BigPanda event handler - Influxdb

BigPanda is an event correlation and automation platform that helps organizations prevent and resolve IT outages.

Configuration

Configuration and default option values for the BigPanda event handler are set in your kapacitor.conf. The example below shows the default configuration:

toml

[bigpanda]
  enabled = false
  # BigPanda integration App Key
  app-key = ""
  # Authorization Bearer token for BigPanda REST API.  
  token = ""
  # BigPanda Alert API url  
  url = "https://api.bigpanda.io/data/v2/alerts"

`enabled`

Set to true to enable the BigPanda event handler.

`token`

Set your authorization Bearer token for BigPanda REST API.

`app-key`

Set your BigPanda integration App Key. To get your App Key, log in to your BigPanda account and select Integrations in the header toolbar, and then click the New Integration. Select Alerts REST API, click Integrate button, and then Create an App Key.

`url`

BigPanda Alert API URL.

Options

The following BigPanda event handler options can be set in a handler file or when using .bigPanda() in a TICKscript.

Name	Type	Description
appKey	string	BigPanda appKey
primaryProperty	string	BigPanda primary property
secondaryProperty	string	BigPanda secondary property
host	string	Host alert payload parameter (object that caused the alert)
attributes	map of key value pairs	Option to add additional attribute(s) to the alert payload

BigPanda uses the primary property to construct the title and the secondary property to construct the subtitle of an incident. See Alert Correlation Logic for more information.

By default, the handler maps the Kapacitor task and alert properties below to the BigPanda Alert or Event fields as follows:

Value	BigPanda Alert Field
`id`	check
`message`	description
`details`	details
`TaskName`	task

All EventData tags and fields are appended to the BigPanda Alert as Additional attributes. For more information, see BigPanda Alert REST API.

TICKscript examples

stream
  |from()
    .measurement('cpu')
  |alert()
    .id('cpu_usage')
    .crit(lambda: "usage_user" > 90)
    .stateChangesOnly()
    .message('Hey, check your CPU')
    .bigPanda()

stream
  |from()
    .database('telegraf')
    .retentionPolicy('autogen')
    .measurement('cpu')
    .groupBy('host')
    .where(lambda: "cpu" == 'cpu-total')
  |eval(lambda: 100.0 - "usage_idle").as('total_used')
  |window().period(10s).every(10s)
  |mean('total_used').as('total_used')
  |alert()
    .id('cpu_usage_check')
    .message('Hey {{ index .Tags "host"}} / {{ .ID }}: is high!')
    .details('https://example.com/dashboard/{{ index .Tags "host"}}')
    .info(lambda: "total_used" > 70)
    .warn(lambda: "total_used" > 80)
    .crit(lambda: "total_used" > 90)
    .stateChangesOnly()
    .appKey('...')
    bigPanda()
      .host('{{ .Tags.host }}')
      .attribute('monitor_link', 'http://example.com/monitor?node={{ .Tags.host }}')
      .attribute('x_total_used', '{{ .Fields.total_used }}')