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Grafana integrations

Integrations reference

InfluxDB

Grafana Cloud

InfluxDB integration for Grafana Cloud

InfluxDB is a high-performance, open-source, time-series database system designed for handling, analyzing, and visualizing time-series data in real time. InfluxDB is commonly used in various industries, including DevOps and infrastructure monitoring, IoT applications, real-time analytics, and more.

This integration supports InfluxDB OSS 2.7.1+

This integration includes 6 useful alerts and 3 pre-built dashboards to help monitor and visualize InfluxDB metrics and logs.

Before you begin

Metrics

InfluxDB exposes a Prometheus metrics endpoint, /metrics, that is enabled by default. To verify that this endpoint is enabled by running the following command on an InfluxDB node:

curl <your-hostname>:<your-influxdb-port>/metrics

Logs

By default, InfluxDB logs to STDOUT. For Kubernetes and Docker, no additional configuration is required. To monitor InfluxDB logs on Linux, Darwin, or Windows platforms, configure logging to a file.

First, create a log file with proper permissions:

touch /path/to/influxdb.log
chown influxdb /path/to/influxdb.log

When starting InfluxDB using the influxd daemon or a script, redirect STDOUT to a file on startup:

influxd 1> /path/to/influxdb.log

When running InfluxDB using the service manager on Linux, modify the first line of the startup script at /usr/lib/influxdb/scripts/influxd-systemd-start.sh to look like this:

/usr/bin/influxd 1> /path/to/influxdb.log &

For up-to-date information on logging to a file in InfluxDB, refer to this documentation.

Install InfluxDB integration for Grafana Cloud

In your Grafana Cloud stack, click Connections in the left-hand menu.
Find InfluxDB and click its tile to open the integration.
Review the prerequisites in the Configuration Details tab and set up Grafana Alloy to send InfluxDB 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 InfluxDB setup.

Configuration snippets for Grafana Alloy

Advanced mode

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

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

Advanced metrics snippets

prometheus.scrape "metrics_integrations_integrations_influxdb" {
	targets = [{
		__address__      = "constants.hostname:<port>",
		influxdb_cluster = "<your-cluster-name>",
		instance         = constants.hostname,
	}]
	forward_to = [prometheus.remote_write.metrics_service.receiver]
	job_name   = "integrations/influxdb"
}

To monitor your InfluxDB instance, you must use a discovery.relabel component to discover your InfluxDB Prometheus endpoint and apply appropriate labels, followed by a prometheus.scrape component to scrape it.

Configure the following properties within each discovery.relabel component:

__address__: The address to your InfluxDB Prometheus metrics endpoint.
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 InfluxDB instance. Make sure this label value is the same for all telemetry data collected for this instance.
influxdb_cluster label must be set to a value that identifies your InfluxDB cluster.

If you have multiple InfluxDB servers to scrape, configure one discovery.relabel for each and scrape them by including each under targets within the prometheus.scrape component.

Advanced logs snippets

darwin

local.file_match "logs_integrations_integrations_influxdb" {
	path_targets = [{
		__address__      = "<hostname>",
		__path__         = "/var/log/influxdb/influxdb.log",
		influxdb_cluster = "<your-cluster-name>",
		instance         = constants.hostname,
		job              = "integrations/influxdb",
	}]
}

loki.process "logs_integrations_integrations_influxdb" {
	forward_to = [loki.write.grafana_cloud_loki.receiver]

	stage.multiline {
		firstline     = "ts=\\d{4}"
		max_lines     = 0
		max_wait_time = "3s"
	}

	stage.regex {
		expression = "ts=(\\S+) lvl=(?P<level>\\w+) msg=.* log_id=(\\S+) (service=\"{0,1}(?P<service>\\S+) ){0,1}(engine=(?P<engine>\\S*) ){0,1}.*$"
	}

	stage.labels {
		values = {
			engine  = null,
			level   = null,
			service = null,
		}
	}
}

loki.source.file "logs_integrations_integrations_influxdb" {
	targets    = local.file_match.logs_integrations_integrations_influxdb.targets
	forward_to = [loki.process.logs_integrations_integrations_influxdb.receiver]
}

To monitor your InfluxDB 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 InfluxDB 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 InfluxDB instance. Make sure this label value is the same for all telemetry data collected for this instance.
- influxdb_cluster label must be set to a value that identifies your InfluxDB cluster.
loki.process defines how to process logs before sending it to Loki.
loki.source.file sends logs to Loki.

