https://github.com/budd9442/canvas
Distributed Collaborative Paint Canvas
https://github.com/budd9442/canvas
cloud-computing distributed-systems docker k8s-api kubernetes prometheus-grafana
Last synced: about 1 month ago
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Distributed Collaborative Paint Canvas
- Host: GitHub
- URL: https://github.com/budd9442/canvas
- Owner: budd9442
- Created: 2025-12-25T12:38:30.000Z (6 months ago)
- Default Branch: master
- Last Pushed: 2026-04-10T08:13:42.000Z (2 months ago)
- Last Synced: 2026-04-10T09:29:38.368Z (2 months ago)
- Topics: cloud-computing, distributed-systems, docker, k8s-api, kubernetes, prometheus-grafana
- Language: TypeScript
- Homepage:
- Size: 246 KB
- Stars: 3
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Distributed Collaborative Paint Canvas 🎨
A real-time, distributed collaborative drawing application designed to demonstrate the principles of **Distributed Systems**, **High Availability**, and **GitOps-driven Cloud Orchestration**.
---
## 🏗 Choose Your Architecture
This project evolved from a single-node VPS deployment into a professional, multi-AZ AWS cloud infrastructure. You can deploy it in two ways:
### 1. **AWS Production Deployment **
* **Infrastructure**: AWS EKS (Kubernetes), RDS (PostgreSQL), ElastiCache (Redis), Secrets Manager, ALB.
* **Logic**: Fully automated via Terraform (IaC) and GitHub Actions (CI/CD).
### 2. **Local / VPS Deployment **
* **Infrastructure**: Lightweight `k3s` cluster, Docker Compose, or manual Node.js.
* **Logic**: Standard `kubectl apply` manifests.
* **Location**: Legacy manifests are preserved in the [`k83-vps/`](./k83-vps/) directory.
---
## 🚀 AWS Enterprise Deployment (EKS)
### Prerequisites
* AWS CLI configured with Admin permissions.
* Terraform 1.5+
* kubectl & Helm
### Step 1: Bootstrap the State
Before deploying the main resources, initialize the remote S3 backend and DynamoDB state lock:
```bash
cd terraform/bootstrap
terraform init && terraform apply
```
### Step 2: Provision Infrastructure
Update `terraform/main/provider.tf` with the S3 bucket name from the bootstrap step, then:
```bash
cd terraform/main
terraform init
terraform apply
```
*This will provision a custom VPC, EKS Cluster, RDS Postgres, and ElastiCache Redis (~15-20 mins).*
### Step 3: GitOps Rollout
1. Add your `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` to GitHub Repository Secrets.
2. Push a change to the `master` branch.
3. The [Deployment Workflow](./.github/workflows/deploy.yaml) will automatically build the images, push to ECR, and deploy to EKS.
---
## 🐧 Legacy VPS Deployment (k3s)
If you are deploying to a standard Linux VPS using `k3s`:
1. **Ensure k3s is installed**: `curl -sfL https://get.k3s.io | sh -`
2. **Deploy Manifests**:
```bash
kubectl apply -f k83-vps/
```
3. **Config**: Update the `Ingress` in `k83-vps/ingress.yaml` with your VPS IP or public domain.
---
## 🛠 Tech Stack
| Component | AWS Technology | VPS/Local Technology |
|-----------|----------------|----------------------|
| **Kubernetes** | Amazon EKS (Managed) | k3s (Lightweight) |
| **Database** | Amazon RDS (PostgreSQL) | In-cluster Postgres Pod |
| **Cache** | Amazon ElastiCache (Redis) | In-cluster Redis Pod |
| **Ingress** | AWS Load Balancer (ALB) | Traefik / Nginx |
| **Secrets** | AWS Secrets Manager | K8s Secrets (Base64) |
| **Registry** | Amazon ECR | Docker Hub |
| **IaC** | Terraform | Manual Manifests |
---
## 📉 Stress Testing & HPA
The system is built to breathe. We’ve included a "Bot Army" tester to verify Horizontal Pod Autoscaling (HPA).
1. **Install Tester**:
```bash
cd tester
npm install
```
2. **Run "Starry Night" Attack**:
```bash
# Simulates 250 concurrent bots drawing a Van Gogh painting
CONCURRENCY=250 INTERVAL=10 node flood.js
```
3. **Monitor Scaling**:
```bash
kubectl get hpa paint-backend -w
```
---
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](./LICENSE) file for details.