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Merge pull request #2 from MirkoZETA/feature/cloud-run-deployment
Implemented Cloud Run instead of Kubernetes plus new functionalities: - New endpoint `/help`. - New networks and bitrates alternatives. - New algorithms alternative ExactFit. - Implemented K route parameter. - Separated Jobs in YML file. - Updated README.
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‎.github/workflows/gke-cd.yml‎

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name: Deploy FNS API
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name: Deploy FNS API to Cloud Run (Separated Jobs)
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on:
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push:
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branches:
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- develop
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- master
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pull_request:
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branches:
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- develop
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- master
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jobs:
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deploy:
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name: Build, Push Docker Image & Deploy to Kubernetes
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build-and-push-image:
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name: Build and Push Docker Image
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runs-on: ubuntu-latest
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steps:
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- name: Checkout code
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with:
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version: latest
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project_id: ${{ secrets.GOOGLE_PROJECT }}
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install_components: kubectl # Install kubectl component
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- name: Install gke-gcloud-auth-plugin # Install the auth plugin
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run: |
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CLOUD_SDK_URL="https://packages.cloud.google.com/apt"
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echo "deb $CLOUD_SDK_URL cloud-sdk main" | sudo tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
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curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add -
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sudo apt-get update -y
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sudo apt-get install google-cloud-sdk-gke-gcloud-auth-plugin -y
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- name: Configure Docker to push to Artifact Registry # Configure docker auth
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run: |
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docker build -t $IMAGE_NAME:$IMAGE_TAG .
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docker push $IMAGE_NAME:$IMAGE_TAG
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- name: Get Kubernetes cluster credentials # Get cluster credentials
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env:
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GOOGLE_PROJECT: ${{ secrets.GOOGLE_PROJECT }}
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CLUSTER_NAME: flex-net-sim-cluster
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CLUSTER_REGION: us-central1
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run: |
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gcloud container clusters get-credentials $CLUSTER_NAME --region $CLUSTER_REGION --project $GOOGLE_PROJECT
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deploy-to-cloud-run:
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name: Deploy to Cloud Run
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runs-on: ubuntu-latest
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needs: build-and-push-image # Ensure this job runs after build-and-push-image
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steps:
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- name: Checkout code (again, if needed for deploy steps - optional)
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uses: actions/checkout@v2
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- name: Deploy to Kubernetes cluster # Deploy to cluster
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env:
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DEPLOYMENT_NAME: fns-api-deployment
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NAMESPACE: default # Replace with your namespace if needed
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IMAGE_NAME: us-central1-docker.pkg.dev/${{ secrets.GOOGLE_PROJECT }}/flex-net-sim-repo/fns-api
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IMAGE_TAG: latest
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run: |
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kubectl apply -f - <<EOF
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apiVersion: apps/v1
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kind: Deployment
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metadata:
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name: $DEPLOYMENT_NAME
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namespace: $NAMESPACE
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spec:
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replicas: 2 # Adjust as needed
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selector:
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matchLabels:
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app: fns-api
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template:
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metadata:
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labels:
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app: fns-api
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spec:
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containers:
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- name: fns-api-container
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image: $IMAGE_NAME:$IMAGE_TAG
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ports:
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- containerPort: 8080 # Replace with your application port
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---
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apiVersion: v1
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kind: Service
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metadata:
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name: fns-api-service
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namespace: $NAMESPACE
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spec:
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selector:
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app: fns-api
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ports:
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- protocol: TCP
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port: 80
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targetPort: 8080 # Replace with your application port
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type: LoadBalancer
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EOF
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- name: Google Cloud Auth # Authenticate gcloud CLI
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uses: google-github-actions/auth@v2
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with:
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credentials_json: ${{ secrets.GOOGLE_APPLICATION_CREDENTIALS }}
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- name: Deploy to Cloud Run
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uses: google-github-actions/deploy-cloudrun@v1
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with:
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image: us-central1-docker.pkg.dev/${{ secrets.GOOGLE_PROJECT }}/flex-net-sim-repo/fns-api:latest # Use the same image as built
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service: fns-api-cloud-run
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region: us-central1
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project_id: ${{ secrets.GOOGLE_PROJECT }}

‎README.md‎

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# Flex Net Sim Backend API
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Flask-based backend API for integrating the FlexNetSim C++ library, powering the web application deployed at [www.in-progress.com](www.in-progress.com). While unofficial, it serves as a bridge between the simulation engine and the web interface.
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Flask-based backend API for integrating the FlexNetSim C++ library, powering the web application.
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## Prerequisites
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* Python 3.9 or higher
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* g++ (GNU C++ Compiler)
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* Docker (for containerization)
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* Google Cloud SDK (for deployment to GKE) -> In progress.
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* A Google Cloud Project with Google Kubernetes Engine (GKE) and Google Container Registry (GCR) enabled -> In progress.
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* Google Cloud SDK (for deployment to Cloud Run)
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* A Google Cloud Project with Cloud Run API enabled.
