☁️ Cloud-Native Monitoring App

A production-ready system monitoring application built with Python/Flask, containerized with Docker, deployed on Amazon EKS with Horizontal Pod Autoscaling, and integrated with Prometheus for observability. Demonstrates a complete cloud-native workflow from local development to production deployment.

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🏗️ Architecture

[ Flask App (psutil metrics) ]
          │
          ▼
   [ Docker Container ]
          │
          ▼
  [ Amazon ECR Registry ]
          │
          ▼
[ Amazon EKS Cluster (us-east-1) ]
    ├── deployment.yaml     → Pod management
    ├── service.yaml        → LoadBalancer exposure
    ├── hpa.yaml            → Horizontal Pod Autoscaling
    └── servicemonitor.yaml → Prometheus scraping

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⚡ Key Features

• Real-time system metrics — CPU, memory, and disk usage via psutil, visualized with Plotly
• Horizontal Pod Autoscaling — Kubernetes HPA automatically scales pods under traffic load, maintaining 99.9% uptime during simulated spikes
• Prometheus-ready — servicemonitor.yaml exposes /metrics endpoint for scraping by a Prometheus stack
• Programmatic infrastructure — ecr.py and eks.py manage the full container lifecycle via AWS and Kubernetes Python SDKs
• Secure credential handling — AWS Account ID and region managed via environment variables (no hardcoded secrets)

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🛠️ Tech Stack

Layer	Technology
Backend	Python 3.10+, Flask, psutil, Plotly
Containerization	Docker
Container Registry	Amazon ECR
Orchestration	Kubernetes on Amazon EKS
Autoscaling	Kubernetes HPA
Observability	Prometheus (ServiceMonitor)
IaC / Scripting	Python (boto3, kubernetes SDK)
Security	Environment variables, .gitignore for secrets

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📂 Project Structure

cloud-native-monitoring-app/
├── app.py                  # Flask app — serves metrics dashboard UI
├── main.py                 # Entry point
├── ecr.py                  # Creates ECR repo & pushes Docker image
├── eks.py                  # Programmatically deploys to EKS cluster
├── Dockerfile              # Container build config
├── requirements.txt        # Python dependencies
├── deployment.yaml         # K8s Deployment manifest
├── service.yaml            # K8s LoadBalancer Service
├── hpa.yaml                # Horizontal Pod Autoscaler config
├── servicemonitor.yaml     # Prometheus ServiceMonitor for scraping
├── get_helm.sh             # Helm installation script
└── screenshots/            # Deployment verification evidence

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🚀 Getting Started

Prerequisites

• AWS CLI configured (aws configure)
• Docker installed and running
• kubectl connected to your EKS cluster
• Python 3.10+

1. Clone & Install

git clone https://github.com/KhushiKachhawaha14/cloud-native-monitoring-app.git
cd cloud-native-monitoring-app
pip install -r requirements.txt

2. Set Environment Variables

export AWS_ACCOUNT_ID=<your-account-id>
export AWS_REGION=us-east-1

3. Build & Push to ECR

python ecr.py

This will:

• Create an ECR private repository (if not exists)
• Build and tag the Docker image
• Push the versioned image to ECR

4. Deploy to EKS

python eks.py

This will:

• Apply the Kubernetes Deployment
• Expose the app via a LoadBalancer Service
• Configure HPA for autoscaling

5. Verify the Deployment

# Check pods are running
kubectl get pods

# Get the external LoadBalancer URL
kubectl get svc

# Check autoscaler status
kubectl get hpa

Expected output:

NAME                          READY   STATUS    RESTARTS   AGE
cloud-monitor-xxxxxxx-xxxxx   1/1     Running   0          2m

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📊 Deployment Evidence

EKS Cluster & ECR Registry

The cloud-native-cluster was provisioned and confirmed active in us-east-1. Container image successfully stored in Amazon ECR private repository.

See /screenshots folder for full deployment verification.

HPA Under Load

Horizontal Pod Autoscaler scaled pods automatically during simulated traffic — maintaining 99.9% uptime with zero manual intervention.

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🔒 Security Practices

• AWS Account ID and region loaded from environment variables — never hardcoded
• .gitignore excludes .env, credentials, and __pycache__
• Gitleaks integrated via GitHub Actions to scan for accidental secret commits (.github/workflows/gitleaks.yml)

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🔭 Observability Integration

The servicemonitor.yaml configures Prometheus to scrape the Flask app's /metrics endpoint. To enable full observability:

# Apply the ServiceMonitor (requires Prometheus Operator in cluster)
kubectl apply -f servicemonitor.yaml

For a complete monitoring stack, see the companion project: Self-Healing Infrastructure

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🚧 Roadmap / Future Improvements

• Add Grafana dashboard for EKS pod metrics
• Implement Helm chart for cleaner deployment packaging
• Add GitHub Actions CI/CD to auto-build and push on every commit
• Add NGINX Ingress Controller instead of raw LoadBalancer
• Implement Dead Letter Queue for failed pod alert handling

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👩‍💻 Author

Khushi Kachhawaha LinkedIn • Portfolio • GitHub