Monitor infrastructure

Grafana integrations

Integrations reference

Raspberry Pi

Grafana Cloud

Raspberry Pi integration for Grafana Cloud

The Raspberry Pi integration uses Grafana Alloy to collect metrics related to the operating system (Linux-based), including aspects like CPU usage, load average, memory usage, and disk and networking I/O. It also supports system logs being scraped by Alloy using promtail. An accompanying dashboard is provided to visualize these metrics and logs.

The Raspberry Pi integration uses node-observ-lib.

This integration includes 15 useful alerts and 2 pre-built dashboards to help monitor and visualize Raspberry Pi metrics and logs.

Before you begin

Each Raspberry Pi node being observed must have its dedicated Grafana Alloy running.

Install Raspberry Pi integration for Grafana Cloud

In your Grafana Cloud stack, click Connections in the left-hand menu.
Find Raspberry Pi and click its tile to open the integration.
Review the prerequisites in the Configuration Details tab and set up Grafana Alloy to send Raspberry Pi metrics and logs to your Grafana Cloud instance.
Click Install to add this integration’s pre-built dashboards and alerts to your Grafana Cloud instance, and you can start monitoring your Raspberry Pi setup.

Configuration snippets for Grafana Alloy

Simple mode

These snippets are configured to scrape a single Raspberry Pi instance running locally with default ports.

First, manually copy and append the following snippets into your alloy configuration file.

Integrations snippets

prometheus.exporter.unix "integrations_node_exporter" { }

discovery.relabel "integrations_node_exporter" {
	targets = prometheus.exporter.unix.integrations_node_exporter.targets

	rule {
		target_label = "instance"
		replacement  = constants.hostname
	}

	rule {
		target_label = "job"
		replacement  = "integrations/raspberrypi-node"
	}
}

prometheus.scrape "integrations_node_exporter" {
	targets    = discovery.relabel.integrations_node_exporter.output
	forward_to = [prometheus.remote_write.metrics_service.receiver]
	job_name   = "integrations/node_exporter"
}

Logs snippets

linux

discovery.relabel "logs_integrations_integrations_node_exporter_journal_scrape" {
	targets = []

	rule {
		source_labels = ["__journal__systemd_unit"]
		target_label  = "unit"
	}

	rule {
		source_labels = ["__journal__boot_id"]
		target_label  = "boot_id"
	}

	rule {
		source_labels = ["__journal__transport"]
		target_label  = "transport"
	}

	rule {
		source_labels = ["__journal_priority_keyword"]
		target_label  = "level"
	}
}

loki.source.journal "logs_integrations_integrations_node_exporter_journal_scrape" {
	max_age       = "24h0m0s"
	relabel_rules = discovery.relabel.logs_integrations_integrations_node_exporter_journal_scrape.rules
	forward_to    = [loki.write.grafana_cloud_loki.receiver]
	labels        = {
		instance = constants.hostname,
		job      = "integrations/raspberrypi-node",
	}
}

local.file_match "logs_integrations_integrations_node_exporter_direct_scrape" {
	path_targets = [{
		__address__ = "localhost",
		__path__    = "/var/log/{syslog,messages,*.log}",
		instance    = constants.hostname,
		job         = "integrations/raspberrypi-node",
	}]
}

loki.source.file "logs_integrations_integrations_node_exporter_direct_scrape" {
	targets    = local.file_match.logs_integrations_integrations_node_exporter_direct_scrape.targets
	forward_to = [loki.write.grafana_cloud_loki.receiver]
}

Advanced mode

The following snippets provide examples to guide you through the configuration process.

To instruct Grafana Alloy to scrape your Raspberry Pi instances, manually copy and append the snippets to your alloy configuration file, then follow subsequent instructions.

Advanced integrations snippets

prometheus.exporter.unix "integrations_node_exporter" { }

discovery.relabel "integrations_node_exporter" {
	targets = prometheus.exporter.unix.integrations_node_exporter.targets

	rule {
		target_label = "instance"
		replacement  = constants.hostname
	}

	rule {
		target_label = "job"
		replacement  = "integrations/raspberrypi-node"
	}
}

prometheus.scrape "integrations_node_exporter" {
	targets    = discovery.relabel.integrations_node_exporter.output
	forward_to = [prometheus.remote_write.metrics_service.receiver]
	job_name   = "integrations/node_exporter"
}

This integrations uses the prometheus.exporter.unix component to generate metrics from a Raspberry Pi instance.

For the full array of configuration options, refer to the prometheus.exporter.unix component reference documentation.

This exporter must be linked with a discovery.relabel component to apply the necessary relabelings.

For each Raspberry Pi instance to be monitored you must create a pair of these components.

Configure the following properties within each discovery.relabel component:

instance label: constants.hostname sets the instance label to your Grafana Alloy server hostname. If that is not suitable, change it to a value uniquely identifies this Raspberry Pi instance. Make sure this label value is the same for all telemetry data collected for this instance.

You can then scrape them by including each discovery.relabel under targets within the prometheus.scrape component.