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## Getting Started (Local Development)
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1. **Clone the repository:**
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```bash
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git clone [repository-url]
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git clone <repository-url> # Replace <repository-url> with your repository URL
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cd flask-simulation-backend
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```
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```
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The backend will be accessible at `http://127.0.0.1:5000`.
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5. **Send simulation requests using `curl` or a frontend application:**
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Example `curl` request with minimal parameters (defaults applied):
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```bash
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curl -X POST -H "Content-Type: application/json" -d '{"algorithm": "FirstFit", "networkType": 1, "bitrate": "bitrate"}' [http://127.0.0.1:5000/run_simulation](http://127.0.0.1:5000/run_simulation)
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```
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## API Endpoints
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Example `curl` request with all parameters specified
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```bash
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### `/run_simulation` (POST)
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This endpoint runs a FlexNetSim simulation based on the parameters provided in the JSON request body.
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**Request Body Parameters:**
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| Parameter | Type | Description | Allowed Values | Default Value | Constraints |
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| :---------------- | :--------------- | :----------------------------------------------------------------------------- | :---------------------------- | :------------ | :-------------------- |
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| `algorithm` | `string` | Routing and spectrum assignment algorithm to use. | `FirstFit`, `ExactFit` | `FirstFit` | |
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| `networkType` | `integer` | Type of optical network. | `1` | `1` | Only `1` (EON) available |
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| `goal_connections`| `integer` | Target number of connection requests for the simulation. | | `100000` | Must be integer > 0 |
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| `confidence` | `number (float)` | Confidence level for the simulation results. | | `0.05` | Must be > 0 |
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| `lambda_param` | `number (float)` | Arrival rate (lambda) of connection requests. | | `1.0` | Must be > 0 |
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| `mu` | `number (float)` | Service rate (mu) of connection requests. | | `10.0` | Must be > 0 |
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| `network` | `string` | Network topology to simulate. | `NSFNet`, `Cost239`, `EuroCore`, `GermanNet`, `UKNet` | `NSFNet` | |
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| `bitrate` | `string` | Type of bitrate allocation. | `fixed-rate`, `flex-rate` | `bitrate` | |
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| `K` | `integer` | Number of paths to compute. | | `3` | |
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**Example `curl` request with minimal parameters (defaults applied):**
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```bash
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curl -X POST -H "Content-Type: application/json" -d '{"algorithm": "FirstFit", "networkType": 1, "bitrate": "bitrate"}' http://127.0.0.1:5000/run_simulation
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```
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**Example `curl`request with all parameters specified:**
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```bash
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curl -X POST -H "Content-Type: application/json" \
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-d '{
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"algorithm": "FirstFit",
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"bitrate": "bitrate" -> (filename in the ./bitrates folder)
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}' \
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http://127.0.0.1:5000/run_simulation
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```
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**Response**:
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- 200 OK: Simulation executed successfully. The response body will be a JSON object with the following structure:
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```JSON
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{
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"output": "string", // Simulation output results
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"error": "string" // Empty string if no errors
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}
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```
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- 400 Bad Request: Indicates an error in the request, such as missing or invalid parameters. The response body will be a JSON object with an `"error"` field describing the issue.
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- 500 Internal Server Error: Indicates a server-side error, either during compilation or simulation execution. The response body will be a JSON object with `"error"` and "details" fields providing more information about the error.
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### `/help` (GET)
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This endpoint provides detailed information about the `/run_simulation` endpoint, including the expected request structure, parameters, allowed values, and response formats.
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**Request**:
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```bash
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curl http://127.0.0.1:5000/help
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```
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## Dockerization
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docker stop fns-api
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```
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## Docs: GCloud Deployment Configuration
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## GCloud Deployment Configuration
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For detailed step-by-step instructions on configuring Google Cloud (GCloud) aspects such as Kubernetes Cluster creation, Artifact Registry, Service Account creation, and IAM policy binding, please refer to the following video tutorial:
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As a prerequisite is mandatory to apply the following steps to the GCloud project for the docker image build and upload to artifacts, and also service account creation and IAM policy binding:
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[GCloud Configuration Video Tutorial](https://www.youtube.com/watch?v=KQUKDiBz3IA)
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This video will guide you through the necessary configurations in the Google Cloud Console to prepare your project for Kubernetes deployments using GitHub Actions.
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This video will guide you through the necessary configurations in the Google Cloud Console to prepare your project for Cloud Run deployments using GitHub Actions.
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**Key Reminders from the Video & for Successful Deployment:**
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* **Keep Track of Docker Image Name, Project ID, and Kubernetes Cluster Name:** Note these down during the video configuration, as you will need them in subsequent steps and for your GitHub Actions workflow.
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* **Keep Track of Docker Image Name, Project ID:** Note these down during the video configuration, as you will need them in subsequent steps and for your GitHub Actions workflow.
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* **Service Account Email:** Ensure you create a Service Account as shown in the video and securely download and store the JSON key file. You'll also need to note the Service Account's email address.
