Let's deploy our REST API to Kubernetes 🚀

Today I will show you how to deploy a REST API to a production Kubernetes cluster, using Gimlet 🚀

Let’s get started!

The problem

Two weeks ago we built a REST API to serve historical data on taxi rides in NYC. And last week we wrote a professional Dockerfile to package it inside a Docker image.

The API works like a charm on our laptop…

But the thing is, until you don’t deploy it to a production environment, and make it accessible to

• your clients 💁🏻‍♀️

• your colleagues 👨🏻‍💼

• or even the whole world 🌏

your real-world impact is ZERO.

So today, I want to show you how to deploy this API to a production Kubernetes cluster.

So you build ML software that has real-world impact 🚀

What is Kubernetes? ☸📦

Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of your Dockerized apps

It is currently the most widely used container orchestration platform in the world, and it has become the de facto standard due to its robust features, large community support, and backing from major tech companies.

 

Kubernetes is a powerful beast. However, it has also one BIG problem…

The Kubernetes YAML HELL 🔥

The Kubernetes configuration file required to deploy even the simplest service is

• very verbose,

• error-prone and

• excessively complex.

which adds too much friction (and frustration!) in your deployment process

 

So the question is

Here is the solution ⬇️

Gimlet to the rescue 🦸🏻

Gimlet is a tool that helps you quickly deploy your apps to your Kubernetes. Let me show you how.

Manual deployment 👆

Let’s do it!

• Go to gimlet.io

•   Sign up for FREE using your Github username and

• Import your github repository.

Go to your imported repository, and click on New Deployment, then pick

• Manually deploy from a Dockerfile

• From the Gimlet registry

• Set your Dockerfile name (Dockerfile.2stage in my case), and

• Set the port number your API is listening to (8000 in my case)

BOOM.

Your API is now available to the world!

What’s next? ⏭️ 

It feels great deploying to production.

However, this is not the end of the story. It is just the beginning.

Any piece of software needs to be iteratively updated over time. Hence, you need a fast and automatic way to transfer your code changes into new deployments.

How can you accomplish this?

Automatic deployments to the rescue 🦸🏻 

The Gimlet Github action helps you automatically deploy your code changes to your Kubernetes cluster.

For example, you can add a github workflow like this to your repo, that

• Triggers after every push to main branch

on:
  push:
    branches:
      - 'main'

• Tests your code

tests:
    name: 🧪 Run tests
    runs-on: ubuntu-latest
    needs:
      - "cancel-previous-runs"
    steps:
      - name: ⬇️ Check out
        uses: actions/checkout@v4
      - name: 🐍 Set up Python 3.10
        uses: actions/setup-python@v4
        with:
          python-version: '3.10'
      - name: 📦 Install Poetry
        uses: snok/install-poetry@v1
      - name: 📦 Install dependencies
        run: poetry install
      - name: 🧪 Run tests
        run: poetry run pytest tests/

• Builds and pushes the Docker image to your Docker registry (in this case, I use mine from Github)

docker-build:
    name: 📦 Docker build
    runs-on: ubuntu-latest
    needs:
    - "tests"
    steps:
    - name: ⬇️ Check out
      uses: actions/checkout@v4
    - name: 🐋 Set up Docker Buildx
      uses: docker/setup-buildx-action@v3
    - name: Login to GitHub Container Registry
      uses: docker/login-action@v3
      with:
        registry: ghcr.io
        username: ${{ github.repository_owner }}
        password: ${{ secrets.PAT }}
    - name: 🐋 Build and push docker image
      uses: docker/build-push-action@v6
      with:
        context: .
        file: Dockerfile.2stage
        platforms: linux/amd64
        push: true
        tags: ghcr.io/paulescu/taxi-data-api-python:${{ github.sha }}

• And deploys it to Kubernetes using the Gimlet action.

deploy:
    name: 🧑‍🚀 Deploy
    runs-on: ubuntu-latest
    needs:
    - "docker-build"
    if: github.ref == 'refs/heads/main'
    environment: production
    steps:
    - name: ⬇️ Check out
      uses: actions/checkout@v4
    - name: 🚀 Deploy / Production
      uses: gimlet-io/[email protected]
      with:
        DEPLOY: "true"
        ENV: "electric-paper"
        APP: "taxi-data-api-python"
      env:
        GIMLET_SERVER: ${{ secrets.GIMLET_SERVER }}
        GIMLET_TOKEN: ${{ secrets.GIMLET_TOKEN }}

Continuous delivery made simple.

BOOM!

Now it is your turn 🫵 

Happy deployments!

Talk to you next week,

Pau