How to Self-Host Glances 2026

TL;DR

Glances (LGPL 3.0, ~26K GitHub stars, Python) is a cross-platform real-time system monitoring tool — like an enhanced htop with a web UI. It shows CPU, RAM, disk I/O, network, processes, Docker containers, sensors, and more in a single dashboard. Run it on any server and access via browser. Unlike Netdata (~72K stars, heavier), Glances is a single Python process with minimal dependencies and no daemon. Perfect for quick server health checks without a full monitoring stack.

Key Takeaways

Glances: LGPL 3.0, ~26K stars, Python — htop on the web, single process, minimal
Web UI: Browser dashboard with auto-refresh, accessible from any device
REST API: Query any metric programmatically
Prometheus export: Feed Netdata/Grafana with Glances metrics
Docker monitoring: Per-container CPU, RAM, and network stats
Plugins: 60+ built-in plugins — disks, network, GPU, sensors, processes

Glances vs Netdata vs htop

Feature	Glances	Netdata	htop
License	LGPL 3.0	GPL 3.0	GPL 2.0
GitHub Stars	~26K	~72K	~7K
Web UI	Yes	Yes (rich)	No
Setup	pip or docker	Docker	apt/brew
RAM	~50MB	~100MB	~5MB
Docker monitoring	Yes	Yes	No
Alerts	Basic	700+ rules	No
Prometheus export	Yes	Yes	No
Multi-host	Via client-server	Parent-child	No
History/retention	No	Yes (dbengine)	No

Part 1: Docker Setup

# docker-compose.yml
services:
  glances:
    image: nicolargo/glances:latest-full    # -full includes all plugins
    container_name: glances
    restart: unless-stopped
    ports:
      - "61208:61208"     # Web UI
      - "61209:61209"     # API
    pid: host
    network_mode: host    # Required for full network monitoring
    volumes:
      - /var/run/docker.sock:/var/run/docker.sock:ro
      - /etc/os-release:/etc/os-release:ro
      - glances_config:/glances/conf
    environment:
      GLANCES_OPT: "-w"   # Web server mode
    privileged: true       # For sensor access

volumes:
  glances_config:

docker compose up -d

Visit http://your-server:61208 — the dashboard loads immediately.

Part 2: Without Docker (Direct Install)

For minimal overhead directly on the host:

# Install with full extras:
pip install glances[all]

# Or just the basics:
pip install glances

# Run in web server mode:
glances -w --port 61208

# Or as a systemd service:
sudo tee /etc/systemd/system/glances.service << 'EOF'
[Unit]
Description=Glances monitoring daemon
After=network.target

[Service]
ExecStart=/usr/local/bin/glances -w --port 61208 --config /etc/glances/glances.conf
Restart=on-abort
User=root

[Install]
WantedBy=multi-user.target
EOF

sudo systemctl enable --now glances

Part 3: HTTPS with Caddy

monitor.yourdomain.com {
    basicauth {
        admin $2a$14$hash_here    # caddy hash-password
    }
    reverse_proxy localhost:61208
}

Glances has no built-in auth — protect with Caddy basicauth or leave open on LAN.

Part 4: What Glances Shows

System overview panel:

CPU: 12.3% (8 cores)    Load: 0.5, 0.3, 0.2
RAM: 3.2G / 16G (20%)   Swap: 0 / 8G (0%)

Per-process table (sortable by CPU, RAM, name):

PID   USER    CPU%  MEM%  NAME
1234  www     8.2   2.1   nginx
5678  redis   1.1   0.8   redis-server

Docker containers (auto-detected):

Container        CPU%   MEM      Status
nextcloud        2.1    512M     running
postgres         0.5    256M     running
nginx            0.2    64M      running

Disk I/O:

/dev/sda    Read: 15 MB/s    Write: 8 MB/s

Network interfaces:

eth0   Rx: 12 Mb/s   Tx: 4 Mb/s   Cx: 142

Part 5: Configuration

Create a config file for custom thresholds and display:

# /glances/conf/glances.conf

[global]
refresh=2        # Refresh every 2 seconds
check_update=false

[cpu]
user_careful=50
user_warning=70
user_critical=90

[memory]
careful=50
warning=70
critical=90

[filesystem]
careful=50
warning=70
critical=90

[docker]
# Show Docker stats
all=false        # Only running containers

[processlist]
cpu_careful=50
cpu_warning=70
cpu_critical=90
mem_careful=20
mem_warning=50
mem_critical=70
max_processes=20

[alert]
min_duration=6   # Alert must persist 6 seconds before notifying

Part 6: REST API

Query any metric programmatically:

# Get all stats as JSON:
curl http://your-server:61208/api/3/all | jq

# Specific metrics:
curl http://your-server:61208/api/3/cpu
curl http://your-server:61208/api/3/mem
curl http://your-server:61208/api/3/diskio
curl http://your-server:61208/api/3/network
curl http://your-server:61208/api/3/docker
curl http://your-server:61208/api/3/processlist

