VPS Monitoring Setup with Prometheus and Grafana

Why Monitor Your VPS

When your website or application slows down or crashes, the first question is: "What happened?" Without monitoring, you're flying blind — forced to SSH in and run top or df -h manually, with no historical context to understand what led up to the problem.

Prometheus + Grafana is the most widely adopted self-hosted monitoring stack in production environments. It installs on any VPS for free and gives you deeper visibility than expensive SaaS monitoring tools.

Prometheus + Grafana Architecture

Before installing, understand the components:

• Node Exporter — runs on the monitored VPS, exposes OS metrics via HTTP on port 9100
• Prometheus — scrapes metrics from Node Exporter every 15 seconds and stores them in its time-series database
• Grafana — connects to Prometheus as a data source and renders metrics as interactive dashboards
• Alertmanager (optional) — receives alerts from Prometheus and routes them to Email, Slack, or webhooks

Installing Prometheus

Download and install Prometheus on Ubuntu 22.04:

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

# Create directories
sudo mkdir /etc/prometheus /var/lib/prometheus

# Download Prometheus (check latest version at github.com/prometheus/prometheus)
PROM_VER="2.53.0"
wget https://github.com/prometheus/prometheus/releases/download/v${PROM_VER}/prometheus-${PROM_VER}.linux-amd64.tar.gz
tar -xzf prometheus-${PROM_VER}.linux-amd64.tar.gz
cd prometheus-${PROM_VER}.linux-amd64/

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

# Copy config files
sudo cp -r consoles/ /etc/prometheus/
sudo cp -r console_libraries/ /etc/prometheus/
sudo chown -R prometheus:prometheus /etc/prometheus /var/lib/prometheus

Create the initial config file

sudo nano /etc/prometheus/prometheus.yml

global:
  scrape_interval: 15s
  evaluation_interval: 15s

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

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

Create a systemd service

sudo nano /etc/systemd/system/prometheus.service

[Unit]
Description=Prometheus
Wants=network-online.target
After=network-online.target

[Service]
User=prometheus
Group=prometheus
Type=simple
ExecStart=/usr/local/bin/prometheus \
  --config.file /etc/prometheus/prometheus.yml \
  --storage.tsdb.path /var/lib/prometheus/ \
  --web.console.templates=/etc/prometheus/consoles \
  --web.console.libraries=/etc/prometheus/console_libraries \
  --storage.tsdb.retention.time=30d

[Install]
WantedBy=multi-user.target

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

Installing Node Exporter

Node Exporter collects OS-level metrics — CPU, RAM, Disk, Network:

NODE_VER="1.8.1"
wget https://github.com/prometheus/node_exporter/releases/download/v${NODE_VER}/node_exporter-${NODE_VER}.linux-amd64.tar.gz
tar -xzf node_exporter-${NODE_VER}.linux-amd64.tar.gz
sudo cp node_exporter-${NODE_VER}.linux-amd64/node_exporter /usr/local/bin/

sudo useradd --no-create-home --shell /bin/false node_exporter

sudo nano /etc/systemd/system/node_exporter.service

[Unit]
Description=Node Exporter
Wants=network-online.target
After=network-online.target

[Service]
User=node_exporter
Group=node_exporter
Type=simple
ExecStart=/usr/local/bin/node_exporter

[Install]
WantedBy=multi-user.target

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

Verify Node Exporter is running: curl http://localhost:9100/metrics | head -20

Configuring Prometheus Scrape Jobs

The prometheus.yml config above already targets localhost:9100. Verify Node Exporter is being scraped by visiting the Prometheus UI:

Try these example queries in the Prometheus UI Expression box:

# CPU usage (%)
100 - (avg by(instance)(rate(node_cpu_seconds_total{mode="idle"}[5m])) * 100)

# RAM used (bytes)
node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes

# Disk usage (%)
(node_filesystem_size_bytes - node_filesystem_free_bytes) / node_filesystem_size_bytes * 100

Installing Grafana

Grafana can be installed from the official apt repository:

sudo apt-get install -y apt-transport-https software-properties-common wget
wget -q -O - https://apt.grafana.com/gpg.key | gpg --dearmor | sudo tee /usr/share/keyrings/grafana.gpg > /dev/null
echo "deb [signed-by=/usr/share/keyrings/grafana.gpg] https://apt.grafana.com stable main" | sudo tee /etc/apt/sources.list.d/grafana.list

sudo apt-get update
sudo apt-get install -y grafana

sudo systemctl daemon-reload
sudo systemctl enable grafana-server
sudo systemctl start grafana-server

Open http://YOUR_VPS_IP:3000 in your browser → log in with admin / admin → you'll be prompted to change the password immediately.

Creating Your First Dashboard

Connect Prometheus as a Grafana data source:

1. In Grafana UI → Connections → Data sources → Add data source → select Prometheus
2. URL: http://localhost:9090 → Save & test → should show "Data source is working"
3. Import a ready-made dashboard → Dashboards → Import → enter ID 1860 → Load → select your Prometheus data source → Import

Setting Up CPU/RAM Alerts

Add alert rules to Prometheus to trigger notifications when thresholds are exceeded:

sudo nano /etc/prometheus/alert.rules.yml

groups:
- name: node_alerts
  rules:
  - alert: HighCPU
    expr: 100 - (avg by(instance)(rate(node_cpu_seconds_total{mode="idle"}[5m])) * 100) > 85
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "High CPU {{ $value }}%"
      description: "Instance {{ $labels.instance }} CPU usage above 85% for 5 minutes"

  - alert: LowMemory
    expr: (node_memory_MemAvailable_bytes / node_memory_MemTotal_bytes) * 100 < 15
    for: 5m
    labels:
      severity: critical
    annotations:
      summary: "Low RAM {{ $value }}% available"
      description: "Instance {{ $labels.instance }} has less than 15% available RAM"

  - alert: DiskAlmostFull
    expr: (node_filesystem_size_bytes - node_filesystem_free_bytes) / node_filesystem_size_bytes * 100 > 85
    for: 10m
    labels:
      severity: warning
    annotations:
      summary: "Disk {{ $value }}% used"
      description: "Disk on {{ $labels.instance }} ({{ $labels.mountpoint }}) is {{ $value }}% full"

Add the rule file to prometheus.yml:

rule_files:
  - "/etc/prometheus/alert.rules.yml"

sudo systemctl reload prometheus

Security — Firewall and Basic Auth

By default, Prometheus (9090) and Node Exporter (9100) are accessible from any IP. Lock them down:

# Block external access to Prometheus and Node Exporter
sudo ufw deny 9090
sudo ufw deny 9100
# Or allow only your own IP
sudo ufw allow from YOUR_OFFICE_IP to any port 9090

Grafana authentication settings

sudo nano /etc/grafana/grafana.ini

[auth.anonymous]
enabled = false

[security]
admin_password = YOUR_STRONG_PASSWORD

Summary

You now have a complete self-hosted monitoring stack. Here's what was set up:

• Prometheus installed as the time-series metrics database, scraping every 15 seconds
• Node Exporter exposing OS metrics (CPU, RAM, Disk, Network) on port 9100
• Grafana connected to Prometheus with Dashboard 1860 ready to use
• Alert rules for CPU >85%, RAM <15% free, and Disk >85% full
• Firewall rules blocking direct external access to Prometheus and Node Exporter

With this setup, you have the historical data to make informed scaling decisions — no more guessing when to upgrade. If you need a VPS with enough resources to run Prometheus + Grafana alongside your application, see AsiaGB VPS packages.