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Metricstarttime Processor

Status Available in: contrib Maintainers: @dashpole, @ridwanmsharif Source: opentelemetry-collector-contrib

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Supported Telemetry

Metrics

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Overview

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Configuration

The processor will work without configuring any settings, but the following options are supported:
  • strategy (default true_reset_point): Specifies which strategy to use. Valid values are true_reset_point, subtract_initial_point, and start_time_metric. See below for how each strategy works.
  • gc_interval (default 10m): Defines the interval to check if any resources have not emitted data since the last check. If a resource has not emitted any data, it is removed from the cache to free up memory. Any additional data from resources removed from the cache will be given a new start time.
  • start_time_metric_regex: Allows specifying a regex for a metric name containing the start time for a resource. This option is only supported when the strategy is start_time_metric, and if unset, the process_start_time metric is used.
Example configurations: 
processors:
  metric_start_time:

processors:
  metric_start_time:
    strategy: start_time_metric
    gc_interval: 1h
    start_time_metric_regex: "^.+_start_time$"

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Strategy: True Reset Point

The true_reset_point strategy handles missing start times for cumulative points by producing a stream of points that starts with a True Reset Point. The true reset point has its start time set to its end timestamp. It is meant to indicate the absolute value of the cumulative point when the collector first observed it. Subsequent points re-use the start timestamp of the initial True Reset point. Pros:
  • The absolute value of the cumulative metric is preserved.
  • It is possible to calculate the correct rate between any two points since the timestamps and values are not modified.
Cons:
  • This strategy is stateful because the initial True Reset point is necessary to properly calculate rates on subsequent points.
  • The True Reset point doesn’t make sense semantically. It has a zero duration, but non-zero values.
  • Many backends reject points with equal start and end timestamps.
    • If the True Reset point is rejected, the next point will appear to have a very large rate.

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Strategy: Subtract Initial Point

The subtract_initial_point strategy handles missing start times for cumulative points by dropping the first point in a cumulative series, “subtracting” that point’s value from subsequent points and using the initial point’s timestamp as the start timestamp for subsequent points. Pros:
  • Cumulative semantics are preserved. This means that for a point with a given [start, end] interval, the cumulative value occurred in that interval.
  • Rates over resulting timeseries are correct, even if points are lost. This strategy is not stateful.
Cons:
  • The absolute value of counters is modified. This is generally not an issue, since counters are usually used to compute rates.
  • The initial point is dropped, which loses information.

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Strategy: Start Time Metric

The start_time_metric strategy handles missing start times by looking for the process_start_time metric, which is commonly supported by Prometheus exporters. If found, it uses the value of the process_start_time metric as the start time for all other cumulative points in the batch of metrics. Use the start_time_metric_regex configuration option to change the name of the metric used for the start time. If the start time metric is not found, it falls back to the time at which the collector started. This strategy should only be used in limited circumstances:
  • When your application has a metric with the start time in Unix nanoseconds, such as process_start_time.
  • The metric_start_time processor is used before any batching, so that the batch of metrics all originate from a single application.
  • This strategy can be used when the collector is run as a sidecar to the application, where the collector’s start time is a good approximation of the application’s start time.
Cons:
  • If the collector’s start time is used as a fallback and the collector restarts, it can produce rates that are incorrect and higher than expected.
  • The process’ start time isn’t the time at which individual instruments or timeseries are initialized. It may result in lower rates if the first observation is significantly later than the process’ start time.

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Configuration

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Example Configuration

metric_start_time:

metric_start_time/subtract_initial_point:
  strategy: subtract_initial_point

metric_start_time/gc_interval:
  gc_interval: 1h

metric_start_time/negative_interval:
  gc_interval: -1h

metric_start_time/true_reset_point:
  strategy: true_reset_point

metric_start_time/start_time_metric:
  strategy: start_time_metric
  start_time_metric_regex: "^.+_process_start_time_seconds$"

metric_start_time/invalid_regex:
  strategy: start_time_metric
  start_time_metric_regex: "(((("

metric_start_time/invalid_strategy:
  strategy: bad

metric_start_time/regex_with_subtract_initial_point:
  strategy: subtract_initial_point
  start_time_metric_regex: "^.+_process_start_time_seconds$"
Last generated: 2026-04-13