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3 changes: 2 additions & 1 deletion explore-analyze/ai-assistant.md
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---
navigation_title: AI assistants
mapped_pages:
- https://www.elastic.co/guide/en/kibana/current/search-ai-assistant.html
- https://www.elastic.co/guide/en/observability/current/obs-ai-assistant.html
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- id: cloud-serverless
---

# AI assistant
# AI assistants in {{kib}}

$$$token-limits$$$

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---
navigation_title: Common issues
mapped_pages:
- https://www.elastic.co/guide/en/kibana/current/alerting-common-issues.html
applies_to:
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- id: kibana
---

# Common Issues [alerting-common-issues]
# Common issues with {{kib}} alerting [alerting-common-issues]

This page describes how to resolve common problems you might encounter with Alerting.

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---
navigation_title: Create and manage rules
mapped_pages:
- https://www.elastic.co/guide/en/kibana/current/create-and-manage-rules.html
applies_to:
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- id: kibana
---

# Create and manage rules [create-and-manage-rules]
# Create and manage alerting rules with {{kib}} [create-and-manage-rules]

The **{{stack-manage-app}}** > **{{rules-ui}}** UI provides a cross-app view of alerting. Different {{kib}} apps like [**{{observability}}**](../../../solutions/observability/incident-management/alerting.md), [**Security**](detection-rules://index.md), [**Maps**](geo-alerting.md) and [**{{ml-app}}**](../../machine-learning/machine-learning-in-kibana.md) can offer their own rules.

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3 changes: 2 additions & 1 deletion explore-analyze/alerts-cases/cases.md
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---
navigation_title: Cases
mapped_pages:
- https://www.elastic.co/guide/en/kibana/current/cases.html
applies_to:
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- id: kibana
---

# Cases [cases]
# Cases in {{kib}} [cases]

Cases are used to open and track issues directly in {{kib}}. You can add assignees and tags to your cases, set their severity and status, and add alerts, comments, and visualizations. You can create cases automatically when alerts occur or send cases to external incident management systems by configuring connectors.

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---
navigation_title: Manage case settings
mapped_pages:
- https://www.elastic.co/guide/en/kibana/current/manage-cases-settings.html
applies_to:
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- id: kibana
---

# Configure case settings [manage-cases-settings]
# Manage case settings in {{kib}} [manage-cases-settings]

To change case closure options and add custom fields, templates, and connectors for external incident management systems, go to **{{stack-manage-app}} > Cases** and click **Settings**.

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3 changes: 2 additions & 1 deletion explore-analyze/alerts-cases/cases/manage-cases.md
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---
navigation_title: Open and manage cases
mapped_pages:
- https://www.elastic.co/guide/en/kibana/current/manage-cases.html
applies_to:
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- id: kibana
---

# Open and manage cases [manage-cases]
# Open and manage cases in {{kib}} [manage-cases]

To perform these tasks, you must have [full access](setup-cases.md) to the appropriate case features in {{kib}}.

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3 changes: 2 additions & 1 deletion explore-analyze/alerts-cases/cases/setup-cases.md
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---
navigation_title: Configure access to cases
mapped_pages:
- https://www.elastic.co/guide/en/kibana/current/setup-cases.html
applies_to:
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- id: kibana
---

# Configure access to cases [setup-cases]
# Configure access to cases in {{kib}} [setup-cases]

To access cases in **{{stack-manage-app}}**, you must have the appropriate {{kib}} privileges:

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- id: elasticsearch
---

# Limitations [watcher-limitations]
# Watcher limitations [watcher-limitations]

## Watches are not updated when file based scripts change [_watches_are_not_updated_when_file_based_scripts_change]

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3 changes: 2 additions & 1 deletion explore-analyze/dashboards.md
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---
navigation_title: Dashboards
mapped_pages:
- https://www.elastic.co/guide/en/kibana/current/dashboard.html
applies_to:
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- id: kibana
---

# Dashboards [dashboard]
# {{kib}} dashboards [dashboard]

Dashboards are the best way to visualize and share insights from your {{es}} data.

