take up to thirty seconds). ## Create the Redis master service A Kubernetes [service](https://kubernetes.io/docs/concepts/services-networking/service/) is a named load balancer that proxies traffic to one or more pods. The services in a Kubernetes cluster are discoverable inside other pods via environment variables or DNS. Services find the pods to load balance based on pod labels. The pod that you created in previous step has the label `app=redis` and `role=master`. The selector field of the service determines which pods will receive the traffic sent to the service. 1. Use the [redis-master-service.yaml](https://github.com/IBM/cloudpakforapplications-appmod-workshop/tree/ebd6be7840f361e749fdba87cf5f9e52fccc6e58/workshop/generatedContent/v2/redis-master-service.yaml) file to create the service in your Kubernetes cluster: ``` kubectl create -f redis-master-service.yaml ``` ``` $ kubectl create -f redis-master-service.yaml service/redis-master created ``` 2. To verify that the redis-master service is up, list the services you created in the cluster: ``` kubectl get services ``` ``` $ kubectl get services NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kubernetes ClusterIP 172.21.0.1 443/TCP 8h redis-master ClusterIP 172.21.36.3 6379/TCP 10s ... ``` Result: All new pods will see the `redis-master` service running on the host (`$REDIS_MASTER_SERVICE_HOST` environment variable) at port `6379`, or running on `redis-master:6379`. After the service is created, the service proxy on each node is configured to set up a proxy on the specified port (in our example, that's port `6379`). ## Create the Redis slave pods The Redis master we created earlier is a single pod (REPLICAS = 1), while the Redis read slaves we are creating here are 'replicated' pods with 2 instances that will be started. In Kubernetes, a replication controller is responsible for managing the multiple instances of a replicated pod. 1. Use the file [redis-slave-deployment.yaml](https://github.com/IBM/cloudpakforapplications-appmod-workshop/tree/ebd6be7840f361e749fdba87cf5f9e52fccc6e58/workshop/generatedContent/v2/redis-slave-deployment.yaml) to create the replication controller: ``` kubectl create -f redis-slave-deployment.yaml ``` ``` $ kubectl create -f redis-slave-deployment.yaml deployment.apps/redis-slave created ``` 2. To verify that the redis-slave controller is running: ``` kubectl get rs ``` ``` $ kubectl get rs NAME DESIRED CURRENT READY AGE redis-master-7b7968db76 1 1 1 2m48s redis-slave-6944587c87 2 2 2 36s ``` Result: The deployment creates the replicaset, which then creates configures the Redis slave pods through the redis-master service (name:port pair, in our example that's `redis-master:6379`). 3. Verify that the Redis master and slaves pods are running: ``` kubectl get pods ``` ``` $ kubectl get pods NAME READY STATUS RESTARTS AGE redis-master-7b7968db76-8mjqg 1/1 Running 0 3m25s redis-slave-6944587c87-4gvgj 1/1 Running 0 73s redis-slave-6944587c87-h66wp 1/1 Running 0 73s ... ``` Result: You see the single Redis master and two Redis slave pods. ## Create the Redis slave service Just like the master, we want to have a service to proxy connections to the read slaves. In this case, in addition to discovery, the Redis slave service provides transparent load balancing to clients. 1. Use the [redis-slave-service.yaml](https://github.com/IBM/cloudpakforapplications-appmod-workshop/tree/ebd6be7840f361e749fdba87cf5f9e52fccc6e58/workshop/generatedContent/v2/redis-slave-service.yaml) file to create the Redis slave service: ``` kubectl create -f redis-slave-service.yaml ``` ``` $ kubectl create -f redis-slave-service.yaml service/redis-slave created ``` 2. To verify that the redis-slave service is up, list the services you created: ``` kubectl get services ``` ``` $ kubectl get services NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kubernetes ClusterIP 172.21.0.1 443/TCP 8h redis-master ClusterIP 172.21.36.3 6379/TCP 2m32s redis-slave ClusterIP 172.21.251.35 6379/TCP 7s ``` Result: The service is created and accessible at `redis-slave:6379` by pods running in the project ## Create the guestbook pods This is a simple Go `net/http` ([negroni](https://github.com/codegangsta/negroni) based) server that is configured to talk to either the slave or master services depending on whether the request is a read or a write. The pods we are creating expose a simple JSON interface and serves a jQuery-Ajax based UI. Like the Redis read slaves, these pods are also managed by a replication controller. 1. Use the [guestbook-deployment.yaml](https://github.com/IBM/cloudpakforapplications-appmod-workshop/tree/ebd6be7840f361e749fdba87cf5f9e52fccc6e58/workshop/generatedContent/v2/guestbook-deployment.yaml) file to create the guestbook replication controller: ``` kubectl create -f guestbook-deployment.yaml ``` ``` $ kubectl create -f guestbook-deployment.yaml deployment.apps/guestbook-v2 created ``` > Tip: If you want to modify the guestbook code it can be found in the `guestbook` directory, along with its Makefile. If you have pushed your custom image be sure to update the `image` property accordingly in the guestbook-deployment.yaml. 1. Verify that the guestbook deployment is running: ``` kubectl get deploy ``` ``` $ kubectl get deploy NAME READY UP-TO-DATE AVAILABLE AGE guestbook-v2 3/3 3 3 24s redis-master 1/1 1 1 5m37s redis-slave 2/2 2 2 3m58s ``` 2. Verify that the guestbook pods are running (it might take up to thirty seconds to create the pods): ``` kubectl get pods ``` ``` $ kubectl get pods NAME READY STATUS RESTARTS AGE guestbook-v2-75fbf9c4d-c2m6s 1/1 Running 0 25s guestbook-v2-75fbf9c4d-nx2f2 1/1 Running 0 25s guestbook-v2-75fbf9c4d-p2x97 1/1 Running 0 25s redis-master-7b7968db76-8mjqg 1/1 Running 0 5m10s redis-slave-6944587c87-4gvgj 1/1 Running 0 2m58s redis-slave-6944587c87-h66wp 1/1 Running 0 2m58s ``` Result: You see a single Redis master, two Redis slaves, and three guestbook pods. ## Create and expose the guestbook service Just like the others, we create a service to group the guestbook pods. Since guestbook uses a web application protocol we will expose it for access outside the cluster using a service of type \`NodePort. 