hello-kubernetes

Hello Kubernetes

This tutorial will get you up and running with Dapr in a Kubernetes cluster. You will be deploying the same applications from Hello World. To recap, the Python App generates messages and the Node app consumes and persists them. The following architecture diagram illustrates the components that make up this quickstart:

Prerequisites

This quickstart requires you to have the following installed on your machine:

• kubectl
• A Kubernetes cluster, such as Minikube, AKS or GKE

Also, unless you have already done so, clone the repository with the quickstarts and cd into the right directory:

git clone [-b <dapr_version_tag>] https://github.com/dapr/quickstarts.git
cd quickstarts/tutorials/hello-kubernetes

Note: See https://github.com/dapr/quickstarts#supported-dapr-runtime-version for supported tags. Use git clone https://github.com/dapr/quickstarts.git when using the edge version of dapr runtime.

The first thing you need is an RBAC enabled Kubernetes cluster. This could be running on your machine using Minikube, or it could be a fully-fledged cluster in Azure using AKS.

Using Dapr Multi-app run with Dapr dev mode deployment

Step 1 - Setup Dapr dev mode on your Kubernetes cluster

Follow the steps below to deploy Dapr to Kubernetes using the --dev flag. For more details, see Deploy Dapr on a Kubernetes cluster.

Note: Any previous Dapr installations in the Kubernetes cluster need to be uninstalled first. You can use dapr uninstall -k to remove Dapr

With the dapr init -k --dev command, the CLI will also install he Redis and Zipkin containers dapr-dev-redis and dapr-dev-zipkin in the default namespace apart from the Dapr control plane in dapr-system namespace. The statestore, pubsub and appconfig default components and configuration are applied in the default Kubernetes namespace if they do not exist. You can use dapr components -k and dapr configurations -kto see these.

dapr init -k --dev

Expected output in a fresh Kubernetes cluster without Dapr installed:

⌛  Making the jump to hyperspace...
ℹ️  Note: To install Dapr using Helm, see here: https://docs.dapr.io/getting-started/install-dapr-kubernetes/#install-with-helm-advanced

ℹ️  Container images will be pulled from Docker Hub
✅  Deploying the Dapr control plane with latest version to your cluster...
✅  Deploying the Dapr dashboard with latest version to your cluster...
✅  Deploying the Dapr Redis with latest version to your cluster...
✅  Deploying the Dapr Zipkin with latest version to your cluster...
ℹ️  Applying "statestore" component to Kubernetes "default" namespace.
ℹ️  Applying "pubsub" component to Kubernetes "default" namespace.
ℹ️  Applying "appconfig" zipkin configuration to Kubernetes "default" namespace.
✅  Success! Dapr has been installed to namespace dapr-system. To verify, run `dapr status -k' in your terminal. To get started, go here: https://aka.ms/dapr-getting-started

Step 2 - Run the Multi-app run template to deploy both the Node.js and Python apps

To run both the Node.js and Python apps, run the following command from the hello-kubernetes directory:

dapr run -k -f dapr.yaml

Expected output

ℹ️  This is a preview feature and subject to change in future releases.
ℹ️  Validating config and starting app "nodeapp"
ℹ️  Deploying app "nodeapp" to Kubernetes
ℹ️  Deploying service YAML "/path/quickstarts/tutorials/hello-kubernetes/node/.dapr/deploy/service.yaml" to Kubernetes
ℹ️  Deploying deployment YAML "/path/quickstarts/tutorials/hello-kubernetes/node/.dapr/deploy/deployment.yaml" to Kubernetes
ℹ️  Streaming logs for containers in pod "nodeapp-6dcddb44f5-q5gnr"
ℹ️  Writing log files to directory : /path/quickstarts/tutorials/hello-kubernetes/node/.dapr/logs
ℹ️  Validating config and starting app "pythonapp"
ℹ️  Deploying app "pythonapp" to Kubernetes
ℹ️  Deploying deployment YAML "/path/quickstarts/tutorials/hello-kubernetes/python/.dapr/deploy/deployment.yaml" to Kubernetes
== APP - nodeapp == Node App listening on port 3000!
ℹ️  Streaming logs for containers in pod "pythonapp-7479cdcb7b-z827w"
ℹ️  Writing log files to directory : /path/quickstarts/tutorials/hello-kubernetes/python/.dapr/logs
ℹ️  Starting to monitor Kubernetes pods for deletion.
== APP - nodeapp == Got a new order! Order ID: 2
== APP - nodeapp == Successfully persisted state for Order ID: 2
== APP - nodeapp == Got a new order! Order ID: 3
== APP - nodeapp == Successfully persisted state for Order ID: 3
== APP - nodeapp == Got a new order! Order ID: 4
== APP - nodeapp == Successfully persisted state for Order ID: 4
== APP - nodeapp == Got a new order! Order ID: 5
== APP - nodeapp == Successfully persisted state for Order ID: 5

Use Ctrl+C to stop the apps. Or you can run the following command to stop the apps:

dapr stop -k -f dapr.yaml

This spins down the Kubernetes resources that were deployed in the previous step.

