Configure a watcher of watchers system to monitor InfluxDB servers

The flexibility and portability of InfluxData’s TICK stack make it easy to use in different monitoring solutions, including monitoring the TICK stack with another TICK stack. This guide walks through setting up an external TICK stack monitor to which important metrics are sent and monitored.

The following terms are used throughout this guide:

  • Primary - The monitored TICK stack or cluster for which uptime is most important.
  • Monitor - The monitoring TICK stack to which monitoring data is sent and processed.

This guide assumes a primary node or cluster is already running.

Install a monitor

Install a separate TICK stack to act as your monitor. Your monitor should be on hardware separate from your primary cluster. Installation instructions for the TICK stack are provided in the installation guides.

In order for your monitor to receive data from your primary cluster, the primary must be able to connect to your monitor’s API endpoint via HTTP or UDP.

Install Telegraf on each node

Install the telegraf agent on each node in your primary InfluxDB cluster you would like to monitor.

Send data collected by Telegraf to your monitor

Generate a Telegraf configuration file and modify the InfluxDB output url setting to include the URL of your monitor’s InfluxDB API endpoint.

telegraf.conf

# ...

[[outputs.influxdb]]
  ## The full HTTP or UDP URL for your InfluxDB instance.
  urls = ["http://monitor-url.com:8086"]

# ...

Configure Telegraf input plugins

By default, Telegraf is configured to collect the following system metrics from the host machine:

  • CPU
  • Disk
  • Disk IO
  • Memory
  • Processes
  • Swap
  • System (load, number of CPUs, number of users, uptime, etc.)

Use other Telegraf input plugins to collect a variety of metrics.

Monitor InfluxDB performance metrics

To monitor the internal performance of InfluxDB, enable the InfluxDB input plugin in the Telegraf configuration files used to run Telegraf on InfluxDB instances. The InfluxDB input plugin pulls InfluxDB internal metrics from the local InfluxDB /debug/vars endpoint.

# ...

[[inputs.influxdb]]
  # ...
  ## Multiple URLs from which to read InfluxDB-formatted JSON
  ## Default is "http://localhost:8086/debug/vars".
  urls = [
    "http://localhost:8086/debug/vars"
  ]

# ...

Monitor Kapacitor performance metrics

To monitor the internal performance of Kapacitor, enable the Kapacitor input plugin in the Telegraf configuration files used to run Telegraf on Kapacaitor instances. The Kapacitor input plugin pulls Kapactor internal metrics from the local Kapacitor /debug/vars endpoint.

# ...

[[inputs.influxdb]]
  # ...
  ## Multiple URLs from which to read Kapacitor-formatted JSON
  ## Default is "http://localhost:9092/kapacitor/v1/debug/vars".
  urls = [
    "http://localhost:9092/kapacitor/v1/debug/vars"
  ]

# ...

(Optional) Namespace monitoring data

If Telegraf is running on your monitor instance, it will store your monitor’s own metrics in the telegraf database by default. To keep your monitor’s internal data separate from your other monitoring data, configure your local Telegraf agent to write to a database other than telegraf using the database setting under [[outputs.influxdb]] in your telelgraf.conf.

# ...

[[outputs.influxdb]]
  # ...
  ## The target database for metrics; will be created as needed.
  database = "monitor_local"

  # ...

(Optional) Update primary hostnames

Telegraf’s default behavior is to include a host tag on each data point using the os.hostname provided by the host machine. Customize the hostname by updating the hostname setting under the [agent] section in your telegraf.conf.

Example custom hostname in telegraf.conf

[agent]

  # ...

  ## Override default hostname, if empty use os.Hostname()
  hostname = "primary_influxdb_1"

  # ...

Start Telegraf

With Telegraf installed and configured on each of your primary nodes, start Telegraf using your custom configuration file.

telegraf -config path/to/telegraf.conf

Create Kapacitor monitoring alerts

Monitoring data should now be flowing from your primary cluster to your monitor where it can be processed by your monitor’s Kapacitor component. Create Kapacitor alerts that alert you of issues detected in any of the monitored metrics.

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