Advanced logs snippets

linux

discovery.relabel "logs_integrations_integrations_node_exporter_journal_scrape" {
	targets = []

	rule {
		source_labels = ["__journal__systemd_unit"]
		target_label  = "unit"
	}

	rule {
		source_labels = ["__journal__boot_id"]
		target_label  = "boot_id"
	}

	rule {
		source_labels = ["__journal__transport"]
		target_label  = "transport"
	}

	rule {
		source_labels = ["__journal_priority_keyword"]
		target_label  = "level"
	}
}

loki.source.journal "logs_integrations_integrations_node_exporter_journal_scrape" {
	max_age       = "24h0m0s"
	relabel_rules = discovery.relabel.logs_integrations_integrations_node_exporter_journal_scrape.rules
	forward_to    = [loki.write.grafana_cloud_loki.receiver]
	labels        = {
		instance = constants.hostname,
		job      = "integrations/raspberrypi-node",
	}
}

local.file_match "logs_integrations_integrations_node_exporter_direct_scrape" {
	path_targets = [{
		__address__ = "localhost",
		__path__    = "/var/log/{syslog,messages,*.log}",
		instance    = constants.hostname,
		job         = "integrations/raspberrypi-node",
	}]
}

loki.source.file "logs_integrations_integrations_node_exporter_direct_scrape" {
	targets    = local.file_match.logs_integrations_integrations_node_exporter_direct_scrape.targets
	forward_to = [loki.write.grafana_cloud_loki.receiver]
}

To monitor your Raspberry Pi instance logs, you will use a combination of the following components:

local.file_match defines where to find the log file to be scraped. Change the following properties according to your environment:
- __address__: The Raspberry Pi instance address
- __path__: The path to the log file.
- instance label: constants.hostname sets the instance label to your Grafana Alloy server hostname. If that is not suitable, change it to a value uniquely identifies this Raspberry Pi instance. Make sure this label value is the same for all telemetry data collected for this instance.
loki.source.journal Reads logs from the systemd journal. Change the following properties according to your environment:
- max_age: The oldest relative time from process start that will be read.
discovery.relabel defines any relabeling needed before sending logs to Loki.
loki.source.file sends logs to Loki.

Dashboards

The Raspberry Pi integration installs the following dashboards in your Grafana Cloud instance to help monitor your system.

Raspberry Pi / logs
Raspberry Pi / overview

Raspberry Pi overview

Raspberry Pi logs

Alerts

The Raspberry Pi integration includes the following useful alerts:

raspberrypi-node-filesystem-alerts

Alert	Description
NodeFilesystemAlmostOutOfSpace	Warning: Filesystem has less than 5% space left.
NodeFilesystemAlmostOutOfSpace	Critical: Filesystem has less than 3% space left.
NodeFilesystemFilesFillingUp	Warning: Filesystem is predicted to run out of inodes within the next 24 hours.
NodeFilesystemFilesFillingUp	Critical: Filesystem is predicted to run out of inodes within the next 4 hours.
NodeFilesystemAlmostOutOfFiles	Warning: Filesystem has less than 5% inodes left.
NodeFilesystemAlmostOutOfFiles	Critical: Filesystem has less than 3% inodes left.

raspberrypi-node-alerts

Alert	Description
NodeNetworkReceiveErrs	Warning: Network interface is reporting many receive errors.
NodeNetworkTransmitErrs	Warning: Network interface is reporting many transmit errors.
NodeCPUHighUsage	Info: High CPU usage.
NodeSystemSaturation	Warning: System saturated, load per core is very high.
NodeMemoryMajorPagesFaults	Warning: Memory major page faults are occurring at very high rate.
NodeMemoryHighUtilization	Warning: Host is running out of memory.
NodeDiskIOSaturation	Warning: Disk IO queue is high.
NodeSystemdServiceFailed	Warning: Systemd service has entered failed state.
NodeHardwareTemperatureHigh	Warning: Sensor’s temperature is high.

Metrics

The most important metrics provided by the Raspberry Pi integration, which are used on the pre-built dashboards and Prometheus alerts, are as follows:

node_boot_time_seconds
node_cpu_seconds_total
node_disk_io_time_seconds_total
node_disk_io_time_weighted_seconds_total
node_disk_read_bytes_total
node_disk_written_bytes_total
node_filesystem_avail_bytes
node_filesystem_files
node_filesystem_files_free
node_filesystem_readonly
node_filesystem_size_bytes
node_hwmon_temp_celsius
node_load1
node_load15
node_load5
node_memory_Buffers_bytes
node_memory_Cached_bytes
node_memory_MemAvailable_bytes
node_memory_MemFree_bytes
node_memory_MemTotal_bytes
node_memory_Slab_bytes
node_memory_SwapTotal_bytes
node_network_receive_bytes_total
node_network_receive_drop_total
node_network_receive_errs_total
node_network_receive_packets_total
node_network_transmit_bytes_total
node_network_transmit_drop_total
node_network_transmit_errs_total
node_network_transmit_packets_total
node_os_info
node_systemd_unit_state
node_uname_info
node_vmstat_pgmajfault
up

Changelog

# 1.0.1 - November 2024

- Update status panel check queries

# 1.0.0 - December 2023

* Use latest linux observabiltiy library
* Add separate logs dashboard
* Add inventory panels row 
* Add grafana annotations for events like reboot, OOMkill and others
* Add metrics and logs status panels
* Rename dashboards' prefix to 'Raspberry Pi /'
* Add new alerts: NodeCPUHighUsage, NodeSystemSaturation, NodeMemoryMajorPagesFaults, NodeDiskIOSaturation, NodeSystemdServiceFailed, NodeHardwareTemperatureHigh.

# 0.0.4 - September 2023

* Update Grafana Agent configuration snippets to include filtered metrics used in gauge panels

# 0.0.3 - August 2023

* Add regex filter for logs datasource

# 0.0.2 - July 2023

* New Filter Metrics option for configuring the Grafana Agent, which saves on metrics cost by dropping any metric not used by this integration. Beware that anything custom built using metrics that are not on the snippet will stop working.

# 0.0.1 - September 2022

* Initial release

Cost

By connecting your Raspberry Pi instance to Grafana Cloud, you might incur charges. To view information on the number of active series that your Grafana Cloud account uses for metrics included in each Cloud tier, see Active series and dpm usage and Cloud tier pricing.