Unsorted Array App

This repository contains a Python application that provides an API for processing data. Given an unsorted array as an input, the app will print all unique pairs in the unsorted array with equal sum. The API is built using Flask and is designed to be simple and easy to deploy using Docker.

In addition to the application itself, the repository also includes:

• A Dockerfile to containerize the app
• Terraform scripts for infrastructure setup (like DynamoDB)
• GitHub Actions workflows for CI/CD
• Makefile targets for simplifying common tasks
• Kubernetes manifests for local Minikube deployment

Features

• A REST API that listens for POST requests and processes the data
• Integration with DynamoDB for logging requests (optional)
• Docker support for easy local development and deployment
• Kubernetes support for deployment on local clusters - Assumes minikbe has been installed locally
• CI/CD integration via GitHub Actions

Makefile Targets

The Makefile in this repository provides few useful targets for common tasks such as building, running, and pushing Docker images. Below are the available targets and their usage:

Running the App on the Dev Machine

This target sets up a virtual environment, installs the required dependencies, and starts the Flask app locally.

make run-dev

This command will:

• Create a Python virtual environment in the venv/ directory
• Install dependencies from requirements.txt
• Run the app on your local machine, accessible via http://localhost:5000

Building the Docker Image

This target builds the Docker image using the provided Dockerfile

make build

This command will:

• Build the Docker image for the app and tag it as latest

Pushing the Docker Image

This target pushes the built Docker image to the Docker registry (e.g., Docker Hub).

make push

This command will:

• Tag the local image with the appropriate tag for the Docker registry
• Push the image to the registry

Running the App Inside a Docker Container

This target runs the app in a Docker container, exposing the app on a given port (default 5000) of the host machine.

make run-container

This command will:

• Run the app within a Docker container with the latest tag
• Expose the app on a given port (default 5000) of your local machine

Build and Push the Docker Image

This target combines the build and push targets to streamline the process of building and pushing the Docker image.

make build-and-push

This command will:

• Build the Docker image
• Push the image to the Docker registry (e.g., Docker Hub)

Deploy the App to Minikube

This target deploys your app to a local Minikube Kubernetes cluster. It will apply all the necessary Kubernetes manifests (namespace, configmap, deployment, service) to the cluster.

make deploy-kubernetes

This command will:

• Build the Docker image
• Ensure Minikube is started
• Apply the namespace, configMap, deployment, and service manifests to deploy the app to the Minikube cluster

Once this target has been executed, one can use kubectl port-forward to expose the app to a local port as:

kubectl -n dev port-forward service/unsorted-array-app-svc 5000:5000

If on the minikube cluster the app image cannot be downloaded you might have to use:

eval $(minikube -p minikube docker-env)

To clean-up the cluster, simply run:

minikube delete

Suggestions for Improvements

The repo currently holds a simplistic approach to the implementation. A couple of things that could be improved are:

• Use of tflocal for local testing with DynamoDB. More specifically, attempts of using tflocal to deploy the DynamoDB and get the app to use it, did not succeed. In order to keep this implementation within a reasonable time-frame, the in-memory-store alternative was implemented
• Adding a Helm chart to make the app deployable on Kubernetes, using Helm