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To monitor a server with Prometheus and Grafana, expose host metrics with an exporter, configure Prometheus to scrape that exporter, then connect Grafana to Prometheus and build panels with PromQL. Prometheus collects and stores the time series; Grafana queries and visualizes them. The setup below follows Grafana’s Linux-oriented getting-started guide, so other operating systems and environments may need different steps.
How the monitoring workflow fits together
Think of the stack as three parts with distinct jobs:
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- Exporter: exposes host metrics over an HTTP endpoint. Node exporter is Grafana’s example for Linux hosts; Windows hosts use
windows_exporter. - Prometheus: pulls metrics from configured target endpoints and stores them as time series.
- Grafana: connects to Prometheus as a data source, lets you explore metrics with PromQL, and displays query results in dashboard panels.
Prometheus is not the dashboard interface: its basic model is to scrape HTTP endpoints exposed by targets. See the Prometheus first steps guide and Grafana’s Prometheus dashboard walkthrough.
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Plan for the monitored hosts and their operating systems first. The steps in Grafana’s introductory guide are written for Linux; installation and service configuration can differ elsewhere.
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- Install an exporter on each host. For the guide’s Linux example, install Node exporter. For a local instance, check that
http://localhost:9100/metricsis reachable and returns metric text. For Windows, consult thewindows_exporterproject and use its current installation instructions. - Configure Prometheus to scrape the exporter. Install Prometheus and add a scrape job to
prometheus.ymlthat targets the endpoint for each exporter. The target address must be reachable from the Prometheus server;localhostrefers to the machine making the request, so it is only appropriate when Prometheus and the exporter are on the same host. - Connect Grafana to Prometheus. In Grafana, add a Prometheus data source and enter the Prometheus server address. Grafana’s Prometheus data source is included; a separate plugin installation is not required. Follow the current Prometheus data source documentation for the version you run.
- Explore available metrics. Open Grafana Explore, select the Prometheus data source, and inspect metrics returned by the server before designing panels. This helps confirm both collection and querying are working.
- Build dashboard panels with PromQL. Create queries for the metrics you want to see, then add them as panels and choose a visualization suited to the data. Prometheus’s Grafana support guide describes querying Prometheus data in Grafana.
Choose a host for the stack
You can run Grafana and Prometheus on an existing server or virtual machine; the introductory setup does not require dedicated hardware. A separate machine, such as a mini PC, is an optional way to keep monitoring services apart from the hosts being monitored, not a requirement of the workflow.
Another option is hosted Grafana Cloud rather than operating a Grafana instance yourself. Grafana’s alerting documentation presents the hosted service as a way to avoid installing, maintaining, and scaling Grafana. The cited documentation does not establish a general winner for cost, feature limits, data residency, or vendor lock-in, so evaluate those requirements for your environment rather than assuming hosted or self-managed is better.
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Turn metrics into useful panels and alerts
Use panels for visibility
A dashboard panel visualizes a query result; a visible threshold or concerning line is not, by itself, an alert. For queries that use PromQL rate or increase, Grafana’s visualization guidance recommends $__rate_interval for Grafana 7.2 and later. This is version-specific guidance, so check the current Grafana documentation and version when building or migrating dashboards.
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Grafana documents two alert-rule paths. Grafana-managed rules are defined and evaluated in Grafana, using Prometheus as the query source. Data source-managed rules originate in Prometheus configuration or rule files; when the relevant setting is enabled, Grafana can display Prometheus rules in its alerting UI, but those rules are read-only there. Edit Prometheus-native rules in Prometheus configuration or rule files.
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An alert needs more than a dashboard threshold: decide who owns the rule, how often it is evaluated, how long a condition must remain true before firing, and where notifications go. Grafana’s Prometheus alerting documentation covers the query, condition, evaluation interval, pending period, labels, and notification configuration; it also expects a Prometheus data source and familiarity with the relevant PromQL metrics.
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Grafana can expose its own internal metrics at /metrics for Prometheus to scrape. Those metrics can then be used in Grafana dashboards, Explore, or alerts, including metrics concerning dashboards, users, HTTP status codes, active alerts, and performance. Grafana’s monitoring setup guide also discusses native histogram settings; disabling classic HTTP histogram buckets can reduce metric cardinality. Make this an intentional configuration decision, since changing which metrics are exposed affects the monitoring data available to you.
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Check exporters before adding them
Exporters make metrics available for systems that cannot be instrumented directly. Prometheus distinguishes projects maintained within its official GitHub organization from externally contributed exporters and cautions that it cannot vet every third-party project. Before relying on an exporter beyond the official Node exporter example, check who maintains it, whether it supports your system, and whether its current version is compatible with your Prometheus setup. The Prometheus exporters and integrations guide explains the distinction.
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