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3 changes: 2 additions & 1 deletion explore-analyze/machine-learning/anomaly-detection.md
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---
navigation_title: Anomaly detection
mapped_pages:
- https://www.elastic.co/guide/en/machine-learning/current/ml-ad-overview.html
- https://www.elastic.co/guide/en/kibana/current/xpack-ml-anomalies.html
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- id: kibana
---

# Anomaly detection [ml-ad-overview]
# Anomaly detection with machine learning [ml-ad-overview]

You can use {{stack}} {{ml-features}} to analyze time series data and identify anomalous patterns in your data set.

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---
navigation_title: Advanced concepts
mapped_pages:
- https://www.elastic.co/guide/en/machine-learning/current/ml-ad-concepts.html
applies_to:
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- id: machine-learning
---

# Advanced concepts [ml-ad-concepts]
# Advanced concepts for anomaly detection [ml-ad-concepts]

This section explains the more complex concepts of the Elastic {{ml}} {{anomaly-detect}} feature.

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---
navigation_title: Resources
mapped_pages:
- https://www.elastic.co/guide/en/machine-learning/current/ml-ad-resources.html
applies_to:
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- id: machine-learning
---

# Resources [ml-ad-resources]
# Resources for anomaly detection [ml-ad-resources]

This section contains further resources for using {{anomaly-detect}}.

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---
navigation_title: API quick reference
mapped_pages:
- https://www.elastic.co/guide/en/machine-learning/current/ml-api-quickref.html
applies_to:
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- id: machine-learning
---

# API quick reference [ml-api-quickref]
# Anomaly detection API quick reference [ml-api-quickref]

All {{ml}} {{anomaly-detect}} endpoints have the following base:

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---
navigation_title: Analysis function reference
mapped_pages:
- https://www.elastic.co/guide/en/machine-learning/current/ml-functions.html
applies_to:
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- id: machine-learning
---

# Function reference [ml-functions]
# Machine learning analysis function reference [ml-functions]

The {{ml-features}} include analysis functions that provide a wide variety of flexible ways to analyze data for anomalies.

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- id: machine-learning
---

# Limitations [ml-limitations]
# Anomaly detection limitations [ml-limitations]

The following limitations and known problems apply to the {{version.stack}} release of the Elastic {{ml-features}}. The limitations are grouped into four categories:

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---
navigation_title: Advanced concepts
mapped_pages:
- https://www.elastic.co/guide/en/machine-learning/current/ml-dfa-concepts.html
applies_to:
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- id: machine-learning
---

# Advanced concepts [ml-dfa-concepts]
# Advanced concepts for data frame analytics [ml-dfa-concepts]

This section explains the more complex concepts of the Elastic {{ml}} {{dfanalytics}} feature.

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- id: machine-learning
---

# Limitations [ml-dfa-limitations]
# Data frame analytics limitations [ml-dfa-limitations]

The following limitations and known problems apply to the {{version.stack}} release of the Elastic {{dfanalytics}} feature. The limitations are grouped into the following categories:

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- id: machine-learning
---

# Overview [ml-dfa-overview]
# Overview of data frame analytics with Elastic machine learning [ml-dfa-overview]

{{dfanalytics-cap}} enable you to perform different analyses of your data and annotate it with the results. By doing this, it provides additional insights into the data. [{{oldetection-cap}}](ml-dfa-finding-outliers.md) identifies unusual data points in the data set. [{{regression-cap}}](ml-dfa-regression.md) makes predictions on your data after it determines certain relationships among your data points. [{{classification-cap}}](ml-dfa-classification.md) predicts the class or category of a given data point in a data set. {{infer-cap}} enables you to use trained {{ml}} models against incoming data in a continuous fashion.

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---
navigation_title: Resources
mapped_pages:
- https://www.elastic.co/guide/en/machine-learning/current/ml-dfa-resources.html
applies_to:
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- id: machine-learning
---

# Resources [ml-dfa-resources]
# Resources for data frame analytics [ml-dfa-resources]

This section contains further resources for using {{dfanalytics}}.