# CPU usage:
curl -s http://your-server:61208/api/3/cpu | jq '.total'

# Memory free:
curl -s http://your-server:61208/api/3/mem | jq '.free'

# Top 5 processes by CPU:
curl -s http://your-server:61208/api/3/processlist \
  | jq 'sort_by(-.cpu_percent) | .[0:5] | .[] | {name, cpu_percent, memory_percent}'

Part 7: Prometheus Export

Feed metrics to Grafana:

# Add to docker-compose.yml:
environment:
  GLANCES_OPT: "-w --export prometheus"

Or run the Prometheus exporter separately:

glances -w --export prometheus --port 61208

Then in Prometheus scrape_configs:

- job_name: "glances"
  static_configs:
    - targets: ["server.yourdomain.com:61208"]
  metrics_path: /api/3/all
  params:
    format: [prometheus]

Part 8: Multi-Host (Client-Server Mode)

Monitor multiple servers from one Glances instance:

On each server being monitored:

glances -s --port 61209   # Server mode (XML-RPC API)

Or in Docker:

environment:
  GLANCES_OPT: "-s --port 61209"

On the monitoring client:

glances -c server1.yourdomain.com --port 61209
glances -c server2.yourdomain.com --port 61209

Part 9: Alerts

Basic email alerts when thresholds are exceeded:

# glances.conf
[alert]
min_duration=6

[smtp]
host=smtp.yourdomain.com
port=587
username=noreply@yourdomain.com
password=your-smtp-password
to=ops@yourdomain.com
from=glances@yourdomain.com
ssl=true

For more sophisticated alerting, pipe Glances metrics to Prometheus + Alertmanager.

Maintenance

# Update Glances:
docker compose pull
docker compose up -d

# Logs:
docker compose logs -f glances

# Check current metrics quickly (CLI mode):
docker exec glances glances --stdout cpu.total,mem.percent,load

# Run in terminal mode on host (classic htop-style):
glances

Why Self-Host Glances?

The case for self-hosting Glances comes down to three practical factors: data ownership, cost at scale, and operational control.

Data ownership is the fundamental argument. When you use a SaaS version of any tool, your data lives on someone else's infrastructure subject to their terms of service, their security practices, and their business continuity. If the vendor raises prices, gets acquired, changes API limits, or shuts down, you're left scrambling. Self-hosting Glances means your data and configuration stay on infrastructure you control — whether that's a VPS, a bare metal server, or a home lab.

Cost at scale matters once you move beyond individual use. Most SaaS equivalents charge per user or per data volume. A self-hosted instance on a $10-20/month VPS typically costs less than per-user SaaS pricing for teams of five or more — and the cost doesn't scale linearly with usage. One well-configured server handles dozens of users for a flat monthly fee.

Operational control is the third factor. The Docker Compose configuration above exposes every setting that commercial equivalents often hide behind enterprise plans: custom networking, environment variables, storage backends, and authentication integrations. You decide when to update, how to configure backups, and what access controls to apply.

The honest tradeoff: you're responsible for updates, backups, and availability. For teams running any production workloads, this is familiar territory. For individuals, the learning curve is real but the tooling (Docker, Caddy, automated backups) is well-documented and widely supported.

Server Requirements and Sizing

Before deploying Glances, assess your server capacity against expected workload.

Minimum viable setup: A 1 vCPU, 1GB RAM VPS with 20GB SSD is sufficient for personal use or small teams. Most consumer VPS providers — Hetzner, DigitalOcean, Linode, Vultr — offer machines in this range for $5-10/month. Hetzner offers excellent price-to-performance for European and US regions.

Recommended production setup: 2 vCPUs with 4GB RAM and 40GB SSD handles most medium deployments without resource contention. This gives Glances headroom for background tasks, caching, and concurrent users while leaving capacity for other services on the same host.

Storage planning: The Docker volumes in this docker-compose.yml store all persistent Glances data. Estimate your storage growth rate early — for data-intensive tools, budget for 3-5x your initial estimate. Hetzner Cloud and Vultr both support online volume resizing without stopping your instance.

Operating system: Any modern 64-bit Linux distribution works. Ubuntu 22.04 LTS and Debian 12 are the most commonly tested configurations. Ensure Docker Engine 24.0+ and Docker Compose v2 are installed — verify with docker --version and docker compose version. Avoid Docker Desktop on production Linux servers; it adds virtualization overhead and behaves differently from Docker Engine in ways that cause subtle networking issues.

Network: Only ports 80 and 443 need to be publicly accessible when running behind a reverse proxy. Internal service ports should be bound to localhost only. A minimal UFW firewall that blocks all inbound traffic except SSH, HTTP, and HTTPS is the single most effective security measure for a self-hosted server.

Backup and Disaster Recovery

Running Glances without a tested backup strategy is an unacceptable availability risk. Docker volumes are not automatically backed up — if you delete a volume or the host fails, data is gone with no recovery path.

What to back up: The named Docker volumes containing Glances's data (database files, user uploads, application state), your docker-compose.yml and any customized configuration files, and .env files containing secrets.