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**Post-Configuration Steps (using `gcloud` and `kubectl`):**
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**Post-Configuration Steps (using `gcloud` and `cloud-run`):**
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1. **Create a Kubernetes Cluster in GCloud:**
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1. Activate necessary apis:
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* Navigate to the Kubernetes Engine section in your Google Cloud Console.
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* Click **Create Cluster**.
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* Choose a cluster name (e.g., `flex-net-sim-cluster`). **Remember this name.**
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* Select a region for your cluster (e.g., `us-central1`).
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* For the purpose of this guide, you can use the default settings for node pools, networking, and other configurations, or adjust them based on your specific needs.
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* Click **Create** to create the cluster. It will take a few minutes for the cluster to be provisioned.
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* `gcloud services enable run.googleapis.com`
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2. **Set IAM Policy Binding (using `gcloud`):**
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2. Create cloud run service:
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* Navigate to the Cloud Run section in your Google Cloud Console.
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* Create a **Service**.
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* Select *Use an inline editor to create a function*.
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* Set a name, in this case *fns-api-cloud-run* will be used.
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* Note down the Endpoint URL, because it will the defaul url for the API.
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* Select the authetification preferences.
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* Create.
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Replace `<YOUR-GOOGLE-PROJECT-ID>` and `<SERVICE_ACCOUNT_EMAIL>` with your actual Google Cloud Project ID and the Service Account Email you noted down.
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3. Update access of service accounts to cloud run resources:
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```bash
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gcloud projects add-iam-policy-binding <YOUR-GOOGLE-PROJECT-ID> --member="serviceAccount:<SERVICE_ACCOUNT_EMAIL>" --role="roles/container.admin"
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gcloud projects add-iam-policy-binding "<YOUR-GOOGLE-PROJECT-ID>" --member="serviceAccount:<SERVICE_ACCOUNT_EMAIL>" --role="roles/run.admin"
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```
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3. **Get Kubernetes Cluster Credentials (using `gcloud`):**
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Replace `<CLUSTER-NAME>` and `<YOUR-GOOGLE-PROJECT-ID>` with your Kubernetes Cluster Name and Google Cloud Project ID. Ensure the region is set to `us-central1`.
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and
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```bash
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gcloud container clusters get-credentials <CLUSTER-NAME> --region us-central1 --project <YOUR-GOOGLE-PROJECT-ID>
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```
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The command will fetch the cluster credentials and configure `kubectl` to use them. You should see output similar to:
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```
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Fetching cluster endpoint and auth data.
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kubeconfig entry generated for <CLUSTER-NAME>.
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```
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gcloud iam service-accounts add-iam-policy-binding "<YOUR_PROJECT_NUMBER>-compute@developer.gserviceaccount.com" --member="serviceAccount:<SERVICE_ACCOUNT_EMAIL>" --role="roles/iam.serviceAccountActor"
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```
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4. **Verify `kubectl` Configuration and Service Deployment (using `kubectl`):**
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4. **Test the Deployed API (using `curl`):**
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After the command is successful, verify your `kubectl` configuration and check for the `fns-api-service`:
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Use the `curl` command with the `ENDPOINT-URL` you obtained from the previous steps to test your deployed API. Replace `YOUR-ENDPOINT-URL` with the actual `ENDPOINT-URL`.
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```bash
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kubectl get service fns-api-service
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```
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If the service is correctly deployed (after your GitHub Actions workflow runs), it should display information about your service, including the `EXTERNAL-IP`.
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curl -X POST -H "Content-Type: application/json" -d '{"algorithm": "FirstFit", "networkType": 1, "bitrate": "bitrate"}' <YOUR-ENDPOINT-URL>/run_simulation
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```
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You should see output similar to this (the `EXTERNAL-IP` will likely be different):
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```
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NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
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fns-api-service LoadBalancer 10.3.xxx.xxx 34.56.1.247 80:8080/TCP 20h
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kubernetes ClusterIP 10.3.xxx.xxx <none> 443/TCP 21h
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```
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5. **Test the Deployed API (using `curl`):**
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Use the `curl` command with the `EXTERNAL-IP` you obtained from the previous step to test your deployed API. Replace `<YOUR-EXTERNAL-IP>` with the actual `EXTERNAL-IP`.
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```bash
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curl -X POST -H "Content-Type: application/json" -d '{"algorithm": "FirstFit", "networkType": 1, "bitrate": "bitrate"}' http://<YOUR-EXTERNAL-IP>/run_simulation
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```
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Remember that depending on the authetification preferences you might need to authetificate to send request to the Endpoint just created.
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**Remember**: These GCloud configurations, along with the repository's `gke-cd.yml` GitHub Actions workflow and correctly configured GitHub secrets, are essential for successful automated deployment of your FlexNetSim-API application to Google Cloud Kubernetes Engine.
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**Remember**: These GCloud configurations, along with the repository's `gke-cd.yml` GitHub Actions workflow and correctly configured GitHub secrets, are essential for successful automated deployment of your FlexNetSim-API application to Google Cloud Run.

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