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Support custom metric types (e.g. datadog "distributions") #46
Support custom metric types (e.g. datadog "distributions") #46
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Would really love to have Distribution metrics too! 😍 Unfortunately the maintainer hasn't been very responsive in this repo, e.g. no reply in this issue from a year ago. Not blaming at all, life happens and no one is obliged to support this library. @lexmag do you think this is something that could be added to Statix? |
Will you open the MR @bforchhammer or shall I give it a try? Really keen on having this available. Thanks all for your contributions and push for this. ❤️ |
Example of usage follows: iex> MyApp.Statix.distribution("rendering", 12, []) :ok From the Datadog documentation: > Unlike the HISTOGRAM metric type, which aggregates on the Agent during a given time interval, a DISTRIBUTION metric sends all the raw data during a time interval to Datadog, and aggregations occur server-side. Because the underlying data structure represents raw, unaggregated data, distributions provide two major features: > > - Calculation of percentile aggregations > - Customization of tagging https://docs.datadoghq.com/developers/metrics/types/?tab=distribution#definition Closes lexmag#46
Example of usage follows: iex> MyApp.Statix.distribution("rendering", 12, []) :ok From the Datadog documentation: > Unlike the HISTOGRAM metric type, which aggregates on the Agent during a given time interval, a DISTRIBUTION metric sends all the raw data during a time interval to Datadog, and aggregations occur server-side. Because the underlying data structure represents raw, unaggregated data, distributions provide two major features: > > - Calculation of percentile aggregations > - Customization of tagging https://docs.datadoghq.com/developers/metrics/types/?tab=distribution#definition Closes lexmag#46
@dnlserrano Well, looks like you found some time over the weekend! Awesome, thanks for the PR! ❤️ |
Example of usage follows: iex> MyApp.Statix.distribution("rendering", 12, []) :ok From the Datadog documentation: > Unlike the HISTOGRAM metric type, which aggregates on the Agent during a given time interval, a DISTRIBUTION metric sends all the raw data during a time interval to Datadog, and aggregations occur server-side. Because the underlying data structure represents raw, unaggregated data, distributions provide two major features: > > - Calculation of percentile aggregations > - Customization of tagging https://docs.datadoghq.com/developers/metrics/types/?tab=distribution#definition Closes lexmag#46
Example of usage follows: iex> MyApp.Statix.distribution("rendering", 12, []) :ok From the Datadog documentation: > Unlike the HISTOGRAM metric type, which aggregates on the Agent during a given time interval, a DISTRIBUTION metric sends all the raw data during a time interval to Datadog, and aggregations occur server-side. Because the underlying data structure represents raw, unaggregated data, distributions provide two major features: > > - Calculation of percentile aggregations > - Customization of tagging https://docs.datadoghq.com/developers/metrics/types/?tab=distribution#definition Closes lexmag#46
Example of usage follows: iex> MyApp.Statix.distribution("rendering", 12, []) :ok From the Datadog documentation: > Unlike the HISTOGRAM metric type, which aggregates on the Agent during a given time interval, a DISTRIBUTION metric sends all the raw data during a time interval to Datadog, and aggregations occur server-side. Because the underlying data structure represents raw, unaggregated data, distributions provide two major features: > > - Calculation of percentile aggregations > - Customization of tagging https://docs.datadoghq.com/developers/metrics/types/?tab=distribution#definition Closes lexmag#46
Example of usage follows: iex> MyApp.Statix.distribution("rendering", 12, []) :ok From the Datadog documentation: > Unlike the HISTOGRAM metric type, which aggregates on the Agent during a given time interval, a DISTRIBUTION metric sends all the raw data during a time interval to Datadog, and aggregations occur server-side. Because the underlying data structure represents raw, unaggregated data, distributions provide two major features: > > - Calculation of percentile aggregations > - Customization of tagging https://docs.datadoghq.com/developers/metrics/types/?tab=distribution#definition Closes lexmag#46
Example of usage follows: iex> MyApp.Statix.distribution("rendering", 12, []) :ok From the Datadog documentation: > Unlike the HISTOGRAM metric type, which aggregates on the Agent during a given time interval, a DISTRIBUTION metric sends all the raw data during a time interval to Datadog, and aggregations occur server-side. Because the underlying data structure represents raw, unaggregated data, distributions provide two major features: > > - Calculation of percentile aggregations > - Customization of tagging https://docs.datadoghq.com/developers/metrics/types/?tab=distribution#definition Closes lexmag#46
Hi,
We've been happily using statix for our statsd needs (thanks!), and I'd like to play around with the distributions type, which datadog introduced a little while ago. To my understanding, it works by sending metrics with type
d
to the datadog statsd agent.I looked at the code and currently the metric types are hard coded and rather difficult to extend without replacing both
Conn
andPacket
...Maybe something like the following could be supported?
Let me know if this sounds like a reasonable approach; I'd be happy to work on it and provide a pull request!
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