The Tool Desk
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The commands below use an upstream tarball installation, which gives you the release published by the Prometheus Authors rather than whatever version a Linux distribution repository happens to package. You can begin with a manually started process for a quick test, then create a restricted systemd service for reliable operation.
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What Prometheus does on a VPS
Prometheus is a monitoring server. It periodically scrapes HTTP endpoints that expose metrics, stores the resulting time series in its local time-series database, and lets you query those series in its expression browser. It is not an agent that passively receives every log line, and it does not automatically discover every process on a server. You define the endpoints to scrape in prometheus.yml.
For a single Linux VPS, the useful first target is the Prometheus process itself. The second is Node Exporter, a separate static binary that exposes operating-system metrics such as CPU time and available filesystem space. The Prometheus Authors describe Node Exporter as “a single static binary that you can install via tarball.”
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The default/example scrape interval used in the official getting-started and Node Exporter guides is 15 seconds. That is frequent enough for normal host visibility without creating unnecessary scrape traffic on a small server. You can change it later after considering CPU, storage, and the number of targets.
Check the VPS before installing
Confirm architecture and operating system
Download an archive built for the VPS architecture. Run:
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cat /etc/os-releaseCommon results include x86_64 for 64-bit Intel/AMD machines and aarch64 for 64-bit ARM machines. Select the corresponding Linux build on the official Prometheus downloads page. Do the same for Node Exporter; using a binary for the wrong architecture produces an “exec format error” or a process that cannot start.
Plan users, directories, and access
Use a dedicated unprivileged account for each service. Prometheus needs to write its time-series database, while Node Exporter normally only reads kernel and system information. Create persistent directories before starting a service so a restart does not place data in an unexpected working directory:
sudo useradd --system --no-create-home --shell /usr/sbin/nologin prometheus
sudo useradd --system --no-create-home --shell /usr/sbin/nologin node_exporter
sudo mkdir -p /etc/prometheus /var/lib/prometheus
sudo chown -R prometheus:prometheus /etc/prometheus /var/lib/prometheusIf an account already exists, the useradd commands will report that fact; do not create a second account with a different name unless you also update the service files and ownership.
Decide how the web interfaces will be reached
Do not expose monitoring and configuration interfaces broadly on a public VPS. The Prometheus security guidance assumes that only trusted users can change command-line arguments, configuration files, and rule files. Decide whether you will:
- bind Prometheus to the loopback address and reach it through an authenticated reverse proxy or an SSH tunnel;
- allow the web port only from a private network or your administration IP range; or
- place the VPS behind a network firewall that blocks unsolicited Internet access.
Node Exporter should likewise be reachable by Prometheus, not by every Internet host. A firewall rule that permits the exporter only from the Prometheus machine is usually the narrowest choice.
Download and install Prometheus from the upstream archive
1. Obtain and extract the release
Open the official Prometheus downloads page, choose the current Linux archive for the architecture reported by uname -m, and download it to a temporary directory. The exact filename changes with each release, so do not hard-code an old version in a permanent script. Then extract and enter the directory:
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tar -xzf prometheus-*.tar.gz
cd prometheus-*The extracted directory contains the Prometheus server binary, promtool, a sample prometheus.yml, and console assets. Install the two executables in a directory on the system path:
sudo install -m 0755 prometheus /usr/local/bin/prometheus
sudo install -m 0755 promtool /usr/local/bin/promtoolKeep the extracted archive until you have confirmed the new binaries work. It is also useful as a rollback copy, but do not run two Prometheus versions against the same data directory at the same time.
2. Create the initial YAML configuration
Write /etc/prometheus/prometheus.yml with a global interval and a self-scrape job:
global:
scrape_interval: 15s
scrape_configs:
- job_name: prometheus
static_configs:
- targets: ['localhost:9090']YAML indentation is significant. scrape_configs must be at the same indentation level as global, and each list item begins with a hyphen. A tab character can make the file invalid; use spaces.
Validate the file before starting the server:
promtool check config /etc/prometheus/prometheus.ymlA successful check reports that the configuration is valid. If it fails, fix the line and indentation identified in the error rather than starting Prometheus with a partially understood configuration.
3. Start Prometheus manually for the first test
Run the server from a shell to see startup messages directly:
prometheus
--config.file=/etc/prometheus/prometheus.yml
--storage.tsdb.path=/var/lib/prometheusThe --storage.tsdb.path flag makes the data location explicit. Prometheus stores its time-series database there unless another startup flag changes it. Keep this process in the foreground while testing. Stop it with Ctrl+C after you have confirmed that the configuration and web interface work.
Run Prometheus as a systemd service
A systemd unit starts Prometheus after boot, restarts it if it exits unexpectedly, and gives you a consistent place to inspect logs. Create /etc/systemd/system/prometheus.service:
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[Unit]
Description=Prometheus monitoring server
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
Restart=on-failure
[Install]
WantedBy=multi-user.targetApply the unit and start it:
sudo systemctl daemon-reload
sudo systemctl enable --now prometheus
sudo systemctl status prometheus
sudo journalctl -u prometheus -eIf the service cannot read the configuration or data directory, inspect ownership and permissions. The service account must be able to read the YAML file and write the database directory. If the port is already occupied, identify the conflicting process before changing Prometheus settings.
