This application fetches and serves character data from the "Rick and Morty" API using specific filters.

1. Docker installed in the system : https://www.docker.com/
2. Minikube installed in the system and k8s local cluster created with it and running: https://minikube.sigs.k8s.io/docs/start/

This workflow automates the deployment and testing of the "Rick and Morty API Data Fetcher" application on a local Kubernetes cluster using Helm and kind (Kubernetes in Docker). The workflow is triggered on every push to the repository.

This step checks out the latest version of your code from the repository using the actions/checkout@v4 action.

Initializes Helm, the package manager for Kubernetes, using the azure/setup-helm@v3 action.

Installs kind, a tool for running local Kubernetes clusters using Docker container nodes. The specific version v0.20.0 is used in this step.

This step checks the status of the kind cluster by:

• Displaying cluster information
• Listing system pods
• Showing the current Kubernetes context
• Displaying the environment's kubeconfig
• Listing Docker images present

Initializes Docker Buildx using the docker/setup-buildx-action@v3 action. Buildx is an extension for building container images.

Builds the Docker image for the "Rick and Morty API Data Fetcher" application using the specified Dockerfile and tags it as rick-and-morty-app:latest. The built image is also loaded into the Docker daemon.

Loads the Docker image into the kind cluster, making it available for deployment.

Uses Helm to deploy the application to the Kubernetes cluster. Overrides the image name and tag to use the locally built Docker image.

• Waits for the application's deployment to be ready using Helm and kubectl.
• Sets up port forwarding from the service to localhost on port 5000.

Sends an HTTP request to the application's /data endpoint and processes the output using jq.

Deletes the kind cluster, cleaning up all resources.