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Define observability requirements for stable components #11772

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Dec 16, 2024
109 changes: 109 additions & 0 deletions docs/component-stability.md
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Expand Up @@ -66,6 +66,115 @@ Stable components MUST be compatible between minor versions unless critical secu
component owner MUST provide a migration path and a reasonable time frame for users to upgrade. The same rules from beta
components apply to stable when it comes to configuration changes.

#### Observability requirements
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Stable components should emit enough internal telemetry to let users detect errors, as well as data
loss and performance issues inside the component, and to help diagnose them if possible.

For extension components, this means some way to monitor errors (for example through logs or span
events), and some way to monitor performance (for example through spans or histograms). Because
extensions can be so diverse, the details will be up to the component authors, and no further
constraints are set out in this document.

For pipeline components however, this section details the kinds of values that should be observable
via internal telemetry for all stable components.

> [!NOTE]
> - The following categories MUST all be covered, unless justification is given as to why one may
> not be applicable.
> - However, for each category, many reasonable implementations are possible, as long as the
> relevant information can be derived from the emitted telemetry; everything after the basic
> category description is a recommendation, and is not normative.
> - Of course, a component may define additional internal telemetry which is not in this list.
> - Some of this internal telemetry may already be provided by pipeline auto-instrumentation or
> helper modules (such as `receiverhelper`, `scraperhelper`, `processorhelper`, or
> `exporterhelper`). Please check the documentation to verify which parts, if any, need to be
> implemented manually.

**Definition:** In the following, an "item" refers generically to a single log record, metric point,
or span.

The internal telemetry of a stable pipeline component should allow observing the following:

1. How much data the component receives.

For receivers, this could be a metric counting requests, received bytes, scraping attempts, etc.

For other components, this would typically be the number of items received through the
`Consumer` API.

2. How much data the component outputs.

For exporters, this could be a metric counting requests, sent bytes, etc.

For other components, this would typically be the number of items forwarded to the next
component through the `Consumer` API.

3. How much data is dropped because of errors.
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Per @djaglowski 's RFC here I think this would just be an attribute on the output metric called outcome? I can see the value in having a separate metric for errors, but want to be sure we don't create a divergence from the RFC. Separately, should we link the RFC from Dan to also specify the previously agreed upon naming conventions?

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We probably want to require the use of the RFC's conventions for component-identifying attributes, and I will definitely include using an outcome attribute on the input metric instead of a separate error metric as a recommended implementation for processors.

However, if we want to incentivize contributing external components, I don't think we want to require strict adherence to all of the RFC's choices, so divergences are somewhat inevitable. Relatedly, have you read the "Important note" about the RFC in the PR description? I'm interested in hearing what you think.

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Per @djaglowski 's RFC here I think this would just be an attribute on the output metric called outcome?

That would be the most natural way to go about this. I feel like this document should not be too prescriptive as to how to accomplish the requirements listed, but making a recommendation like this would make sense to me to ensure consistency across components.

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@jade-guiton-dd I hadn't seen that yet, thanks for bringing my attention to it, i think i had only seen the initial description.

I would strongly advise against option 1 as error back propagation is key if you are running a collector in gateway mode and you want to propagate backpressure to an agent. I think options 2 or 3 are sufficient, option 4 feels not prescriptive enough IMO.

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Given this is the recommendation for a component, it makes sense to have the component author use a custom error metric that they can decide to either include or exclude any downstream errors as part of it. (this is what you have written, and i agree with it 😄)

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they can decide to either include or exclude any downstream errors as part of it. (this is what you have written, and i agree with it 😄)

To be clear, the current requirements allow including downstream errors in a custom error metric, but only if there is a way to distinguish them from internal errors.

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yep, this makes sense to me. Thank you! 🙇

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Just to be sure @djaglowski, do you support option 2 I detailed in the PR description, ie. amending the Pipeline Instrumentation RFC to require the implementation to distinguish errors coming directly from the next pipeline component from errors propagated from components further downstream, in order to fit the last paragraph of point 3?

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I think it makes sense in principal, as long as there is a clear mechanism for communicating this information so that instrumentation that is automatically wrapped around components can unambiguously know the correct outcome.


For receivers, this could include a metric counting payloads that could not be parsed in.

For receivers and exporters that interact with an external service, this could include a metric
counting requests that failed because of network errors.

For processors, this could be an `outcome` (`success` or `failure`) attribute on a "received
items" metric defined for point 1.

The goal is to be able to easily pinpoint the source of data loss in the Collector pipeline, so
this should either:
- only include errors internal to the component, or;
- allow distinguishing said errors from ones originating in an external service, or propagated
from downstream Collector components.

4. Details for error conditions.

This could be in the form of logs or spans detailing the reason for an error. As much detail as
necessary should be provided to ease debugging. Processed signal data should not be included for
security and privacy reasons.

5. Other possible discrepancies between input and output, if any. This may include:

- How much data is dropped as part of normal operation (eg. filtered out).
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- How much data is created by the component.

- How much data is currently held by the component, and how much can be held if there is a fixed
capacity.

This would typically be an UpDownCounter keeping track of the size of an internal queue, along
with a gauge exposing the queue's capacity.

6. Processing performance.

This could include spans for each operation of the component, or a histogram of end-to-end
component latency.

The goal is to be able to easily pinpoint the source of latency in the Collector pipeline, so
this should either:
- only include time spent processing inside the component, or;
- allow distinguishing this latency from that caused by an external service, or from time spent
in downstream Collector components.

As an application of this, components which hold items in a queue should allow differentiating
between time spent processing a batch of data and time where the batch is simply waiting in the
queue.

If multiple spans are emitted for a given batch (before and after a queue for example), they
should either belong to the same trace, or have span links between them, so that they can be
correlated.

When measuring amounts of data, it is recommended to use "items" as your unit of measure. Where this
can't easily be done, any relevant unit may be used, as long as zero is a reliable indicator of the
absence of data. In any case, all metrics should have a defined unit (not "1").

All internal telemetry emitted by a component should have attributes identifying the specific
component instance that it originates from. This should follow the same conventions as the
[pipeline universal telemetry](rfcs/component-universal-telemetry.md).

If data can be dropped/created/held at multiple distinct points in a component's pipeline (eg.
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scraping, validation, processing, etc.), it is recommended to define additional attributes to help
diagnose the specific source of the discrepancy, or to define different signals for each.

### Deprecated

The component is planned to be removed in a future version and no further support will be provided. Note that new issues will likely not be worked on. When a component enters "deprecated" mode, it is expected to exist for at least two minor releases. See the component's readme file for more details on when a component will cease to exist.
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