Install Node Exporter for Linux host metrics
1. Download the matching Node Exporter archive
Choose the Node Exporter release for the same Linux architecture on the official downloads page. Extract it and install the binary:
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cd node_exporter-*
sudo install -m 0755 node_exporter /usr/local/bin/node_exporterNode Exporter is intentionally separate from Prometheus. Updating or restarting the exporter does not replace the Prometheus server, and the exporter does not need a YAML scrape configuration of its own for the basic host-metrics use case.
2. Start and test the exporter
Create /etc/systemd/system/node_exporter.service:
[Unit]
Description=Prometheus 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
Restart=on-failure
[Install]
WantedBy=multi-user.targetEnable it and check the metrics endpoint locally:
sudo systemctl daemon-reload
sudo systemctl enable --now node_exporter
sudo systemctl status node_exporter
curl http://localhost:9100/metricsA working response is plain-text metric exposition data. The Node Exporter guide uses examples such as node_cpu_seconds_total and node_filesystem_avail_bytes. If curl cannot connect, inspect the service journal before editing Prometheus; the exporter must be listening before Prometheus can scrape it.
3. Add the exporter to Prometheus
Edit /etc/prometheus/prometheus.yml and add a second item under scrape_configs:
global:
scrape_interval: 15s
scrape_configs:
- job_name: prometheus
static_configs:
- targets: ['localhost:9090']
- job_name: node
static_configs:
- targets: ['localhost:9100']The job_name becomes part of the labels attached to the scraped series. Keep it stable; dashboards and alerts commonly select series by job. For another VPS, replace localhost with a reachable address and ensure the exporter firewall policy permits the Prometheus server.
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Validate and apply the change:
sudo promtool check config /etc/prometheus/prometheus.yml
sudo systemctl restart prometheus
sudo systemctl status prometheusRestarting is the simplest documented workflow for a small installation. Prometheus also supports configuration reload mechanisms when you have deliberately enabled and secured one; never expose an unauthenticated reload endpoint on a public interface.
Verify every layer of the deployment
Check Prometheus itself
From the VPS, request the Prometheus metrics endpoint:
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curl http://localhost:9090/metricsYou should receive Prometheus’s own process and scrape metrics. A connection failure points to a stopped service, a bind-address mismatch, or a local firewall rule. An HTTP error usually means the process started with a problem that is visible in journalctl.
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Use the web interface and Targets page
Open the interface through your trusted network path and visit /targets, also available as Status → Target health in the UI. The Prometheus and Node Exporter endpoints should both show UP. The page displays the last scrape, scrape duration, and any error returned by a target.
In the expression browser, run these queries individually:
upto see whether each configured target is currently reachable; a value of1means the scrape succeeded and0means it failed.node_cpu_seconds_totalto confirm that Node Exporter is exposing CPU counters.node_filesystem_avail_bytesto confirm that filesystem-availability metrics are being collected.
Use the labels shown with each result to distinguish the Prometheus job from the node job and to verify that the expected instance address is being scraped.
Troubleshoot a target marked DOWN
Work from the target outward rather than changing several settings at once:
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sudo systemctl status node_exporterand inspectsudo journalctl -u node_exporter -e. A crash, permission error, or invalid executable must be fixed at the exporter. - Test the endpoint locally. Run
curl http://localhost:9100/metrics. If this fails on the same VPS, Prometheus cannot succeed either. - Confirm the listening address and port. Use the service logs and the host’s socket tools to verify that the exporter is listening where the target address expects it. A process bound only to loopback cannot be reached through a private network address.
- Check firewall policy. Permit the Prometheus host to reach the exporter while keeping the exporter closed to untrusted sources. Also check any cloud security group in front of the VPS.
- Inspect the target text in YAML. A typo in the hostname, port, indentation, or job block can produce a scrape error. Run
promtool check configafter every edit. - Read the error shown on the Targets page. “Connection refused” generally means no listener or a rejected port; a timeout commonly indicates routing or firewall filtering; an HTTP parsing or status error points to the wrong path or a non-metrics service.
When Prometheus itself is DOWN, first test its own /metrics endpoint and then inspect its journal. If the service starts and exits immediately, a configuration parse failure, unavailable data directory, or occupied listening port is more likely than a Node Exporter problem.
