Merge pull request #5 from Gurram2001/update

Update README.md

Author: Gurram2001

README.md

@@ -1 +1,126 @@
-WebApp using python Flask
+# Complete Guide: Flask WebApp with GitHub Actions, Docker, Azure Deployment & Monitoring
+
+This repository contains a Flask-based web application with CI/CD pipeline configured through GitHub Actions, Docker, and deployment to Azure VM with prometheus, grafana monitoring
+
+## Getting Started
+
+### Clone the Repository
+```bash
+git clone https://github.com/gurram2001/webapp.git
+cd webapp
+```
+
+## CI/CD Configuration
+
+### Secrets to Add in GitHub Repository
+Go to your GitHub repo → Settings → Secrets and Variables → Actions and add:
+
+| Name | Description |
+|------|-------------|
+| DOCKER_USERNAME | Your Docker Hub username |
+| DOCKER_PASSWORD | Your Docker Hub password or token |
+| VM_HOST | Public IP of your Azure VM |
+| VM_USER | SSH username (usually azureuser) |
+| VM_KEY | Your private SSH key |
+
+## Set Up Azure VM
+
+### Create an Azure VM (Ubuntu)
+1. Open port 22 (SSH) and 80 (HTTP) in Network Security Group (NSG)
+2. SSH into VM and install Docker:
+```bash
+sudo apt install docker.io
+sudo usermod -aG docker azureuser
+```
+3. Logout VM and Login again
+4. CHeck with below command
+```bash
+docker run hello-world
+```
+
+## Test the Full Flow
+1. Commit and push code → GitHub Action triggers
+2. Image builds → pushed to Docker Hub
+3. Azure VM pulls latest image → runs container
+4. Open browser: http://<Azure-VM-IP> to see your app
+
+## Monitoring Setup
+
+### Step 1: SSH into your Azure VM
+```bash
+ssh azureuser@<your-azure-vm-ip>
+```
+
+### Step 2: Create a monitoring folder
+```bash
+mkdir ~/monitoring && cd ~/monitoring
+```
+
+### Step 3: Create Prometheus config file
+Create a file named `prometheus.yml`:
+```yaml
+global:
+  scrape_interval: 15s
+scrape_configs:
+  - job_name: 'docker'
+    static_configs:
+      - targets: ['localhost:9323']
+```
+
+### Step 4: Run Prometheus and Grafana in Docker
+```bash
+# Run Prometheus
+docker run -d \
+  -p 9090:9090 \
+  -v ~/monitoring/prometheus.yml:/etc/prometheus/prometheus.yml \
+  --name prometheus \
+  prom/prometheus
+
+# Run Grafana
+docker run -d \
+  -p 3000:3000 \
+  --name=grafana \
+  grafana/grafana
+```
+
+### Step 5: Install Docker Metrics Exporter
+Prometheus needs metrics from Docker – install this exporter:
+```bash
+docker run -d \
+  -p 9323:9323 \
+  -v /var/run/docker.sock:/var/run/docker.sock \
+  --name cadvisor \
+  google/cadvisor:latest
+```
+
+### Step 6: Access Grafana on Browser
+Open: http://<your-azure-vm-ip>:3000
+
+Default login:
+- User: admin
+- Password: admin (you'll be prompted to change)
+
+### Step 7: Connect Prometheus as Grafana Data Source
+In Grafana:
+1. Go to Settings → Data Sources → Add Prometheus
+2. URL: http://localhost:9090
+3. Click Save & Test
+
+### Step 8: Import a Dashboard
+1. Go to + → Import
+2. Paste Dashboard ID: 193 (Docker metrics)
+3. Click Load → Select Prometheus as data source → Import
+
+## Notes
+
+### Understanding Prometheus Configuration
+- **prometheus.yml**: This configuration file tells Prometheus what to monitor (targets) and how often (scrape interval)
+  - The `scrape_interval` defines how frequently Prometheus collects metrics (15s = every 15 seconds)
+  - The `scrape_configs` section defines what services to monitor and where to find them
+  - The `targets` field specifies the host:port where metrics can be collected
+
+### About Exporters
+- Exporters are components that collect and expose metrics from various services in a format Prometheus can understand
+- **cAdvisor** (Container Advisor) is an exporter that collects container metrics from Docker
+- The exporter exposes Docker metrics on port 9323, which Prometheus then scrapes based on the configuration
+