Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[chore] Remove or update mentions to spanmetrics processor #9665

Merged
merged 1 commit into from
Feb 29, 2024
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion docs/design.md
Original file line number Diff line number Diff line change
Expand Up @@ -120,7 +120,7 @@ In the above example `jaeger` exporter will get data from pipeline `traces` and

A pipeline can contain sequentially connected processors. The first processor gets the data from one or more receivers that are configured for the pipeline, the last processor sends the data to one or more exporters that are configured for the pipeline. All processors between the first and last receive the data strictly only from one preceding processor and send data strictly only to the succeeding processor.

Processors can transform the data before forwarding it (i.e. add or remove attributes from spans), they can drop the data simply by deciding not to forward it (this is for example how the `probabilisticsampler` processor works), they can also generate new data. This is how a `spanmetrics` processor can produce metrics for spans processed by the pipeline.
Processors can transform the data before forwarding it (i.e. add or remove attributes from spans), they can drop the data simply by deciding not to forward it (this is for example how the `probabilisticsampler` processor works), they can also generate new data.

The same name of the processor can be referenced in the `processors` key of multiple pipelines. In this case the same configuration will be used for each of these processors however each pipeline will always get its own instance of the processor. Each of these processors will have its own state, the processors are never shared between pipelines. For example if `batch` processor is used in several pipelines each pipeline will have its own batch processor (although each batch processor will be configured exactly the same way if they reference the same key in the configuration). As an example, given the following configuration:

Expand Down
2 changes: 1 addition & 1 deletion docs/processing.md
Original file line number Diff line number Diff line change
Expand Up @@ -57,7 +57,7 @@ expectations.
- Create new metrics based on information in spans, for example to create a duration metric that is not implemented in the SDK yet
- Apply arithmetic between multiple incoming metrics to produce an output one, for example divide an `amount` and a `capacity` to create a `utilization` metric

The processors implementing this use case are `metricsgenerationprocessor`, `spanmetricsprocessor`.
The components implementing this use case are `metricsgenerationprocessor` and the former `spanmetricsprocessor` (now `spanmetricsconnector`).

### Grouping

Expand Down
Loading