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Add strawperson (stage 0) Kubernetes RFC (#1209)
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Co-authored-by: Eric Beahan <[email protected]>
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ferozsalam and ebeahan authored Jan 11, 2021
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# 0012: Orchestrator field set creation

- Stage: **0 (strawperson)** <!-- Update to reflect target stage. See https://elastic.github.io/ecs/stages.html -->
- Date: **2021-01-11** <!-- The ECS team sets this date at merge time. This is the date of the latest stage advancement. -->

There is currently no ECS field set for container orchestration engines. There is an example of an ECS
[use-case][0] for Kubernetes, but it largely relies on other ECS field sets, and doesn't cover all of the
potential fields relevant to typical orchestrators. The purpose of this RFC is to propose some improvements to
the existing use-case and then turn it into a full-featured ECS field set, with a larger number of
fields that describe orchestrator-specific primitives which are currently missing (such as cluster names or
resource types, for example).

One use case for this is to allow easier work with [Kubernetes audit logs][1]. Consistent
field definitions will allow teams working with Kubernetes audit logs to share and correlate
data/alerts/visualisations far more easily than currently possible.

There should not be any breaking impact as a result of this change, due to the fact that it should solely
add a new schema rather than change existing material.

## Fields

<!--
Stage 1: Describe at a high level how this change affects fields. Which fieldsets will be impacted? How many fields overall? Are we primarily adding fields, removing fields, or changing existing fields? The goal here is to understand the fundamental technical implications and likely extent of these changes. ~2-5 sentences.
-->

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Stage 2: Include new or updated yml field definitions for all of the essential fields in this draft. While not exhaustive, the fields documented here should be comprehensive enough to deeply evaluate the technical considerations of this change. The goal here is to validate the technical details for all essential fields and to provide a basis for adding experimental field definitions to the schema. Use GitHub code blocks with yml syntax formatting.
-->

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Stage 3: Add or update all remaining field definitions. The list should now be exhaustive. The goal here is to validate the technical details of all remaining fields and to provide a basis for releasing these field definitions as beta in the schema. Use GitHub code blocks with yml syntax formatting.
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## Usage

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Stage 1: Describe at a high-level how these field changes will be used in practice. Real world examples are encouraged. The goal here is to understand how people would leverage these fields to gain insights or solve problems. ~1-3 paragraphs.
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## Source data

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Stage 1: Provide a high-level description of example sources of data. This does not yet need to be a concrete example of a source document, but instead can simply describe a potential source (e.g. nginx access log). This will ultimately be fleshed out to include literal source examples in a future stage. The goal here is to identify practical sources for these fields in the real world. ~1-3 sentences or unordered list.
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<!--
Stage 2: Included a real world example source document. Ideally this example comes from the source(s) identified in stage 1. If not, it should replace them. The goal here is to validate the utility of these field changes in the context of a real world example. Format with the source name as a ### header and the example document in a GitHub code block with json formatting.
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Stage 3: Add more real world example source documents so we have at least 2 total, but ideally 3. Format as described in stage 2.
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## Scope of impact

<!--
Stage 2: Identifies scope of impact of changes. Are breaking changes required? Should deprecation strategies be adopted? Will significant refactoring be involved? Break the impact down into:
* Ingestion mechanisms (e.g. beats/logstash)
* Usage mechanisms (e.g. Kibana applications, detections)
* ECS project (e.g. docs, tooling)
The goal here is to research and understand the impact of these changes on users in the community and development teams across Elastic. 2-5 sentences each.
-->

## Concerns

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Stage 1: Identify potential concerns, implementation challenges, or complexity. Spend some time on this. Play devil's advocate. Try to identify the sort of non-obvious challenges that tend to surface later. The goal here is to surface risks early, allow everyone the time to work through them, and ultimately document resolution for posterity's sake.
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Stage 2: Document new concerns or resolutions to previously listed concerns. It's not critical that all concerns have resolutions at this point, but it would be helpful if resolutions were taking shape for the most significant concerns.
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Stage 3: Document resolutions for all existing concerns. Any new concerns should be documented along with their resolution. The goal here is to eliminate the risk of churn and instability by resolving outstanding concerns.
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Stage 4: Document any new concerns and their resolution. The goal here is to eliminate risk of churn and instability by ensuring all concerns have been addressed.
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## Real-world implementations

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Stage 4: Identify at least one real-world, production-ready implementation that uses these updated field definitions. An example of this might be a GA feature in an Elastic application in Kibana.
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## People

The following are the people that consulted on the contents of this RFC.

* @ferozsalam | author

## References

* [Kubernetes ECS use case][0]
* [Kubernetes audit log documentation][1]

### RFC Pull Requests

<!-- An RFC should link to the PRs for each of it stage advancements. -->

* Stage 0: https://github.com/elastic/ecs/pull/1209

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* Stage 1: https://github.com/elastic/ecs/pull/NNN
...
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[0]: https://github.com/elastic/ecs/blob/master/use-cases/kubernetes.yml
[1]: https://kubernetes.io/docs/tasks/debug-application-cluster/audit/

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