splunkmetric

README

Splunk Metrics serializer

The Splunk Metrics serializer outputs metrics in the Splunk metric HEC JSON format.

It can be used to write to a file using the file output, or for sending metrics to a HEC using the standard telegraf HTTP output. If you're using the HTTP output, this serializer knows how to batch the metrics so you don't end up with an HTTP POST per metric.

An example event looks like:

{
  "time": 1529708430,
  "event": "metric",
  "host": "patas-mbp",
  "fields": {
    "_value": 0.6,
    "cpu": "cpu0",
    "dc": "mobile",
    "metric_name": "cpu.usage_user",
    "user": "ronnocol"
  }
}

In the above snippet, the following keys are dimensions:

• cpu
• dc
• user

Using Multimetric output

Starting with Splunk Enterprise and Splunk Cloud 8.0, you can now send multiple metric values in one payload. This means, for example, that you can send all of your CPU stats in one JSON struct, an example event looks like:

{
  "time": 1572469920,
  "event": "metric",
  "host": "mono.local",
  "fields": {
    "class": "osx",
    "cpu": "cpu0",
    "metric_name:telegraf.cpu.usage_guest": 0,
    "metric_name:telegraf.cpu.usage_guest_nice": 0,
    "metric_name:telegraf.cpu.usage_idle": 65.1,
    "metric_name:telegraf.cpu.usage_iowait": 0,
    "metric_name:telegraf.cpu.usage_irq": 0,
    "metric_name:telegraf.cpu.usage_nice": 0,
    "metric_name:telegraf.cpu.usage_softirq": 0,
    "metric_name:telegraf.cpu.usage_steal": 0,
    "metric_name:telegraf.cpu.usage_system": 10.2,
    "metric_name:telegraf.cpu.usage_user": 24.7,
  }
}

In order to enable this mode, there's a new option splunkmetric_multimetric that you set in the appropriate output module you plan on using.

Using with the HTTP output

To send this data to a Splunk HEC, you can use the HTTP output, there are some custom headers that you need to add to manage the HEC authorization, here's a sample config for an HTTP output:

[[outputs.http]]
   ## URL is the address to send metrics to
   url = "https://localhost:8088/services/collector"

   ## Timeout for HTTP message
   # timeout = "5s"

   ## HTTP method, one of: "POST" or "PUT"
   # method = "POST"

   ## HTTP Basic Auth credentials
   # username = "username"
   # password = "pa$$word"

   ## Optional TLS Config
   # tls_ca = "/etc/telegraf/ca.pem"
   # tls_cert = "/etc/telegraf/cert.pem"
   # tls_key = "/etc/telegraf/key.pem"
   ## Use TLS but skip chain & host verification
   # insecure_skip_verify = false

   ## Data format to output.
   ## Each data format has it's own unique set of configuration options, read
   ## more about them here:
   ## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md
   data_format = "splunkmetric"
    ## Provides time, index, source overrides for the HEC
   splunkmetric_hec_routing = true
   # splunkmetric_multimetric = true

   ## Additional HTTP headers
    [outputs.http.headers]
   # Should be set manually to "application/json" for json data_format
      Content-Type = "application/json"
      Authorization = "Splunk xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
      X-Splunk-Request-Channel = "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"

Overrides

You can override the default values for the HEC token you are using by adding additional tags to the config file.

The following aspects of the token can be overridden with tags:

• index
• source

You can either use [global_tags] or using a more advanced configuration as documented here.

Such as this example which overrides the index just on the cpu metric:

[[inputs.cpu]]
  percpu = false
  totalcpu = true
  [inputs.cpu.tags]
    index = "cpu_metrics"

Using with the File output

You can use the file output when running telegraf on a machine with a Splunk forwarder.

A sample event when hec_routing is false (or unset) looks like:

{
    "_value": 0.6,
    "cpu": "cpu0",
    "dc": "mobile",
    "metric_name": "cpu.usage_user",
    "user": "ronnocol",
    "time": 1529708430
}

Data formatted in this manner can be ingested with a simple props.conf file that looks like this:

[telegraf]
category = Metrics
description = Telegraf Metrics
pulldown_type = 1
DATETIME_CONFIG =
NO_BINARY_CHECK = true
SHOULD_LINEMERGE = true
disabled = false
INDEXED_EXTRACTIONS = json
KV_MODE = none
TIMESTAMP_FIELDS = time

An example configuration of a file based output is:

 # Send telegraf metrics to file(s)
[[outputs.file]]
   ## Files to write to, "stdout" is a specially handled file.
   files = ["/tmp/metrics.out"]

   ## Data format to output.
   ## Each data format has its own unique set of configuration options, read
   ## more about them here:
   ## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md
   data_format = "splunkmetric"
   splunkmetric_hec_routing = false
   splunkmetric_multimetric = true

Non-numeric metric values

Splunk supports only numeric field values, so serializer would silently drop metrics with the string values. For some cases it is possible to workaround using ENUM processor. Example, provided below doing this for the docker_container_health.health_status metric:

# splunkmetric does not support sting values
[[processors.enum]]
  namepass = ["docker_container_health"]
  [[processors.enum.mapping]]
    ## Name of the field to map
    field = "health_status"
    [processors.enum.mapping.value_mappings]
    starting = 0
    healthy = 1
    unhealthy = 2
    none = 3

Documentation

Index

• func NewSerializer(splunkmetricHecRouting bool, splunkmetricMultimetric bool) (*serializer, error)
• type CommonTags
• type HECTimeSeries

Functions

func NewSerializer

func NewSerializer(splunkmetricHecRouting bool, splunkmetricMultimetric bool) (*serializer, error)

NewSerializer Setup our new serializer

Types

type CommonTags

type CommonTags struct {
	Time   float64
	Host   string
	Index  string
	Source string
	Fields map[string]interface{}
}

type HECTimeSeries

type HECTimeSeries struct {
	Time   float64                `json:"time"`
	Host   string                 `json:"host,omitempty"`
	Index  string                 `json:"index,omitempty"`
	Source string                 `json:"source,omitempty"`
	Fields map[string]interface{} `json:"fields"`
}