linux

local.file_match "logs_integrations_integrations_influxdb" {
	path_targets = [{
		__address__      = "<hostname>",
		__path__         = "/var/log/influxdb/influxdb.log",
		influxdb_cluster = "<your-cluster-name>",
		instance         = constants.hostname,
		job              = "integrations/influxdb",
	}]
}

loki.process "logs_integrations_integrations_influxdb" {
	forward_to = [loki.write.grafana_cloud_loki.receiver]

	stage.multiline {
		firstline     = "ts=\\d{4}"
		max_lines     = 0
		max_wait_time = "3s"
	}

	stage.regex {
		expression = "ts=(\\S+) lvl=(?P<level>\\w+) msg=.* log_id=(\\S+) (service=\"{0,1}(?P<service>\\S+) ){0,1}(engine=(?P<engine>\\S*) ){0,1}.*$"
	}

	stage.labels {
		values = {
			engine  = null,
			level   = null,
			service = null,
		}
	}
}

loki.source.file "logs_integrations_integrations_influxdb" {
	targets    = local.file_match.logs_integrations_integrations_influxdb.targets
	forward_to = [loki.process.logs_integrations_integrations_influxdb.receiver]
}

To monitor your InfluxDB 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 InfluxDB 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 InfluxDB instance. Make sure this label value is the same for all telemetry data collected for this instance.
- influxdb_cluster label must be set to a value that identifies your InfluxDB cluster.
loki.process defines how to process logs before sending it to Loki.
loki.source.file sends logs to Loki.

windows

local.file_match "logs_integrations_integrations_influxdb" {
	path_targets = [{
		__address__      = "<hostname>",
		__path__         = "/var/log/influxdb/influxdb.log",
		influxdb_cluster = "<your-cluster-name>",
		instance         = constants.hostname,
		job              = "integrations/influxdb",
	}]
}

loki.process "logs_integrations_integrations_influxdb" {
	forward_to = [loki.write.grafana_cloud_loki.receiver]

	stage.multiline {
		firstline     = "ts=\\d{4}"
		max_lines     = 0
		max_wait_time = "3s"
	}

	stage.regex {
		expression = "ts=(\\S+) lvl=(?P<level>\\w+) msg=.* log_id=(\\S+) (service=\"{0,1}(?P<service>\\S+) ){0,1}(engine=(?P<engine>\\S*) ){0,1}.*$"
	}

	stage.labels {
		values = {
			engine  = null,
			level   = null,
			service = null,
		}
	}
}

loki.source.file "logs_integrations_integrations_influxdb" {
	targets    = local.file_match.logs_integrations_integrations_influxdb.targets
	forward_to = [loki.process.logs_integrations_integrations_influxdb.receiver]
}

To monitor your InfluxDB 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 InfluxDB 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 InfluxDB instance. Make sure this label value is the same for all telemetry data collected for this instance.
- influxdb_cluster label must be set to a value that identifies your InfluxDB cluster.
loki.process defines how to process logs before sending it to Loki.
loki.source.file sends logs to Loki.

Dashboards

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

InfluxDB cluster overview
InfluxDB instance overview
InfluxDB logs overview

InfluxDB cluster overview (queries)

InfluxDB cluster overview (tasks)

InfluxDB cluster overview (Go)

Alerts

The InfluxDB integration includes the following useful alerts:

Alert	Description
InfluxDBWarningTaskSchedulerHighFailureRate	Warning: Automated data processing tasks are failing at a high rate.
InfluxDBCriticalTaskSchedulerHighFailureRate	Critical: Automated data processing tasks are failing at a critical rate.
InfluxDBHighBusyWorkerPercentage	Critical: There is a high percentage of busy workers.
InfluxDBHighHeapMemoryUsage	Critical: There is a high amount of heap memory being used.
InfluxDBHighAverageAPIRequestLatency	Critical: Average API request latency is too high. High latency will negatively affect system performance, degrading data availability and precision.
InfluxDBSlowAverageIQLExecutionTime	Warning: InfluxQL execution times are too slow. Slow query execution times will negatively affect system performance, degrading data availability and precision.

Metrics

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

boltdb_reads_total
boltdb_writes_total
go_gc_duration_seconds_sum
go_memstats_gc_cpu_fraction
go_memstats_heap_alloc_bytes
go_memstats_heap_idle_bytes
go_memstats_last_gc_time_seconds
go_threads
http_api_request_duration_seconds_sum
http_api_requests_total
http_query_request_bytes
http_query_request_count
http_query_response_bytes
http_write_request_bytes
http_write_request_count
http_write_response_bytes
influxdb_buckets_total
influxdb_dashboards_total
influxdb_remotes_total
influxdb_replications_total
influxdb_scrapers_total
influxdb_uptime_seconds
influxdb_users_total
influxql_service_executing_duration_seconds_sum
influxql_service_requests_total
qc_compiling_active
qc_executing_active
qc_queueing_active
task_executor_total_runs_active
task_executor_workers_busy
task_scheduler_current_execution
task_scheduler_total_execute_failure
task_scheduler_total_execution_calls
task_scheduler_total_schedule_calls
task_scheduler_total_schedule_fails
up

Changelog

# 1.0.1 - November 2024

- Update status panel check queries

# 1.0.0 - January 2023

- Initial release

Cost

By connecting your InfluxDB 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.