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telegrafreceiver

README.md

Telegraf Receiver

Stability level: Beta

Telegraf receiver for ingesting metrics from various input plugins into otc pipeline.

Supported pipeline types: metrics

Use case: user configures telegraf input plugins in config for ingestion and otc processors and exporters for data processing and export.

Configuration

The following settings are required:

  • agent_config: Telegraf config. For now it allows to provide agent and input plugins configuration. One can refer to telegraf configuration docs for full list of configuration options.

The Following settings are optional:

  • separate_field (default value is false): Specify whether metric field should be added separately as data point label.
  • consume_retry_delay (default value is 500ms): The retry delay for recoverable errors from the rest of the pipeline. Don't change this or the related setting below unless you know what you're doing.
  • consume_max_retries (default value is 10): The maximum number of retries for recoverable errors from the rest of the pipeline.

Example:

receivers:
  telegraf:
    separate_field: false
    agent_config: |
      [agent]
        interval = "2s"
        flush_interval = "3s"
      [[inputs.mem]]

The full list of settings exposed for this receiver are documented in config.go.

Limitations

With its current implementation Telegraf receiver has the following limitations:

  • only input plugins can be configured in telegraf agent confugration section (apart from agent's configuration itself). That means that metrics go straight from input plugin to the receiver for translation (into otc data model) without any processing
  • only the following Telegraf metric data types are supported:
    • telegraf.Gauge that is translated to pmetric.MetricDataTypeGauge,
    • telegraf.Counter that is translated to pmetric.MetricDataTypeSum.

Migration from Telegraf

Data model

Internal OTC metric format differs from the Telegraf one and separate_field controls the conversion:

  • If separate_field is false, the Open Telemetry metric name is going to be concatenated from the Telegraf metric name and the Telegraf field with _ as separator.

    The following telegraf structure:

    {
  "fields": {
    "HeapMemoryUsage.committed": 1007157248
    "HeapMemoryUsage.init": 1007157248
  },
  "name": "tomcat_jmx_jvm_memory",
  "tags": {
    "component": "webserver",
    "environment": "dev",
    "host": "32fafdb10522",
    "jolokia_agent_url": "http://tomcat:8080/jolokia",
    "webserver_system": "tomcat"
  },
  "timestamp": 1646904912
}

    is going to be converted to the following OpenTelemetry structure:

    2022-03-10T07:16:34.117Z  DEBUG loggingexporter/logging_exporter.go:64
ResourceMetrics #0
Resource SchemaURL:
Resource labels:
    -> component: STRING(webserver)
    -> environment: STRING(dev)
    -> host: STRING(32fafdb10522)
    -> jolokia_agent_url: STRING(http://tomcat:8080/jolokia)
    -> webserver_system: STRING(tomcat)
InstrumentationLibraryMetrics #0
InstrumentationLibraryMetrics SchemaURL:
InstrumentationLibrary telegraf v0.1
Metric #0
Descriptor:
    -> Name: tomcat_jmx_jvm_memory_HeapMemoryUsage.committed
    -> Description:
    -> Unit:
    -> DataType: Gauge
NumberDataPoints #0
StartTimestamp: 1970-01-01 00:00:00 +0000 UTC
Timestamp: 2022-03-10 09:35:12 +0000 UTC
Value: 1007157248.000000
Metric #1
Descriptor:
    -> Name: tomcat_jmx_jvm_memory_HeapMemoryUsage.init
    -> Description:
    -> Unit:
    -> DataType: Gauge
NumberDataPoints #0
StartTimestamp: 1970-01-01 00:00:00 +0000 UTC
Timestamp: 2022-03-10 09:35:12 +0000 UTC
Value: 1007157248.000000

  • If separate_fields is true, the Open Telemetry metric name is going to be the same as the Telegraf one, and the Telegraf field is going to be converted to the Open Telemetry data point attribute.

    The following telegraf structure:

    {
  "fields": {
    "HeapMemoryUsage.committed": 1007157248
    "HeapMemoryUsage.init": 1007157248
  },
  "name": "tomcat_jmx_jvm_memory",
  "tags": {
    "component": "webserver",
    "environment": "dev",
    "host": "32fafdb10522",
    "jolokia_agent_url": "http://tomcat:8080/jolokia",
    "webserver_system": "tomcat"
  },
  "timestamp": 1646904912
}

    is going to be converted to the following OpenTelemetry structure:

    2022-03-10T11:28:30.333Z  DEBUG loggingexporter/logging_exporter.go:64
ResourceMetrics #0
Resource SchemaURL:
Resource labels:
    -> component: STRING(webserver)
    -> environment: STRING(dev)
    -> host: STRING(32fafdb10522)
    -> jolokia_agent_url: STRING(http://tomcat:8080/jolokia)
    -> webserver_system: STRING(tomcat)
InstrumentationLibraryMetrics #0
InstrumentationLibraryMetrics SchemaURL:
InstrumentationLibrary
Metric #0
Descriptor:
    -> Name: tomcat_jmx_jvm_memory
    -> Description:
    -> Unit:
    -> DataType: Gauge
NumberDataPoints #0
Data point attributes:
    -> field: STRING(HeapMemoryUsage.committed)
StartTimestamp: 1970-01-01 00:00:00 +0000 UTC
Timestamp: 2022-03-10 09:35:12 +0000 UTC
Value: 1007157248.000000
Metric #1
Descriptor:
    -> Name: tomcat_jmx_jvm_memory
    -> Description:
    -> Unit:
    -> DataType: Gauge
NumberDataPoints #0
Data point attributes:
    -> field: STRING(HeapMemoryUsage.init)
StartTimestamp: 1970-01-01 00:00:00 +0000 UTC
Timestamp: 2022-03-10 09:35:12 +0000 UTC
Value: 1007157248.000000

Keep compatibility while sending metrics to Sumo Logic

In Telegraf, metrics can be sent to Sumo Logic using Sumologic Output Plugin. It supports three formats (prometheus, carbon2, graphite), where each of them has some limitations (e.g. only specific set of chars can be used for metric name for prometheus).

OTLP doesn't have most of those limitations, so in order to keep the same metric names, some transformations should be done by processors.

Let's consider the following example. metric.with.dots is going to be sent as metric_with_dots by prometheus or metric.with.dots by OTLP. To unify it, you can use the Metrics Transform Processor:

processors:
  metricstransform:
    transforms:
      ## Replace metric.with.dots metric to metric_with_dots
      - include: metric.with.dots
        match_type: strict
        action: update
        new_name: metric_with_dots
# ...
service:
  pipelines:
    metrics:
      receivers:
        - telegraf
      processors:
        - metricstransform
      exporters:
        - sumologic
# ...

With Metrics Transform Processor and regular expressions you can also handle more complex scenarios, like in the following snippet:

processors:
  metricstransform:
    transforms:
      ## Change <part1>.<part2> metrics to to <part1>_<part2>
      - include: ^([^\.]*)\.([^\.]*)$$
        match_type: strict
        action: update
        new_name: $${1}.$${2}
      ## Change <part1>.<part2>.<part3> metrics to to <part1>_<part2>_<part3>
      - include: ^([^\.]*)\.([^\.]*)\.([^\.]*)$$
        match_type: strict
        action: update
        new_name: $${1}.$${2}.${3}
# ...
service:
  pipelines:
    metrics:
      receivers:
        - telegraf
      processors:
        - metricstransform
      exporters:
        - sumologic
# ...