Telepresence Quick Start - NodeJS

Prerequisites
1. Install the Telepresence CLI
2. Test Telepresence
3. Install a sample Node.js application
4. Set up a local development environment
5. Intercept all traffic to the service
6. Make a code change
7. Create a Preview URL
What's next?

Prerequisites

You’ll need kubectl installed and setup to use a Kubernetes cluster, preferably an empty test cluster.

Need a cluster? We provide free demo clusters to use with this quick start, quickly set one up!.

If you have used Telepresence previously, please first reset your Telepresence deployment with: telepresence uninstall --everything.

1. Install the Telepresence CLI

# 1. Download the latest binary (~60 MB):
sudo curl -fL https://app.getambassador.io/download/tel2/darwin/amd64/latest/telepresence -o /usr/local/bin/telepresence
 
# 2. Make the binary executable:
sudo chmod a+x /usr/local/bin/telepresence

2. Test Telepresence

Telepresence connects your local workstation to a remote Kubernetes cluster.

Connect to the cluster: telepresence connect
Terminal
```
$ telepresence connect
  Launching Telepresence Daemon
  ...
  Connected to context default (https://<cluster-public-IP>)
```
macOS users: If you receive an error when running Telepresence that the developer cannot be verified, open
System Preferences → Security & Privacy → General.
Click Open Anyway at the bottom to bypass the security block. Then retry the telepresence connect command.

Test that Telepresence is working properly by connecting to the Kubernetes API server: curl -ik https://kubernetes.default.svc.cluster.local

Didn't work? Make sure you are using Telepresence 2.0.3 or greater, check with telepresence version and upgrade here if needed.

$ curl -ik https://kubernetes.default.svc.cluster.local
  HTTP/1.1 401 Unauthorized
  Cache-Control: no-cache, private
  Content-Type: application/json
  Www-Authenticate: Basic realm="kubernetes-master"
  Date: Tue, 09 Feb 2021 23:21:51 GMT
  Content-Length: 165
  {
    "kind": "Status",
    "apiVersion": "v1",
    "metadata": {
    },
    "status": "Failure",
    "message": "Unauthorized",
    "reason": "Unauthorized",
    "code": 401
  }%

The 401 response is expected. What's important is that you were able to contact the API.

Congratulations! You’ve just accessed your remote Kubernetes API server, as if you were on the same network! With Telepresence, you’re able to use any tool that you have locally to connect to any service in the cluster.

3. Install a sample Node.js application

Your local workstation may not have the compute or memory resources necessary to run all the services in a multi-service application. In this example, we’ll show you how Telepresence can give you a fast development loop, even in this situation.

While Telepresence works with any language, this guide uses a sample app written in Node.js. We have versions in Go, Java,Python using Flask, and Python using FastAPI if you prefer.

Start by installing a sample application that consists of multiple services: kubectl apply -f https://raw.githubusercontent.com/datawire/edgey-corp-nodejs/main/k8s-config/edgey-corp-web-app-no-mapping.yaml

$ kubectl apply -f https://raw.githubusercontent.com/datawire/edgey-corp-nodejs/main/k8s-config/edgey-corp-web-app-no-mapping.yaml
  deployment.apps/dataprocessingservice created
  service/dataprocessingservice created
  ...

Give your cluster a few moments to deploy the sample application.

Use kubectl get pods to check the status of your pods:

$ kubectl get pods
  NAME                                         READY   STATUS    RESTARTS   AGE
  verylargedatastore-855c8b8789-z8nhs          1/1     Running   0          78s
  verylargejavaservice-7dfddbc95c-696br        1/1     Running   0          78s
  dataprocessingservice-5f6bfdcf7b-qvd27       1/1     Running   0          79s

Once all the pods are in a Running state, go to the frontend service in your browser at http://verylargejavaservice.default.svc.cluster.local:8080.
You should see the EdgyCorp WebApp with a green title and green pod in the diagram.

Congratulations, you can now access services running in your cluster by name from your laptop!

4. Set up a local development environment

You will now download the repo containing the services' code and run the DataProcessingService service locally. This version of the code has the UI color set to blue instead of green.

Confirm first that nothing is running locally on port 3000! If curl localhost:3000 returns Connection refused then you should be good to go.

Clone the web app’s GitHub repo: git clone https://github.com/datawire/edgey-corp-nodejs.git

$ git clone https://github.com/datawire/edgey-corp-nodejs.git
  Cloning into 'edgey-corp-nodejs'...
  remote: Enumerating objects: 441, done.
  ...

