Is your feature request related to a problem? Please describe.

I’m interested in implementing custom metrics like:

• Processing time for a request, which would be a float value (e.g., 60.0s).
  

• HTTP status code for a request, represented as an integer (e.g., 2XX, 5XX).
  

There are additional scenario-specific metrics I’d like to track as well(eg. token-usage etc.).

For my use case here I won't be able to use any of the available custom metric type like gauge, counter etc as counter would just keep a single value which is the current count which can be incremented or decremented, so I would not be able to keep multiple values/entries like for HTTP Code or processing times & the same goes for gauge which can be set to a certain value & when updated that values gets updated to a new value. Gauge can be useful for a metric like health status (viz Good & Bad) & counter would be useful for showing the current count of request processed or similar.

Describe the solution you'd like

Checking the source code of gauge and counter helps me understand that both utilize a
a variable with maybe int or float type.
After looking at the source code of all available metrics, I think none of them can be utilized to store and send list-like (timeseries/multiple values, like this [200,500,200,400,512] ) values. Histogram has self._counts which is of type list, but it saves frequency and not the actual value itself.

I was hoping that I could extend the BaseMetric class to create a metric which stores values in a list or dict like datastructure to be able to hold timeseries like data.

class ProcessingTime(BaseMetric):
    __slots__ = BaseMetric.__slots__ + ("_data",)

    def __init__(self, name, reset_on_collect=False) -> None:
        """
        Creates a new ProcessingTime metric.
        
        :param name: Label of the metric.
        :param reset_on_collect: Flag to reset the values when collected.
        """
        super(ProcessingTime, self).__init__(name, reset_on_collect=reset_on_collect)
        self._data = {}

    def add_video(self, video_id: str, processing_time: float) -> None:
        """
        Adds processing time for a given video ID.
        
        :param video_id: Alphanumeric ID of the video processed.
        :param processing_time: Processing time in seconds.
        """
        if not isinstance(video_id, str) or not video_id:
            raise ValueError("Video ID must be a non-empty string.")
        if not isinstance(processing_time, (int, float)):
            raise ValueError("Processing time must be a numeric value.")
        self._data[video_id] = float(processing_time)

How would I go about doing that ?
Also If this is something that would be helpful to the community maybe we can a add new metric type.

Also I would appreciate a more detailed guide or additional examples on how to effectively implement and use custom metrics in Python applications.

Describe alternatives you've considered

I don't want to have transactions & spans, but metrics so that I can plot a graph, currently I have achieved this by sending extra parameters in log & indexing them & then plotting them logger.info("Example message!", extra={"processing_time": 30.0}). But this method is slow & due to storage constraints I can't store historical data of longer periods(>5 days in my case).

Additional context

Please have a look at this conversation at elastic discussion forum which prompted this feature request.