x-pack/metricbeat/module/gcp: CrossSeriesReducer Support

[Linu-Elias]

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Related issues

• Closes [GCP] Add CrossSeriesReducer support in ListTimeSeries request #41045

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[mergify]

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[elasticmachine]

Pinging @elastic/obs-ds-hosted-services (Team:obs-ds-hosted-services)

[gpop63]

I noticed that labels are omitted when using reducers due to data aggregation across multiple time series, but using GroupBy with specific fields might fix this issue. Without labels not sure how useful using a reducer would be.

[mergify]

This pull request is now in conflicts. Could you fix it? 🙏
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git fetch upstream
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git merge upstream/main
git push upstream gcp_reducer_support

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[gpop63]

I did a bit of testing on this will leave here some notes.

When we're fetching time series data and we apply a CrossSeriesReducer like REDUCE_SUM, REDUCE_MEAN, etc., it combines multiple time series into fewer ones or even a single one. By default, if we don't specify GroupByFields, the reducer will aggregate all the time series together, and we lose all the labels like zone, instance_id, project_id.

Example without GroupByFields:

We have CPU usage metrics from multiple instances across different zones. We apply a REDUCE_SUM without any GroupByFields. All CPU usage data is summed up into a single time series. We lose visibility into which data came from which zone or instance because the labels are not preserved.

Example with GroupByFields:

Same as above. We apply a REDUCE_SUM and set GroupByFields to ["resource.labels.zone", "resource.labels.instance_id"]. The reducer sums up CPU usage separately for each zone and instance. We retain the zone and instance_id labels in the results, so we can see the aggregated data per zone and per instance.

So I believe we have to expose GroupByFields in the config and allow users to specify by which labels they want to group the data.

[Linu-Elias]

I agree with @gpop63, Additionally I have observed that we only receive the labels explicitly specified in the GroupByFields along with project_id.

For example, if GroupByFields is set to only resource labels such as resource.labels.instance_id, the ListTimeSeries() will return the timeseries data without other important labels like resource.labels.zone and metric label metric.labels.instance_name.

Therefore, it's crucial to ensure that all the important labels are included while using GroupByFields in order to group the result based on those labels, So if we plan to expose GroupByFields in the config and allow users to specify by which labels they want to group the data, we also have to mention that that labels they specify will the the ones included in the instance ECS cloud fields.