Backup approach: For simple setups, stop the container, archive the volume contents, then restart. For production environments where stopping causes disruption, use filesystem snapshots or database dump commands (PostgreSQL pg_dump, SQLite .backup, MySQL mysqldump) that produce consistent backups without downtime.

For a complete automated backup workflow that ships snapshots to S3-compatible object storage, see the Restic + Rclone backup guide. Restic handles deduplication and encryption; Rclone handles multi-destination uploads. The same setup works for any Docker volume.

Backup cadence: Daily backups to remote storage are a reasonable baseline for actively used tools. Use a 30-day retention window minimum — long enough to recover from mistakes discovered weeks later. For critical data, extend to 90 days and use a secondary destination.

Restore testing: A backup that has never been restored is a backup you cannot trust. Once a month, restore your Glances backup to a separate Docker Compose stack on different ports and verify the data is intact. This catches silent backup failures, script errors, and volume permission issues before they matter in a real recovery.

Security Hardening

Self-hosting means you are responsible for Glances's security posture. The Docker Compose setup provides a functional base; production deployments need additional hardening.

Always use a reverse proxy: Never expose Glances's internal port directly to the internet. The docker-compose.yml binds to localhost; Caddy or Nginx provides HTTPS termination. Direct HTTP access transmits credentials in plaintext. A reverse proxy also centralizes TLS management, rate limiting, and access logging.

Strong credentials: Change default passwords immediately after first login. For secrets in docker-compose environment variables, generate random values with openssl rand -base64 32 rather than reusing existing passwords.

Firewall configuration:

ufw default deny incoming
ufw allow 22/tcp
ufw allow 80/tcp
ufw allow 443/tcp
ufw enable

Internal service ports (databases, admin panels, internal APIs) should only be reachable from localhost or the Docker network, never directly from the internet.

Network isolation: Docker Compose named networks keep Glances's services isolated from other containers on the same host. Database containers should not share networks with containers that don't need direct database access.

VPN access for sensitive services: For internal-only tools, restricting access to a VPN adds a strong second layer. Headscale is an open source Tailscale control server that puts your self-hosted stack behind a WireGuard mesh, eliminating public internet exposure for internal tools.

Update discipline: Subscribe to Glances's GitHub releases page to receive security advisory notifications. Schedule a monthly maintenance window to pull updated images. Running outdated container images is the most common cause of self-hosted service compromises.

Troubleshooting Common Issues

Container exits immediately or won't start

Check logs first — they almost always explain the failure:

docker compose logs -f glances

Common causes: a missing required environment variable, a port already in use, or a volume permission error. Port conflicts appear as bind: address already in use. Find the conflicting process with ss -tlpn | grep PORT and either stop it or change Glances's port mapping in docker-compose.yml.

Cannot reach the web interface

Work through this checklist:

Confirm the container is running: docker compose ps
Test locally on the server: curl -I http://localhost:PORT
If local access works but external doesn't, check your firewall: ufw status
If using a reverse proxy, verify it's running and the config is valid: caddy validate --config /etc/caddy/Caddyfile

Permission errors on volume mounts

Some containers run as a non-root user. If the Docker volume is owned by root, the container process cannot write to it. Find the volume's host path with docker volume inspect VOLUME_NAME, check the tool's documentation for its expected UID, and apply correct ownership:

chown -R 1000:1000 /var/lib/docker/volumes/your_volume/_data

High resource usage over time

Memory or CPU growing continuously usually indicates unconfigured log rotation, an unbound cache, or accumulated data needing pruning. Check current usage with docker stats glances. Add resource limits in docker-compose.yml to prevent one container from starving others. For ongoing visibility into resource trends, deploy Prometheus + Grafana or Netdata.

Data disappears after container restart

Data stored in the container's writable layer — rather than a named volume — is lost when the container is removed or recreated. This happens when the volume mount path in docker-compose.yml doesn't match where the application writes data. Verify mount paths against the tool's documentation and correct the mapping. Named volumes persist across container removal; only docker compose down -v deletes them.

Keeping Glances Updated

Glances follows a regular release cadence. Staying current matters for security patches and compatibility. The update process with Docker Compose is straightforward:

docker compose pull          # Download updated images
docker compose up -d         # Restart with new images
docker image prune -f        # Remove old image layers (optional)

Read the changelog before major version updates. Some releases include database migrations or breaking configuration changes. For major version bumps, test in a staging environment first — run a copy of the service on different ports with the same volume data to validate the migration before touching production.

Version pinning: For stability, pin to a specific image tag in docker-compose.yml instead of latest. Update deliberately after reviewing the changelog. This trades automatic patch delivery for predictable behavior — the right call for business-critical services.

Post-update verification: After updating, confirm Glances is functioning correctly. Most services expose a /health endpoint that returns HTTP 200 — curl it from the server or monitor it with your uptime tool.

See all open source monitoring and observability tools at OSSAlt.com/categories/monitoring.

The SaaS-to-Self-Hosted Migration Guide (Free PDF)