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[8.12] [Request][REDO] Add warning against using ES|QL on production environmentsFirst draft (backport #4554) #4555

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[8.12] [Request][REDO] Add warning against using ES|QL on production environmentsFirst draft (backport #4554) #4555

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2 changes: 1 addition & 1 deletion docs/assistant/security-assistant.asciidoc
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Expand Up @@ -178,7 +178,7 @@ The *Show anonymized* toggle controls whether you see the obfuscated or plaintex
[discrete]
[[ai-assistant-knowledge-base]]
=== Knowledge base
beta::[]
beta::["Do not use {esql} on production environments. This functionality is in beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features."]

The **Knowledge base** tab of the AI Assistant settings menu allows you to enable retrieval-augmented generation so that AI Assistant can answer questions about the Elastic Search Query Language ({esql}), or about alerts in your environment.

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2 changes: 1 addition & 1 deletion docs/detections/about-rules.asciidoc
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Expand Up @@ -44,7 +44,7 @@ TIP: You can also use value lists as the indicator match index. See <<indicator-

* <<create-esql-rule, *ES|QL*>>: Searches the defined indices and creates an alert when results match an {ref}/esql.html[Elasticsearch Query Language (ES|QL)] query.
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preview::[]
preview::["Do not use {esql} on production environments. This functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features."]

[role="screenshot"]
image::images/all-rules.png[Shows the Rules page]
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2 changes: 1 addition & 1 deletion docs/detections/api/rules/rules-api-create.asciidoc
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Expand Up @@ -39,7 +39,7 @@ mappings should be {ecs-ref}[ECS-compliant].
* *New terms*: Generates an alert for each new term detected in source documents within a specified time range.
* *{esql}*: Uses {ref}/esql.html[Elasticsearch Query Language ({esql})] to find events and aggregate search results.
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preview::[]
preview::["Do not use {esql} on production environments. This functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features."]
* *{ml-cap} rules*: Creates an alert when a {ml} job discovers an anomaly above
the defined threshold (see <<machine-learning>>).

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2 changes: 1 addition & 1 deletion docs/detections/rules-ui-create.asciidoc
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Expand Up @@ -274,7 +274,7 @@ For example, if a rule has an interval of 5 minutes, no additional look-back tim
[[create-esql-rule]]
=== Create an {esql} rule

preview::[]
preview::["Do not use {esql} on production environments. This functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features."]

Use {ref}/esql.html[{esql}] to query your source events and aggregate event data. Query results are returned in a table with rows and columns. Each row becomes an alert.

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2 changes: 1 addition & 1 deletion docs/events/timeline-ui-overview.asciidoc
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Expand Up @@ -196,7 +196,7 @@ From the *Correlation* tab, you can also do the following:
[[esql-in-timeline]]
== Use {esql} to investigate events

preview::[]
preview::["Do not use {esql} on production environments. This functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features."]

The {ref}/esql.html[Elasticsearch Query Language ({esql})] provides a powerful way to filter, transform, and analyze event data stored in {es}. {esql} queries use "pipes" to manipulate and transform data in a step-by-step fashion. This approach allows you to compose a series of operations, where the output of one operation becomes the input for the next, enabling complex data transformations and analysis.

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