1. Use the [guestbook-service.yaml](https://github.com/IBM/cloudpakforapplications-appmod-workshop/tree/ebd6be7840f361e749fdba87cf5f9e52fccc6e58/workshop/generatedContent/v2/guestbook-service.yaml) file to create the guestbook service: ``` kubectl create -f guestbook-service.yaml ``` 2. Verify that the guestbook service is up by listing the services in the cluster: ``` kubectl get services ``` ``` $ kubectl get services NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE guestbook NodePort 172.21.128.59 3000:30796/TCP 35s kubernetes ClusterIP 172.21.0.1 443/TCP 8h redis-master ClusterIP 172.21.36.3 6379/TCP 13m redis-slave ClusterIP 172.21.251.35 6379/TCP 11m ``` Result: The service is created, and exposed as a NodePort and in this example is listening on `30796`. ## Create the analyzer pod This is a simple Python Flask application that creates a POST endpoint `/tone` and takes the input text and sends it to the Watson Tone Analyzer service. In the [analyzer-deployment.yaml](https://github.com/IBM/cloudpakforapplications-appmod-workshop/tree/ebd6be7840f361e749fdba87cf5f9e52fccc6e58/workshop/generatedContent/v2/analyzer-deployment.yaml) the spec for the pod defines environment variables for the service credentials by reading the secret `binding-tone` created by the IBM Cloud operator. 1. Use the [analyzer-deployment.yaml](https://github.com/IBM/cloudpakforapplications-appmod-workshop/tree/ebd6be7840f361e749fdba87cf5f9e52fccc6e58/workshop/generatedContent/v2/analyzer-deployment.yaml) file to create the analyzer replication controller: ``` kubectl create -f analyzer-deployment.yaml ``` ``` $ kubectl create -f analyzer-deployment.yaml deployment.apps/analyzer created ``` Tip: If you want to modify the analyzer code it can be found in the `analyzer` directory, along with its Makefile. If you have pushed your custom image be sure to update the `image` property accordingly in the analyzer-deployment.yaml. 2. Verify that the guestbook deployment is running: ``` kubectl get deploy ``` ``` $ kubectl get deploy NAME READY UP-TO-DATE AVAILABLE AGE analyzer 0/1 1 0 16s guestbook-v2 3/3 3 3 14m redis-master 1/1 1 1 19m redis-slave 2/2 2 2 17m ``` ## Create the analyzer service Create a service so that the guestbook application can call the analyzer pod 1. Use the [analyzer-service.yaml](https://github.com/IBM/cloudpakforapplications-appmod-workshop/tree/ebd6be7840f361e749fdba87cf5f9e52fccc6e58/workshop/generatedContent/v2/analyzer-service.yaml) file to create the analyzer service: ``` kubectl create -f analyzer-service.yaml ``` 2. To verify that the analyzer service is up, list the services created in the cluster: ``` kubectl get services ``` ``` $ kubectl get services NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE analyzer ClusterIP 172.21.125.6 80/TCP 38s guestbook NodePort 172.21.128.59 3000:30796/TCP 5m54s kubernetes ClusterIP 172.21.0.1 443/TCP 8h redis-master ClusterIP 172.21.36.3 6379/TCP 19m redis-slave ClusterIP 172.21.251.35 6379/TCP 16m ``` Result: The service is created ## View the guestbook You can now play with the guestbook that you just created by opening it in a browser, use the IP and NodePort for your deployment. Find the IP address for your cluster using this command (use the Public IP): ``` ibmcloud ks workers -c mycluster ``` ``` $ ibmcloud ks workers -c mycluster ID Public IP Private IP Flavor State Status Zone Version kube-bmotc1dd0i2tk1jloing-mycluster-default-0000008d 184.172.252.167 10.76.195.211 free normal Ready hou02 1.14.7_1535 ``` In this example the IP is: `184.172.252.167` Get the nodeport (it will be different from the first exercise): ``` kubectl get service guestbook ``` ``` $ kubectl get service guestbook NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE guestbook NodePort 172.21.64.67 3000:30796/TCP 9m16s ``` For this value of IP address and NodePort, you would use a url like `http://184.172.252.167:30796` to access the guestbook. Result: The guestbook displays in your browser: ![Guestbook](https://3686722056-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-M1Bh2a26msY5M4vW3R9%2Fsync%2Ff144f00778da7d774d096b45fbbe366de521fb17.png?generation=1590609040589471\&alt=media) ## Cleanup After you're done playing with the guestbook, you can cleanup by deleting the guestbook service and removing the associated resources that were created, including routes, forwarding rules, target pools, and Kubernetes replication controllers and services. Delete all the resources sourced by the files in the `v2` directory: ``` kubectl delete -f . ``` ``` $ kubectl delete -f . deployment.apps "analyzer" deleted service "analyzer" deleted deployment.apps "guestbook-v2" deleted service "guestbook" deleted deployment.apps "redis-master" deleted service "redis-master" deleted deployment.apps "redis-slave" deleted service "redis-slave" deleted ```