Choose an operating model
| Decision | Option | When it fits | Trade-off |
|---|---|---|---|
| Binary source | Distribution package | You want integration with the operating system’s package manager and update policy. | The packaged release may lag behind the current upstream release. |
| Binary source | Upstream tarball | You need the release selected on the official Prometheus downloads page and a predictable standalone layout. | You own download verification, replacement, permissions, and update scheduling. |
| Process management | Manual foreground process | Initial testing, troubleshooting, or a temporary lab VPS. | The process stops when the shell ends unless you add a supervisor, and boot recovery is manual. |
| Process management | systemd service | Any persistent production or personal monitoring host. | You must maintain a unit file, service account, and data-directory ownership. |
| Target definition | Static targets | A small, stable set of VPS instances. | Every address change requires a configuration edit and reload or restart. |
| Target definition | File-based discovery | A changing fleet whose target list is maintained separately from the main YAML. | You must operate and protect the discovery file and keep its labels valid. |
| Web access | Local-only binding | You administer the VPS through SSH or a private network. | Remote users need a tunnel or private route. |
| Web access | Protected reverse proxy | You need browser access from elsewhere and can enforce authentication and TLS. | The proxy becomes another security-sensitive component to configure and update. |
| Topology | One Prometheus per VPS | Small deployments where each server can retain its own history. | Dashboards and retention are fragmented across machines. |
| Topology | Central Prometheus | A fleet that needs one query surface and centralized alerting. | Network reachability, firewall rules, and the central server become critical dependencies. |
Monitor multiple VPS instances with file-based discovery
Static configuration is clear for one or two machines. For a changing fleet, use file_sd_configs and keep the target list in a separate targets.json file. The official file-SD guidance says Prometheus watches that file and automatically updates the scrape target list when it changes, avoiding an edit to the main configuration for every target change.
A minimal discovery block looks like this:
scrape_configs:
- job_name: node
file_sd_configs:
- files:
- /etc/prometheus/targets.jsonThe discovery file contains an array of target groups. For example:
[
{
'targets': ['vps-a.example.internal:9100'],
'labels': {'environment': 'production', 'region': 'east'}
},
{
'targets': ['vps-b.example.internal:9100'],
'labels': {'environment': 'production', 'region': 'west'}
}
]JSON requires double quotes in an actual file; the single quotes above are shown only to keep this HTML example readable inside the publication format. Before deploying, replace them with valid JSON double quotes and validate the resulting configuration. Store the file with ownership and permissions that let the Prometheus service read it but prevent untrusted users from changing scrape destinations. A target-file edit can redirect monitoring traffic, so treat it as configuration, not as harmless data.
Secure and maintain the VPS
Restrict interfaces and configuration
Prometheus command-line flags can change storage, listening behavior, and other security-relevant properties. Protect the service unit, YAML file, rule files, discovery files, and the data directory from untrusted write access. If a reverse proxy is used, require authentication and encrypted transport, and avoid forwarding administrative endpoints unnecessarily.
Do not publish Node Exporter’s metrics endpoint to the entire Internet. Metrics can reveal hostnames, mount points, interfaces, kernel details, and workload patterns even when they do not contain application secrets.
Update on a defined schedule
Prometheus and exporters are ordinary software components, not fire-and-forget appliances. Track upstream releases, test replacement binaries, preserve the data directory, and restart one service at a time. The Prometheus security guidance sets a seven-day target for applying security fixes to Prometheus and listed exporters. Treat that as an operational goal: review advisories promptly, schedule the update inside seven days when a security fix applies, and verify the Targets page afterward.
Protect storage and retention
The local time-series database grows with scrape frequency, number of targets, and number of distinct labels. Monitor free space on the filesystem containing /var/lib/prometheus. A full disk can stop new samples and may prevent clean shutdown. Keep a backup or snapshot strategy appropriate to the value of the history, and document the storage path in the systemd unit so a future administrator does not mistake it for disposable temporary data.
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- Wrong archive architecture: choose the Linux build that matches
uname -m; an ARM VPS cannot run an x86-64 executable. - Running from the extracted directory: a shell test may work while a boot-time service fails because its working directory or relative paths are different. Use absolute paths in the unit and configuration.
- Data directory owned by root: a service running as
prometheusmust be able to write its configured storage path. - Malformed YAML: tabs, incorrect list indentation, and placing
targetsoutsidestatic_configsare frequent causes. Validate withpromtool check config. - Exporter installed but not scraped: installing Node Exporter does not add it to Prometheus. The
nodejob must appear underscrape_configs, followed by a restart or secured reload. - Firewall opened too widely: allow only the administration path to Prometheus and only the Prometheus host to Node Exporter.
- Editing the wrong configuration: inspect the service’s
--config.fileargument. A valid edit to another copy has no effect. - Changing target addresses without checking routes: a hostname that resolves on the shell may still be unreachable from the Prometheus service namespace or network policy.
What a successful installation looks like
At the end of the basic setup, Prometheus is running under a dedicated account, its YAML file defines a 15-second scrape interval and two jobs, and its database resides in the explicit storage directory. Node Exporter is running separately and serves host metrics locally. The Prometheus Targets page reports both jobs as UP, the expression browser returns up values of 1 for those endpoints, and queries for CPU and filesystem metrics return current series.
From there, keep the deployment deliberately small until you know which metrics, retention period, access paths, and alert rules you actually need. Add file-based discovery when the fleet changes often, move to a centralized server when one query surface is more valuable than local independence, and keep every monitoring interface behind a narrowly controlled network boundary.
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