Change into the repo directory, then into DataProcessingService: cd edgey-corp-nodejs/DataProcessingService/
Install the dependencies and start the Node server: npm install && npm start
Terminal
```
$ npm install && npm start
  ...
  Welcome to the DataProcessingService!
  { _: [] }
  Server running on port 3000
```
Install Node.js from here if needed.
In a new terminal window, curl the service running locally to confirm it’s set to strong: curl localhost:3000/color
Terminal
```
$ curl localhost:3000/color
  "blue"
```

Victory, your local Node server is running a-ok!

5. Intercept all traffic to the service

Next, we’ll create an intercept. An intercept is a rule that tells Telepresence where to send traffic. In this example, we will send all traffic destined for the DataProcessingService to the version of the DataProcessingService running locally instead:

Start the intercept with the intercept command, setting the service name and port: telepresence intercept dataprocessingservice --port 3000

$ telepresence intercept dataprocessingservice --port 3000
  Using deployment dataprocessingservice
  intercepted
      Intercept name: dataprocessingservice
      State         : ACTIVE
      Destination   : 127.0.0.1:3000
      Intercepting  : all TCP connections

Go to the frontend service again in your browser. Since the service is now intercepted it can be reached directly by its service name at http://verylargejavaservice:8080. You will now see the blue elements in the app.
See this doc for more information on how Telepresence resolves DNS.

The frontend’s request to DataProcessingService is being intercepted and rerouted to the Node server on your laptop!

6. Make a code change

We’ve now set up a local development environment for the DataProcessingService, and we’ve created an intercept that sends traffic in the cluster to our local environment. We can now combine these two concepts to show how we can quickly make and test changes.

Open edgey-corp-nodejs/DataProcessingService/app.js in your editor and change line 6 from blue to orange. Save the file and the Node server will auto reload.
Now, visit http://verylargejavaservice:8080 again in your browser. You will now see the orange elements in the application.

We’ve just shown how we can edit code locally, and immediately see these changes in the cluster.
Normally, this process would require a container build, push to registry, and deploy.
With Telepresence, these changes happen instantly.

7. Create a Preview URL

Create preview URLs to do selective intercepts, meaning only traffic coming from the preview URL will be intercepted, so you can easily share the services you’re working on with your teammates.

Clean up your previous intercept by removing it: telepresence leave dataprocessingservice
Login to Ambassador Cloud, a web interface for managing and sharing preview URLs: telepresence login
This opens your browser; login with your GitHub account and choose your org.
Terminal
```
$ telepresence login
  Launching browser authentication flow...
  <browser opens, login with GitHub>
  Login successful.
```

Start the intercept again: telepresence intercept dataprocessingservice --port 3000 You will be asked for your ingress layer 3 address; specify the front end service: verylargejavaservice.default Then when asked for the port, type 8080, for "use TLS", type n and finally confirm the layer 5 hostname.

$ telepresence intercept dataprocessingservice --port 3000
    To create a preview URL, telepresence needs to know how cluster
    ingress works for this service.  Please Select the ingress to use.
    
    1/4: What's your ingress' layer 3 (IP) address?
         You may use an IP address or a DNS name (this is usually a
         "service.namespace" DNS name).
    
           [no default]: verylargejavaservice.default
    
    2/4: What's your ingress' layer 4 address (TCP port number)?
    
           [no default]: 8080
    
    3/4: Does that TCP port on your ingress use TLS (as opposed to cleartext)?
    
           [default: n]:
    
    4/4: If required by your ingress, specify a different layer 5 hostname
         (TLS-SNI, HTTP "Host" header) to access this service.
    
           [default: verylargejavaservice.default]:
    
    Using deployment dataprocessingservice
    intercepted
        Intercept name  : dataprocessingservice
        State           : ACTIVE
        Destination     : 127.0.0.1:3000
        Intercepting    : HTTP requests that match all of:
          header("x-telepresence-intercept-id") ~= regexp("86cb4a70-c7e1-1138-89c2-d8fed7a46cae:dataprocessingservice")
        Preview URL     : https://<random-subdomain>.preview.edgestack.me
        Layer 5 Hostname: verylargejavaservice.default

Wait a moment for the intercept to start; it will also output a preview URL. Go to this URL in your browser, it will be the orange version of the app.
Now go again to http://verylargejavaservice:8080, it’s still green.

Normal traffic coming to your app gets the green cluster service, but traffic coming from the preview URL goes to your laptop and gets the orange local service!

The Preview URL now shows exactly what is running on your local laptop -- in a way that can be securely shared with anyone you work with.

Questions?

We’re here to help. If you have questions, join our Slack or contact us.

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Telepresence Quick Start - NodeJS

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