[RFC] data_stream fields

rfcs/text/0000-data_stream-fields.md

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+# 0000: Data stream fields
+<!-- Leave this ID at 0000. The ECS team will assign a unique, contiguous RFC number upon merging the initial stage of this RFC. -->
+
+- Stage: **1 (proposal)** <!-- Update to reflect target stage. See https://elastic.github.io/ecs/stages.html -->
+- Date: **TBD** <!-- The ECS team sets this date at merge time. This is the date of the latest stage advancement. -->
+
+When introducing the new indexing strategy for Elastic Agent which uses data streams, we found that adding a few "constant_keyword" fields corresponding to the central components in the new indexing strategy would be advantageous. 
+
+
+<!--
+As you work on your RFC, use the "Stage N" comments to guide you in what you should focus on, for the stage you're targeting.
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+
+<!--
+Stage 0: Provide a high level summary of the premise of these changes. Briefly describe the nature, purpose, and impact of the changes. ~2-5 sentences.
+-->
+
+## 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.
+-->
+
+This RFC proposes to introduce a new fieldset called "data_stream". The fieldset consists of the following fields:
+Field     | Mapping type | Description
+----------|--------------|--------------
+data_stream.type | constant_keyword | An overarching type for the data stream. Currently allowed values include "logs", "metrics". We expect to also add "traces" and "synthetics" in the near future
+data_stream.dataset | constant_keyword | The field can contain anything that makes sense to signify the source of the data. Examples include `nginx.access`, `prometheus`, `endpoint` etc. For data streams that otherwise fit, but that do not have dataset set we use the value "generic" for the dataset value. `event.dataset` should have the same value as `data_stream.dataset`. 
+data_stream.namespace | constant_keyword | A user defined namespace. Namespaces are useful to allow grouping of data. Many of our customers already organize their indices this way, and now we are providing this best practice as a default. Many people will use `default` as the value.
+
+In the new indexing strategy, the value of the data stream fields combine to the name of the actual data stream in the following manner `{data_stream.type}-{data_stream.dataset}-{datastream.namespace}`. This means the fields can only contain characters that are valid as part of names of data streams.
+
+data_stream.type is restricted to `logs` or `metrics` for now. 
+
+`data_stream.namespace` and `data_stream.dataset` cannot be longer than 100 bytes and `data_stream.dataset` cannot contain dashes (`-`).
+
+
+<!--
+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.
+-->
+
+<!--
+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.
+-->
+
+## Usage
+
+<!--
+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.
+-->
+
+Data stream fields are already in use in Elastic Agent. Leveraging the data stream fields described here allow users to filter by a specific data type (logs, metrics etc.), dataset (nginx.access, prometheus) or namespace. The following are examples of common queries pertaining to specific datatypes, datasets or namespaces:
+
+* `data_stream.type: logs`
+* `data_stream.dataset: nginx.access`
+* `data_stream.type: logs AND data_stream.namespace: web-frontend`
+
+Because the fields are mapped as `constant_keyword`, Elasticsearch can quickly exclude indices which are irrelevant for the query. See the [Elasticsearch documentation](https://www.elastic.co/guide/en/elasticsearch/reference/current/faster-filtering-with-constant-keyword.html) on `contant_keyword` for more information.
+
+
+
+## Source data
+
+<!--
+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.
+-->
+
+Today, Elastic Agent adds the the data_stream fields in all documents ingested. It's also possible to use the fields in data from other data sources. Elasticsearch 7.9+ ships with built-in index template mappings which will ensure that documents indexed into data streams that match `logs-*-*` and `metrics-*-*` will get the fields mapped correclty to `constant_keyword` types. 
+
+### Using data_stream fields with regular indices
+`data_stream` fields only make sense when indexing into data streams. They should not to be used for regular indices.
+
+
+<!--
+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.
+-->
+
+<!--
+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
+
+<!--
+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.
+-->
+### Relation to event.* fields
+Concerns have been raised about how these fields relate to the event fields. Specifically, event.type, event.kind, event.category etc. We didn't find a way to square this concern at the time and it was decided to move forward with the data_stream fields for now and consider them to be unrelated to the event fields. event.dataset and data_stream.dataset, however, should contain the same value.
+
+<!--
+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
+
+<!--
+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.
+-->
+
+Elastic Agent already uses the data_stream fields. 
+
+Additionally, as previously described, beginning in version 7.9, Elasticsearch ships with built-in index templates for data streams which will automatically ensure that data_stream fields get correclty mapped when the data stream name match `logs-*-*` and `metrics-*-*`.
+
+
+## People
+
+The following are the people that consulted on the contents of this RFC.
+
+* @roncohen | author, sponsor
+* @ruflin | subject matter expert
+
+
+<!--
+Who will be or has consulted on the contents of this RFC? Identify authorship and sponsorship, and optionally identify the nature of involvement of others. Link to GitHub aliases where possible. This list will likely change or grow stage after stage.
+
+e.g.:
+
+* @Yasmina | author
+* @Monique | sponsor
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+* @Mariana
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+
+
+## References
+
+<!-- Insert any links appropriate to this RFC in this section. -->
+
+### RFC Pull Requests
+
+<!-- An RFC should link to the PRs for each of it stage advancements. -->
+
+* Stage 1: https://github.com/elastic/ecs/pull/980
+
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