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otel_metrics

The otel_metrics processor serializes a collection of ExportMetricsServiceRequest records sent from the OTel metrics source into a collection of string records.

Usage

To get started, add the following processor to your pipeline.yaml configuration file:

processor:
    - otel_metrics_raw_processor:

{% include copy.html %}

Configuration

You can use the following optional parameters to configure histogram buckets and their default values. A histogram displays numerical data by grouping data into buckets. You can use histogram buckets to view sets of events that are organized by the total event count and aggregate sum for all events. For more detailed information, see OpenTelemetry Histograms.

Parameter	Default value	Description
`calculate_histogram_buckets`	`True`	Whether or not to calculate histogram buckets.
`calculate_exponential_histogram_buckets`	`True`	Whether or not to calculate exponential histogram buckets.
`exponential_histogram_max_allowed_scale`	`10`	Maximum allowed scale in exponential histogram calculation.
`flatten_attributes`	`False`	Whether or not to flatten the `attributes` field in the JSON data.

calculate_histogram_buckets

If calculate_histogram_buckets is not set to false, then the following JSON file will be added to every histogram JSON. If flatten_attributes is set to false, the JSON string format of the metrics does not change the attributes field. If flatten_attributes is set to true, the values in the attributes field are placed in the parent JSON object. The default value is true. See the following JSON example:

 "buckets": [
    {
      "min": 0.0,
      "max": 5.0,
      "count": 2
    },
    {
      "min": 5.0,
      "max": 10.0,
      "count": 5
    }
  ]

You can create detailed representations of histogram buckets and their boundaries. You can control this feature by using the following parameters in your pipeline.yaml file:

  processor:
    - otel_metrics_raw_processor:
        calculate_histogram_buckets: true
        calculate_exponential_histogram_buckets: true
        exponential_histogram_max_allowed_scale: 10
        flatten_attributes: false

{% include copy.html %}

Each array element describes one bucket. Each bucket contains the lower boundary, upper boundary, and its value count. This is a specific form of more detailed OpenTelemetry representation that is a part of the JSON output created by the otel_metrics processor. See the following JSON file, which is added to each JSON histogram by the otel_metrics processor:

 "explicitBounds": [
    5.0,
    10.0
  ],
   "bucketCountsList": [
    2,
    5
  ]

calculate_exponential_histogram_buckets

If calculate_exponential_histogram_buckets is set to true (the default setting), the following JSON values are added to each JSON histogram:


    "negativeBuckets": [
        {
        "min": 0.0,
        "max": 5.0,
        "count": 2
        },
        {
        "min": 5.0,
        "max": 10.0,
        "count": 5
        }
    ],
...
    "positiveBuckets": [
        {
        "min": 0.0,
        "max": 5.0,
        "count": 2
        },
        {
        "min": 5.0,
        "max": 10.0,
        "count": 5
        }
    ],

The following JSON file is a more detailed form of OpenTelemetry representation that consists of negative and positive buckets, a scale parameter, an offset, and a list of bucket counts:

    "negative": [
        1,
        2,
        3
    ],
    "positive": [
        1,
        2,
        3
    ],
    "scale" : -3,
    "negativeOffset" : 0,
    "positiveOffset" : 1

exponential_histogram_max_allowed_scale

The exponential_histogram_max_allowed_scale parameter defines the maximum allowed scale for an exponential histogram. If you increase this parameter, you will increase potential memory consumption. See the OpenTelemetry specifications for more information on exponential histograms and their computational complexity.

All exponential histograms that have a scale that is above the configured parameter (by default, a value of 10) are discarded and logged with an error level. You can check the log that Data Prepper creates to see the ERROR log message.

The absolute scale value is used for comparison, so a scale of -11 that is treated equally to 11 exceeds the configured value of 10 and can be discarded. {: .note}

Metrics

The following table describes metrics that are common to all processors.

Metric name	Type	Description
`recordsIn`	Counter	Metric representing the number of ingress records.
`recordsOut`	Counter	Metric representing the number of egress records.
`timeElapsed`	Timer	Metric representing the time elapsed during execution of records.

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