Telepresence Quick Start - Python (FastAPI)

Prerequisites

You’ll need kubectl installed and set up (Linux / macOS / Windows) to use a Kubernetes cluster, preferably an empty test cluster.

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

1. Install the Telepresence CLI

2. Test Telepresence

Telepresence connects your local workstation to a remote Kubernetes cluster.

1. Connect to the cluster: telepresence connect

   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.

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

   Didn't work? Make sure you are using Telepresence 2.0.3 or greater, check with telepresence version and upgrade here if needed.
   The 401 response is expected. What's important is that you were able to contact the API.

3. Install a sample Python 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.

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

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

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

3. Once all the pods are in a Running state, go to the frontend service in your browser at http://verylargejavaservice.default:8080.

4. You should see the EdgyCorp WebApp with a green title and green pod in the diagram.

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.

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

2. Change into the repo directory, then into DataProcessingService: cd edgey-corp-python-fastapi/DataProcessingService/

3. Install the dependencies and start the Python server. Python 2.x: pip install fastapi uvicorn requests && python app.py Python 3.x: pip3 install fastapi uvicorn requests && python3 app.py

   Install Python from here if needed.

4. In a new terminal window, curl the service running locally to confirm it’s set to blue: curl localhost:3000/color

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:

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

2. 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.

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.

1. Open edgey-corp-python-fastapi/DataProcessingService/app.py in your editor and change DEFAULT_COLOR on line 17 from blue to orange. Save the file and the Python server will auto reload.

2. Now, visit http://verylargejavaservice:8080 again in your browser. You will now see the orange elements in the application.

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.

1. Clean up your previous intercept by removing it: telepresence leave dataprocessingservice

2. 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.

3. Start the intercept again: telepresence intercept dataprocessingservice --port 3000 --mount=false You will be asked for your ingress; specify the front end service: verylargejavaservice.default Then when asked for the port, type 8080. Finally, type n for “Use TLS”.

4. 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.

5. Go again to http://verylargejavaservice:8080 and 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!

What's Next?