Setting Up Prometheus and Grafana for VPS Monitoring: A Step-by-Step Guide

If you run a VPS without monitoring, you’re flying blind. Resource leaks, traffic spikes, and cron jobs gone wrong can silently degrade performance until your site goes down. Prometheus and Grafana together provide battle-tested, open-source monitoring that gives you real-time visibility into CPU, RAM, disk, network, and application metrics. Here’s how to set them up on a Ubuntu 22.04/24.04 VPS in under 30 minutes.

Prerequisites

• A Ubuntu 22.04 or 24.04 VPS with at least 1 GB RAM (2 GB recommended if your app also runs on the same server)
• Root or sudo access
• Port 9090 (Prometheus) and 3000 (Grafana) open in your firewall — but restrict to your IP or use a reverse proxy with auth

If you don’t have a VPS yet, check affordable VPS hosting options that provide the resources you need for both your application and monitoring stack.

Step 1: Install Prometheus

Prometheus is a time-series database that scrapes and stores metrics from configured targets. Install from the official release (not apt — the repo version is often outdated):

# Create prometheus user
sudo useradd --no-create-home --shell /bin/false prometheus

# Download latest Prometheus (check https://prometheus.io/download/ for latest)
cd /tmp
wget https://github.com/prometheus/prometheus/releases/download/v2.53.1/prometheus-2.53.1.linux-amd64.tar.gz
tar xvf prometheus-2.53.1.linux-amd64.tar.gz
cd prometheus-2.53.1.linux-amd64

# Copy binaries
sudo cp prometheus promtool /usr/local/bin/
sudo chown prometheus:prometheus /usr/local/bin/prometheus /usr/local/bin/promtool

# Create directories
sudo mkdir -p /etc/prometheus /var/lib/prometheus
sudo cp consoles/ console_libraries/ /etc/prometheus/ -r
sudo chown -R prometheus:prometheus /etc/prometheus /var/lib/prometheus

Step 2: Configure Prometheus

Create /etc/prometheus/prometheus.yml:

global:
  scrape_interval: 15s
  evaluation_interval: 15s

scrape_configs:
  - job_name: 'prometheus'
    static_configs:
      - targets: ['localhost:9090']

  - job_name: 'node_exporter'
    static_configs:
      - targets: ['localhost:9100']

Create a systemd service at /etc/systemd/system/prometheus.service and start it.

sudo systemctl daemon-reload
sudo systemctl enable prometheus
sudo systemctl start prometheus
sudo systemctl status prometheus

Step 3: Install Node Exporter

Node Exporter exposes OS-level metrics (CPU, memory, disk, network). Download from the official releases, copy to /usr/local/bin, and run as a systemd service listening on port 9100.

# Download and install
cd /tmp
wget https://github.com/prometheus/node_exporter/releases/download/v1.8.2/node_exporter-1.8.2.linux-amd64.tar.gz
tar xvf node_exporter-1.8.2.linux-amd64.tar.gz
sudo cp node_exporter-1.8.2.linux-amd64/node_exporter /usr/local/bin/
sudo useradd --no-create-home --shell /bin/false node_exporter

# Start
sudo systemctl daemon-reload
sudo systemctl enable node_exporter
sudo systemctl start node_exporter

Verify: curl http://localhost:9100/metrics | head -20

Step 4: Install Grafana

sudo apt-get update
sudo apt-get install -y software-properties-common
sudo add-apt-repository "deb https://packages.grafana.com/oss/deb stable main"
wget -q -O - https://packages.grafana.com/gpg.key | sudo apt-key add -
sudo apt-get update
sudo apt-get install -y grafana
sudo systemctl enable grafana-server
sudo systemctl start grafana-server

Access Grafana at http://your-vps-ip:3000. Default login: admin / admin (change immediately).

Step 5: Connect Grafana to Prometheus

1. Go to Connections > Add new connection in Grafana
2. Search for “Prometheus” and click it
3. Click “Create a Prometheus data source”
4. Set URL to http://localhost:9090
5. Click “Save & Test”

Step 6: Import a Dashboard

1. Go to Dashboards > Import
2. Enter dashboard ID 1860 (Node Exporter Full) and click “Load”
3. Select your Prometheus data source and click “Import”

You’ll immediately see CPU utilization per core, memory breakdown, disk I/O, network traffic, system load, and uptime — all populated from your Node Exporter metrics.

Step 7: Set Up Alerts

In Grafana, go to Alerting > Contact points and add email, Slack, or Telegram. Create alert rules for common failure conditions:

• High CPU: Alert when CPU usage exceeds 90% for 5 minutes
• Low disk: Alert when disk usage drops below 10% free
• High memory: Alert when memory usage exceeds 90% for 5 minutes
• Instance down: Alert when a target is unreachable (up == 0)

Resource Usage of the Monitoring Stack

Component	RAM	CPU	Disk (30d retention)
Prometheus	100-200 MB	1-5% of 1 core	~5-15 GB
Node Exporter	15-25 MB	<1% of 1 core	0 GB
Grafana	80-150 MB	1-3% of 1 core	~1 GB
Total	~200-375 MB	~2-9%	~6-16 GB

This stack fits comfortably alongside your application on a 2 GB VPS. On a 1 GB VPS, reduce Prometheus retention to 7-14 days.

Next Steps: Advanced Monitoring

• Add cAdvisor to monitor Docker containers
• Add MySQL Exporter for database query performance
• Add Blackbox Exporter for external endpoint uptime checks
• Set up Grafana Loki for centralized log aggregation

With Prometheus and Grafana in place, you’ll catch resource exhaustion before downtime occurs, identify regressions instantly, and make data-driven upgrade decisions. For VPS plans with sufficient resources for both your application and a full observability stack, check recommended VPS configurations.