|
1 | | -# neploy |
| 1 | +# Setting up the Kubernetes Cluster Backend |
| 2 | +## Prerequisites |
| 3 | +Before you proceed with setting up the backend for Neploy, please ensure that you have the following prerequisites in place: |
| 4 | +1. **Kubernetes Cluster:** You should have a Kubernetes cluster deployed and accessible. If you don't have a Kubernetes cluster, you can deploy one using tools like [Minikube](https://minikube.sigs.k8s.io/), [k3s](https://k3s.io/), or on cloud providers like [Google Kubernetes Engine](https://cloud.google.com/kubernetes-engine), [Amazon EKS](https://aws.amazon.com/eks/), or [Microsoft Azure Kubernetes Service (AKS)](https://azure.microsoft.com/en-us/services/kubernetes-service/). |
| 5 | +2. **kubectl:** Ensure that you have the `kubectl` command-line tool installed and configured to interact with your Kubernetes cluster. |
| 6 | +3. **Docker:** You should have Docker installed on your local machine to build and push Docker images. You can download and install Docker from the [official Docker website](https://www.docker.com/get-started). |
| 7 | +4. **Container Registry:** You'll need access to a container registry to push your Docker images. Popular options include [Docker Hub](https://hub.docker.com/), [Google Container Registry](https://cloud.google.com/container-registry), and [Amazon Elastic Container Registry (ECR)](https://aws.amazon.com/ecr/). |
| 8 | + |
| 9 | +To deploy the backend for Neploy on a Kubernetes cluster, follow these steps: |
| 10 | + |
| 11 | +1. Navigate to the backend src files directory: |
| 12 | +```bash |
| 13 | +cd neploy-build-python |
| 14 | +``` |
| 15 | +2. Build the Docker image using the provided Dockerfile: |
| 16 | +```bash |
| 17 | +docker build --tag neploy-build-python:latest . |
| 18 | +``` |
| 19 | +3. Push the Docker image to a container registry of your choice (e.g., Docker Hub, Google Container Registry): |
| 20 | +```bash |
| 21 | +docker tag neploy-backend <registry-name>/neploy-build-python:latest |
| 22 | +docker push <registry-name>/neploy-build-python:latest |
| 23 | +``` |
| 24 | +This Dockerfile uses an Ubuntu base image to create a containerized environment for the backend. |
| 25 | + |
| 26 | +4. Open a terminal and make sure you have kubectl configured to access your Kubernetes cluster. |
| 27 | + |
| 28 | +5. Deploy the Kubernetes pod containing the backend using the following command: |
| 29 | +```bash |
| 30 | +kubectl apply -f neploy-build-python/deployment.yaml |
| 31 | +``` |
| 32 | +This deployment.yaml file specifies a pod running the Python Flask scripts for the backend. The /build endpoint is exposed to compile code, and the /optimise endpoint is exposed for AI/ML code review. |
| 33 | + |
| 34 | +6. Deploy the service endpoint for the backend: |
| 35 | +```bash |
| 36 | +kubectl apply -f neploy-build-python/service.yaml |
| 37 | +``` |
| 38 | +This service.yaml file creates a Kubernetes service to expose the pod's endpoints within the cluster. |
| 39 | + |
| 40 | +Once the service is deployed, you can access the backend endpoints from your frontend application using the Kubernetes service's ClusterIP and port. |
| 41 | + |
| 42 | +Ensure that the frontend makes POST REST API calls to the /build and /optimise endpoints of the backend pod to submit code for compilation and AI/ML code review respectively. |
| 43 | + |
| 44 | +Your Kubernetes cluster backend for Neploy is now set up and ready to handle code compilation and AI/ML code review requests from the frontend. |
| 45 | + |
| 46 | +Please note that these steps are general guidelines and might need adjustments based on your Kubernetes cluster setup and networking configurations. |
| 47 | + |
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