title:Monitoring Linux host metrics with the Node Exporter
---
# Monitoring Linux host metrics with the Node Exporter
The Prometheus [**Node Exporter**](https://github.com/prometheus/node_exporter) exposes a wide variety of hardware- and kernel-related metrics.
In this guide, you will:
* Start up a Node Exporter on `localhost`
* Start up a Prometheus instance on `localhost` that's configured to scrape metrics from the running Node Exporter
NOTE: While the Prometheus Node Exporter is for *nix systems, there is a [WMI exporter](https://github.com/martinlindhe/wmi_exporter) for Windows that serves an analogous purpose.
## Installing and running the Node Exporter
The Prometheus Node Exporter is a single static binary that you can install [via tarball](#tarball-installation). Once you've downloaded it from the Prometheus [downloads page](/downloads#node_exporter) extract it, and run it:
Success! The Node Exporter is now exposing metrics that Prometheus can scrape, including a wide variety of system metrics further down in the output (prefixed with `node_`). To view those metrics (along with help and type information):
```bash
curl http://localhost:9100/metrics | grep"node_"
```
## Configuring your Prometheus instances
Your locally running Prometheus instance needs to be properly configured in order to access Node Exporter metrics. The following [`scrape_config`](../prometheus/latest/configuration/configuration/#<scrape_config>) block (in a `prometheus.yml` configuration file) will tell the Prometheus instance to scrape from the Node Exporter via `localhost:9100`:
<aid="config"></a>
```yaml
scrape_configs:
-job_name:'node'
static_configs:
-targets:['localhost:9100']
```
To install Prometheus, [download the latest release](/download) for your platform and untar it:
Once Prometheus is installed you can start it up, using the `--config.file` flag to point to the Prometheus configuration that you created [above](#config):
```bash
./prometheus --config.file=./prometheus.yml
```
## Exploring Node Exporter metrics through the Prometheus expression browser
Now that Prometheus is scraping metrics from a running Node Exporter instance, you can explore those metrics using the Prometheus UI (aka the [expression browser](/docs/visualization/expression-browser)). Navigate to `localhost:9090/graph` in your browser and use the main expression bar at the top of the page to enter expressions. The expression bar looks like this:
Metrics specific to the Node Exporter are prefixed with `node_` and include metrics like `node_cpu_seconds_total` and `node_exporter_build_info`.
Click on the links below to see some example metrics:
Metric | Meaning
:------|:-------
[`rate(node_cpu_seconds_total{mode="system"}[1m])`](http://localhost:9090/graph?g0.range_input=1h&g0.expr=rate(node_cpu_seconds_total%7Bmode%3D%22system%22%7D%5B1m%5D)&g0.tab=1) | The average number of CPU seconds spent in system, per second, over the last minute
[`node_filesystem_avail_bytes`](http://localhost:9090/graph?g0.range_input=1h&g0.expr=node_filesystem_avail_bytes&g0.tab=1) | The filesystem space available to non-root users (in bytes)
[`rate(node_network_receive_bytes_total[1m])`](http://localhost:9090/graph?g0.range_input=1h&g0.expr=rate(node_network_receive_bytes_total%5B1m%5D)&g0.tab=1) | The average network traffic received, per second, over the last minute (in bytes)
Welcome to Prometheus! Prometheus is a monitoring platform that collects metrics from monitored targets by scraping metrics HTTP endpoints on these targets. This guide will show you to how to install, configure and monitor our first resource with Prometheus. You'll download, install and run Prometheus. You'll also download and install an exporter, tools that expose time series data on hosts and services. Our first exporter will be the Node Exporter, which exposes host-level metrics like CPU, memory, and disk.
Welcome to Prometheus! Prometheus is a monitoring platform that collects metrics from monitored targets by scraping metrics HTTP endpoints on these targets. This guide will show you to how to install, configure and monitor our first resource with Prometheus. You'll download, install and run Prometheus. You'll also download and install an exporter, tools that expose time series data on hosts and services. Our first exporter will be Prometheus itself, which provides a wide variety of host-level metrics about memory usage, garbage collection, and more.
You can experiment with the graph range parameters and other settings.
## Installing the Node Exporter
## Monitoring other targets
Collecting metrics from Prometheus alone is not a good representation of Prometheus' capabilities. So let's use the Node Exporter to monitor our first resource. We're going to monitor the local Linux host that the Prometheus server is running on but you could monitor any Linux or OS X host. There's also [a WMI exporter](https://github.com/martinlindhe/wmi_exporter) for Microsoft Windows hosts too.
[Download the latest release of the Node Exporter](/download/#node_exporter) of Prometheus for your platform, then extract it:
```language-bash
tar xvfz node_exporter-*.tar.gz
cd node_exporter-*
```
The Node Exporter is a single binary, `node_exporter`, and has a configurable set of collectors for gathering various types of host-based metrics. By default, collectors gather [CPU, memory, disk, and other metrics](https://github.com/prometheus/node_exporter#enabled-by-default) and expose them for scraping.
Let's start the Node Exporter now on our Linux host.
```language-bash
./node_exporter
```
The Node Exporter's metrics are available on port `9100` on the host at the `/metrics` path. In our case this is: http://localhost:9100/metrics.
You can browse to this URL to see the metrics being exposed.
We now need to tell Prometheus about our new exporter.
## Configuring Prometheus to monitor the host
We will configure Prometheus to scrape this new target. To achieve this, add a new job definition to the `scrape_configs` section in our `prometheus.yml`:
```
- job_name: node
static_configs:
- targets: ['localhost:9100']
```
Our new job is called `node`. It scrapes a static target, `localhost` on port `9100`. You would replace this name with the name or IP address of the host you're monitoring.
Now we restart our Prometheus server to activate our new job.
Go to the expression browser and verify that Prometheus now has information
about the time series that this endpoint exposes. Navigate to
http://localhost:9090/graph and use the dropdown next to the "Execute" button to see a list of metrics this server is collecting. In the list you'll see a number of metrics prefixed with `node_`, that have been collected by the Node Exporter by our `node` job. For example, you can see the node's CPU usage via the `node_cpu_seconds_total` or `node_exporter_build_info` metric.
One useful metric to look for is the `up` metric. The `up` metric can be used to track the status of the target. If the metric has a value of `1` then the scrape of the target was successful, if `0` it failed. This can help give you an indication of the status of the target. You'll see two `up` metrics, one for each target we're scraping: the Prometheus server and the Node Exporter.
Collecting metrics from Prometheus alone isn't a great representation of Prometheus' capabilities. To get a better sense of what Prometheus can do, we recommend exploring documentation about other exporters. The [Monitoring Linux or macOS host metrics using a node exporter](/docs/guides/node-exporter) guide is a good place to start.
## Summary
Now you've been introduced to Prometheus, installed it, and configured it to monitor your first resources. We've also installed our first exporter and seen the basics of how to work with time series data scraped using the expression browser. You can find more [documentation](/docs/introduction/overview/) to help you continue to learn more about Prometheus.
In this guide, you installed Prometheus, configured a Prometheus instance to monitor resources, and learned some basics of working with time series data in Prometheus' expression browser. To continue learning about Prometheus, check out the [Overview](/docs/introduction/overview) for some ideas about what to explore next.