Using the kubectl CLI

Step 1 - Setup Dapr on your Kubernetes cluster

Note: This step can be skipped if already done above.

Follow the steps below to deploy Dapr to Kubernetes. For more details, see Deploy Dapr on a Kubernetes cluster.

Please note, the CLI will install to the dapr-system namespace by default. If this namespace does not exist, the CLI will create it. If you need to deploy to a different namespace, you can use -n mynamespace.

dapr init --kubernetes --wait

Sample output:

⌛  Making the jump to hyperspace...
  Note: To install Dapr using Helm, see here: https://docs.dapr.io/getting-started/install-dapr-kubernetes/#install-with-helm-advanced

✅  Deploying the Dapr control plane to your cluster...
✅  Success! Dapr has been installed to namespace dapr-system. To verify, run `dapr status -k' in your terminal. To get started, go here: https://aka.ms/dapr-getting-started

Without the --wait flag the Dapr CLI will exit as soon as the kubernetes deployments are created. Kubernetes deployments are asyncronous by default, so we use --wait here to make sure the dapr control plane is completely deployed and running before continuing.

dapr status -k

You will see output like the following. All services should show True in the HEALTHY column and Running in the STATUS column before you continue.

  NAME                   NAMESPACE    HEALTHY  STATUS   REPLICAS  VERSION  AGE  CREATED
  dapr-operator          dapr-system  True     Running  1         1.0.1    13s  2021-03-08 11:00.21
  dapr-placement-server  dapr-system  True     Running  1         1.0.1    13s  2021-03-08 11:00.21
  dapr-dashboard         dapr-system  True     Running  1         0.6.0    13s  2021-03-08 11:00.21
  dapr-sentry            dapr-system  True     Running  1         1.0.1    13s  2021-03-08 11:00.21
  dapr-sidecar-injector  dapr-system  True     Running  1         1.0.1    13s  2021-03-08 11:00.21

Step 2 - Create and configure a state store

Dapr can use a number of different state stores (Redis, CosmosDB, DynamoDB, Cassandra, etc) to persist and retrieve state. This demo will use Redis.

1. Follow these steps to create a Redis store.
2. Once your store is created, add the keys to the redis.yaml file in the deploy directory.

   Note: the redis.yaml file provided in this quickstart will work securely out-of-the-box with a Redis installed with helm install bitnami/redis. If you have your own Redis setup, replace the redisHost value with your own Redis master address, and the redisPassword with your own Secret. You can learn more here.

3. Apply the redis.yaml file and observe that your state store was successfully configured!

kubectl apply -f ./deploy/redis.yaml

component.dapr.io/statestore created

Note: If you installed Dapr using the --dev flag in Kubernetes, then the statestore component will be created automatically in the default namespace. The above commmand will output component.dapr.io/statestore configured instead of component.dapr.io/statestore created. If the --dev flag was used for Dapr init, and you want to use the dapr-dev-redis deployment as state store, replace the redisHost value inside ./deploy/redis.yaml with dapr-dev-redis-master:6379 and also the secretKeyRef, name with dapr-dev-redis. Then run the command kubectl apply -f ./deploy/redis.yaml, to apply the file again. This will create a statestore Dapr component pointing to dapr-dev-redis deployment.

Step 3 - Deploy the Node.js app with the Dapr sidecar

kubectl apply -f ./deploy/node.yaml

Kubernetes deployments are asyncronous. This means you'll need to wait for the deployment to complete before moving on to the next steps. You can do so with the following command:

kubectl rollout status deploy/nodeapp

This will deploy the Node.js app to Kubernetes. The Dapr control plane will automatically inject the Dapr sidecar to the Pod. If you take a look at the node.yaml file, you will see how Dapr is enabled for that deployment:

dapr.io/enabled: true - this tells the Dapr control plane to inject a sidecar to this deployment.

dapr.io/app-id: nodeapp - this assigns a unique id or name to the Dapr application, so it can be sent messages to and communicated with by other Dapr apps.

dapr.io/enable-api-logging: "true" - this is added to node.yaml file by default to see the API logs.

You'll also see the container image that you're deploying. If you want to update the code and deploy a new image, see Next Steps section.

There are several different ways to access a Kubernetes service depending on which platform you are using. Port forwarding is one consistent way to access a service, whether it is hosted locally or on a cloud Kubernetes provider like AKS.

kubectl port-forward service/nodeapp 8080:80

This will make your service available on http://localhost:8080.

