BigPanda event handler
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:
[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 }}')Was this page helpful?
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