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Telepresence Quick Start - Python (Flask)

Contents

Prerequisites

You’ll need kubectl or oc installed and set up (Linux / macOS / Windows) to use a Kubernetes cluster, preferably an empty test cluster. This document uses kubectl in all example commands, but OpenShift users should have no problem substituting in the oc command instead.

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

1. Install the Telepresence CLI

GNU/Linux
macOS
Windows

2. Test Telepresence

Telepresence connects your local workstation to a remote Kubernetes cluster.

  1. Connect to the cluster: telepresence connect

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

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 multiservice 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/master/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.git

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

  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/DataProcessingService/app.py in your editor and change DEFAULT_COLOR on line 15 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 a personal intercept with a preview URL; meaning that 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. Log in to Ambassador Cloud, a web interface for managing and sharing preview URLs:

    If you are in an environment where Telepresence cannot launch a local browser for you to interact with, you will need to pass the --apikey flag to telepresence login.

  3. 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.

  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. 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!

logo What's Next?

Collaborating

Use preview URLS to collaborate with your colleagues and others outside of your organization.

Outbound Sessions

While connected to the cluster, your laptop can interact with services as if it was another pod in the cluster.

FAQs

Learn more about uses cases and the technical implementation of Telepresence.