Optional: If you are using a public cloud provider, you can substitue your EXTERNAL-IP address instead of port forwarding. You can find it with:

kubectl get svc nodeapp

Step 4 - Verify Service

To call the service that you set up port forwarding to, from a command prompt run:

curl http://localhost:8080/ports

Expected output:

{"DAPR_HTTP_PORT":"3500","DAPR_GRPC_PORT":"50001"}

Next submit an order to the app

curl --request POST --data "@sample.json" --header Content-Type:application/json http://localhost:8080/neworder

Expected output: Empty reply from server

Confirm the order was persisted by requesting it from the app

curl http://localhost:8080/order

Expected output:

{ "orderId": "42" }

Optional: Now it would be a good time to get acquainted with the Dapr dashboard. Which is a convenient interface to check status, information and logs of applications running on Dapr. The following command will make it available on http://localhost:9999/.

dapr dashboard -k -p 9999

Step 5 - Deploy the Python app with the Dapr sidecar

Next, take a quick look at the Python app. Navigate to the Python app in the kubernetes quickstart: cd quickstarts/tutorials/hello-kubernetes/python and open app.py.

At a quick glance, this is a basic Python app that posts JSON messages to localhost:3500, which is the default listening port for Dapr. You can invoke the Node.js application's neworder endpoint by posting to v1.0/invoke/nodeapp/method/neworder. The message contains some data with an orderId that increments once per second:

n = 0
while True:
    n += 1
    message = {"data": {"orderId": n}}

    try:
        response = requests.post(dapr_url, json=message)
    except Exception as e:
        print(e)

    time.sleep(1)

Deploy the Python app to your Kubernetes cluster:

kubectl apply -f ./deploy/python.yaml

As with above, the following command will wait for the deployment to complete:

kubectl rollout status deploy/pythonapp

Step 6 - Observe messages

Now that the Node.js and Python applications are deployed, watch messages come through:

Get the logs of the Node.js app:

kubectl logs --selector=app=node -c node --tail=-1

If all went well, you should see logs like this:

Got a new order! Order ID: 1
Successfully persisted state for Order ID: 1
Got a new order! Order ID: 2
Successfully persisted state for Order ID: 2
Got a new order! Order ID: 3
Successfully persisted state for Order ID: 3

Step 7 - Observe API call logs

Now that the Node.js and Python applications are deployed, watch API call logs come through:

Get the API call logs of the node app:

kubectl logs --selector=app=node -c daprd --tail=-1

When save state API calls are made, you should see logs similar to this:

time="2022-04-25T22:46:09.82121774Z" level=info method="POST /v1.0/state/statestore" app_id=nodeapp instance=nodeapp-7dd6648dd4-7hpmh scope=dapr.runtime.http-info type=log ver=1.7.2
time="2022-04-25T22:46:10.828764787Z" level=info method="POST /v1.0/state/statestore" app_id=nodeapp instance=nodeapp-7dd6648dd4-7hpmh scope=dapr.runtime.http-info type=log ver=1.7.2

Get the API call logs of the Python app:

kubectl logs --selector=app=python -c daprd --tail=-1

time="2022-04-27T02:47:49.972688145Z" level=info method="POST /neworder" app_id=pythonapp instance=pythonapp-545df48d55-jvj52 scope=dapr.runtime.http-info type=log ver=1.7.2
time="2022-04-27T02:47:50.984994545Z" level=info method="POST /neworder" app_id=pythonapp instance=pythonapp-545df48d55-jvj52 scope=dapr.runtime.http-info type=log ver=1.7.2

Step 8 - Confirm successful persistence

Call the Node.js app's order endpoint to get the latest order. Grab the external IP address that you saved before and, append "/order" and perform a GET request against it (enter it into your browser, use Postman, or curl it!):

curl $NODE_APP/order
{"orderID":"42"}

You should see the latest JSON in response!

Step 9 - Cleanup

Once you're done, you can spin down your Kubernetes resources by navigating to the ./deploy directory and running:

kubectl delete -f .

This will spin down each resource defined by the .yaml files in the deploy directory, including the state component.

Note: This will also delete the state store component. If the --dev flag was used for Dapr init, and you want to use the dapr-dev-redis deployment as state store, replace the redisHost value inside ./deploy/redis.yaml with dapr-dev-redis-master:6379 and also the secretKeyRef, name with dapr-dev-redis. Then run the command kubectl apply -f ./deploy/redis.yaml, to apply the file again. This will create a statestore Dapr component pointing to dapr-dev-redis deployment.

Deploying your code

Now that you're successfully working with Dapr, you probably want to update the code to fit your scenario. The Node.js and Python apps that make up this quickstart are deployed from container images hosted on a private Azure Container Registry. To create new images with updated code, you'll first need to install docker on your machine. Next, follow these steps:

1. Update Node or Python code as you see fit!
2. Navigate to the directory of the app you want to build a new image for.
3. Run docker build -t <YOUR_IMAGE_NAME> . . You can name your image whatever you like. If you're planning on hosting it on docker hub, then it should start with <YOUR_DOCKERHUB_USERNAME>/.
4. Once your image has built you can see it on your machines by running docker images.
5. To publish your docker image to docker hub (or another registry), first login: docker login. Then rundocker push <YOUR IMAGE NAME>.
6. Update your .yaml file to reflect the new image name.
7. Deploy your updated Dapr enabled app: kubectl apply -f <YOUR APP NAME>.yaml.

Related links

• Guidelines for production ready deployments on Kubernetes

Next steps

• Explore additional quickstarts and deploy them locally or on Kubernetes.