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---
navigation_title: API quick reference
mapped_pages:
- https://www.elastic.co/guide/en/machine-learning/current/ml-dfanalytics-apis.html
applies_to:
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- id: machine-learning
---

# API quick reference [ml-dfanalytics-apis]
# Data frame analytics API quick reference [ml-dfanalytics-apis]

All {{dfanalytics}} endpoints have the following base:

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3 changes: 2 additions & 1 deletion explore-analyze/machine-learning/nlp/ml-nlp-apis.md
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---
navigation_title: API quick reference
mapped_pages:
- https://www.elastic.co/guide/en/machine-learning/current/ml-nlp-apis.html
applies_to:
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- id: machine-learning
---

# API quick reference [ml-nlp-apis]
# NLP API quick reference [ml-nlp-apis]

All the trained models endpoints have the following base:

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3 changes: 2 additions & 1 deletion explore-analyze/machine-learning/nlp/ml-nlp-examples.md
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---
navigation_title: Examples
mapped_pages:
- https://www.elastic.co/guide/en/machine-learning/current/ml-nlp-examples.html
applies_to:
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- id: machine-learning
---

# Examples [ml-nlp-examples]
# Machine learning NLP examples [ml-nlp-examples]

The following pages contain end-to-end examples of how to use the different {{nlp}} tasks in the {{stack}}.

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---
navigation_title: Limitations
mapped_pages:
- https://www.elastic.co/guide/en/machine-learning/current/ml-nlp-limitations.html
applies_to:
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- id: machine-learning
---

# Limitations [ml-nlp-limitations]
# NLP limitations [ml-nlp-limitations]

The following limitations and known problems apply to the {{version.stack}} release of the Elastic {{nlp}} trained models feature.

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3 changes: 2 additions & 1 deletion explore-analyze/machine-learning/nlp/ml-nlp-overview.md
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---
navigation_title: Overview
mapped_pages:
- https://www.elastic.co/guide/en/machine-learning/current/ml-nlp-overview.html
applies_to:
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- id: machine-learning
---

# Overview [ml-nlp-overview]
# Overview of NLP with Elastic machine learning [ml-nlp-overview]

{{nlp-cap}} (NLP) refers to the way in which we can use software to understand natural language in spoken word or written text.

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3 changes: 2 additions & 1 deletion explore-analyze/query-filter/tools/playground.md
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---
navigation_title: Playground
mapped_pages:
- https://www.elastic.co/guide/en/serverless/current/elasticsearch-playground.html
applies_to:
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- id: cloud-serverless
---

# Playground [elasticsearch-playground]
# Search Playground for {{es}} queries [elasticsearch-playground]

Use the Search Playground to test and edit {{es}} queries visually in the UI. Then use the Chat Playground to combine your {{es}} data with large language models (LLMs) for retrieval augmented generation (RAG). You can also view the underlying Python code that powers the chat interface, and use it in your own application.

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3 changes: 2 additions & 1 deletion explore-analyze/transforms/transform-api-quickref.md
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---
navigation_title: API quick reference
mapped_pages:
- https://www.elastic.co/guide/en/elasticsearch/reference/current/transform-api-quickref.html
applies_to:
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- id: elasticsearch
---

# API quick reference [transform-api-quickref]
# {{transforms-cap}} API quick reference [transform-api-quickref]

All {{transform}} endpoints have the following base:

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2 changes: 1 addition & 1 deletion explore-analyze/transforms/transform-examples.md
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- id: elasticsearch
---

# Examples [transform-examples]
# {{transforms-cap}} examples [transform-examples]

These examples demonstrate how to use {{transforms}} to derive useful insights from your data. All the examples use one of the [{{kib}} sample datasets](/explore-analyze/index.md). For a more detailed, step-by-step example, see [Tutorial: Transforming the eCommerce sample data](ecommerce-transforms.md).

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2 changes: 1 addition & 1 deletion explore-analyze/transforms/transform-limitations.md
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- id: elasticsearch
---

# Limitations [transform-limitations]
# {{transforms-cap}} limitations [transform-limitations]

The following limitations and known problems apply to the {{version.stack}} release of the Elastic {{transform}} feature. The limitations are grouped into the following categories:

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2 changes: 1 addition & 1 deletion explore-analyze/transforms/transform-overview.md
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- id: elasticsearch
---

# Overview [transform-overview]
# {{transforms-cap}} overview [transform-overview]

You can choose either of the following methods to transform your data: [pivot](#pivot-transform-overview) or [latest](#latest-transform-overview).

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