🖥️ Docker Monitoring Stack (Prometheus + Grafana + Node Exporter)

This repository contains a simple Docker Compose setup for monitoring your host machine using Prometheus, Node Exporter, and Grafana.

📌 Services

🔹 Prometheus

• Collects metrics from Node Exporter and other sources.
• Exposed on port 9090 → http://localhost:9090
• Configured with prometheus.yml.

🔹 Node Exporter

• Exports host system metrics (CPU, memory, disk, network, etc.).
• Exposed on port 9100 → http://localhost:9100/metrics
• Prometheus scrapes metrics from here.

🔹 Grafana

• Visualization layer for Prometheus data.
• Exposed on port 3000 → http://localhost:3000
• Default credentials:
  • User: admin
  • Password: supersecret (can be changed in docker-compose.yml)

🔹 Network

• All services run on a dedicated Docker bridge network called monitoring.

gh repo clone sadikemreduzgun/SimmerLiq-Deployment-Sides
cd SimmerLiq-Deployment-Sides
cd monitoring

Give Grafana’s container user (UID 472) permission to use the grafana folder for preventing Grafana container error:

sudo chown -R 472:472 grafana

for listening all interfaces:

docker-compose up -d

for listening just localhost,

docker-compose up -f docker-compose.localhost.yml -d

Check running containers:

docker ps

⚙️ Notes

• This stack only monitors the host machine where Docker Compose is running.
• If you want to monitor multiple nodes, you’ll need to deploy Node Exporter on each node and configure Prometheus to scrape them by going into monitoring/prometheus and configuring prometheus.yml to scrape node exporters.
• Persistent Grafana data is stored in the ./grafana folder.

✨ Voilà! Now you can collect Node Exporter metrics from your machine and see what’s really happening under the hood.

• This project is running on a production node to monitor system performance. It helps track system load during:
• Artificial load tests on queues
• Heavy backend processes
• Running microservices

🔮 Coming soon: deeper insights like container-level monitoring and more advanced dashboards.