diff --git a/explore-analyze/machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md b/explore-analyze/machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md deleted file mode 100644 index 689aa13aaa..0000000000 --- a/explore-analyze/machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md +++ /dev/null @@ -1,51 +0,0 @@ ---- -mapped_pages: - - https://www.elastic.co/guide/en/kibana/current/xpack-ml-anomalies.html - - https://www.elastic.co/guide/en/serverless/current/observability-aiops-detect-anomalies.html -applies_to: - stack: ga - serverless: ga -products: - - id: kibana - - id: cloud-serverless ---- - -# Anomaly detection [xpack-ml-anomalies] - -The Elastic {{ml}} {{anomaly-detect}} feature automatically models the normal behavior of your time series data — learning trends, periodicity, and more — in real time to identify anomalies, streamline root cause analysis, and reduce false positives. {{anomaly-detect-cap}} runs in and scales with {{es}}, and includes an intuitive UI on the {{kib}} **Machine Learning** page for creating {{anomaly-jobs}} and understanding results. - -If you have a license that includes the {{ml-features}}, you can create {{anomaly-jobs}} and manage jobs and {{dfeeds}} from the **Job Management** pane: - -:::{image} /explore-analyze/images/kibana-ml-job-management.png -:alt: Job Management -:screenshot: -::: - -You can use the **Settings** pane to create and edit calendars and the filters that are used in custom rules: - -:::{image} /explore-analyze/images/kibana-ml-settings.png -:alt: Calendar Management -:screenshot: -::: - -The **Anomaly Explorer** and **Single Metric Viewer** display the results of your {{anomaly-jobs}}. For example: - -:::{image} /explore-analyze/images/kibana-ml-single-metric-viewer.png -:alt: Single Metric Viewer -:screenshot: -::: - -You can optionally add annotations by drag-selecting a period of time in the **Single Metric Viewer** and adding a description. For example, you can add an explanation for anomalies in that time period or provide notes about what is occurring in your operational environment at that time: - -:::{image} /explore-analyze/images/kibana-ml-annotations-list.png -:alt: Single Metric Viewer with annotations -:screenshot: -::: - -In some circumstances, annotations are also added automatically. For example, if the {{anomaly-job}} detects that there is missing data, it annotates the affected time period. For more information, see [Handling delayed data](../anomaly-detection/ml-delayed-data-detection.md). The **Job Management** pane shows the full list of annotations for each job. - -::::{note} -The {{kib}} {{ml-features}} use pop-ups. You must configure your web browser so that it does not block pop-up windows or create an exception for your {{kib}} URL. -:::: - -For more information about the {{anomaly-detect}} feature, see [{{ml-cap}} in the {{stack}}](https://www.elastic.co/what-is/elastic-stack-machine-learning) and [{{ml-cap}} {{anomaly-detect}}](../anomaly-detection.md). diff --git a/explore-analyze/machine-learning/machine-learning-in-kibana/xpack-ml-dfanalytics.md b/explore-analyze/machine-learning/machine-learning-in-kibana/xpack-ml-dfanalytics.md deleted file mode 100644 index e0bccff5e5..0000000000 --- a/explore-analyze/machine-learning/machine-learning-in-kibana/xpack-ml-dfanalytics.md +++ /dev/null @@ -1,22 +0,0 @@ ---- -mapped_pages: - - https://www.elastic.co/guide/en/kibana/current/xpack-ml-dfanalytics.html -applies_to: - stack: ga - serverless: ga -products: - - id: kibana ---- - -# Data frame analytics [xpack-ml-dfanalytics] - -The Elastic {{ml}} {{dfanalytics}} feature enables you to analyze your data using {{classification}}, {{oldetection}}, and {{regression}} algorithms and generate new indices that contain the results alongside your source data. - -If you have a license that includes the {{ml-features}}, you can create {{dfanalytics}} jobs and view their results on the **Data Frame Analytics** page in {{kib}}. For example: - -:::{image} /explore-analyze/images/kibana-classification.png -:alt: {{classification-cap}} results in {{kib}} -:screenshot: -::: - -For more information about the {{dfanalytics}} feature, see [{{ml-cap}} {{dfanalytics}}](../data-frame-analytics.md). diff --git a/explore-analyze/toc.yml b/explore-analyze/toc.yml index 8a716762a1..b37f9b23f4 100644 --- a/explore-analyze/toc.yml +++ b/explore-analyze/toc.yml @@ -214,8 +214,6 @@ toc: - file: machine-learning/nlp/ml-nlp-limitations.md - file: machine-learning/machine-learning-in-kibana.md children: - - file: machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md - - file: machine-learning/machine-learning-in-kibana/xpack-ml-dfanalytics.md - file: machine-learning/machine-learning-in-kibana/xpack-ml-aiops.md - file: machine-learning/machine-learning-in-kibana/inference-processing.md - file: scripting.md diff --git a/explore-analyze/visualize.md b/explore-analyze/visualize.md index e6ae3e3373..d2b0a44319 100644 --- a/explore-analyze/visualize.md +++ b/explore-analyze/visualize.md @@ -29,9 +29,9 @@ $$$panels-editors$$$ | | [Image](visualize/image-panels.md) | Personalize your dashboard with custom images | | | [Links](visualize/link-panels.md) | Add links to other dashboards or to external websites | | | | | -| Machine Learning and Analytics | [Anomaly swim lane](machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md) | Display the results from machine learning anomaly detection jobs | -| | [Anomaly chart](machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md) | Display an anomaly chart from the **Anomaly Explorer** | -| | [Single metric viewer](machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md) | Display an anomaly chart from the **Single Metric Viewer** | +| Machine Learning and Analytics | [Anomaly swim lane](machine-learning/anomaly-detection/ml-ad-view-results.md) | Display the results from machine learning anomaly detection jobs | +| | [Anomaly chart](machine-learning/anomaly-detection/ml-ad-view-results.md) | Display an anomaly chart from the **Anomaly Explorer** | +| | [Single metric viewer](machine-learning/anomaly-detection/ml-ad-view-results.md) | Display an anomaly chart from the **Single Metric Viewer** | | | [Change point detection](machine-learning/machine-learning-in-kibana/xpack-ml-aiops.md#change-point-detection) | Display a chart to visualize change points in your data | | | | | | Observability | [SLO overview](/solutions/observability/incident-management/service-level-objectives-slos.md) | Visualize a selected SLO’s health, including name, current SLI value, target, and status | diff --git a/redirects.yml b/redirects.yml index d7f1e1ab41..9db6cbf393 100644 --- a/redirects.yml +++ b/redirects.yml @@ -213,4 +213,8 @@ redirects: 'manage-data/ingest/transform-enrich/ingest-pipelines-serverless.md': 'manage-data/ingest/transform-enrich/ingest-pipelines.md' # Related to https://github.com/elastic/docs-content/pull/2010 - 'manage-data/lifecycle/index-lifecycle-management/index-management-in-kibana.md': 'manage-data/data-store/index-basics.md' \ No newline at end of file + 'manage-data/lifecycle/index-lifecycle-management/index-management-in-kibana.md': 'manage-data/data-store/index-basics.md' + + # Related to https://github.com/elastic/docs-content/pull/2097 + 'explore-analyze/machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md': 'explore-analyze/machine-learning/anomaly-detection.md' + 'explore-analyze/machine-learning/machine-learning-in-kibana/xpack-ml-dfa-analytics.md': 'explore-analyze/machine-learning/data-frame-analytics.md' \ No newline at end of file diff --git a/solutions/observability/logs/inspect-log-anomalies.md b/solutions/observability/logs/inspect-log-anomalies.md index bd62cad4de..f99c374a0f 100644 --- a/solutions/observability/logs/inspect-log-anomalies.md +++ b/solutions/observability/logs/inspect-log-anomalies.md @@ -16,7 +16,7 @@ When the {{anomaly-detect}} features of {{ml}} are enabled, you can use the **Lo * A significant drop in the log rate might suggest that a piece of infrastructure stopped responding, and thus we’re serving fewer requests. * A spike in the log rate could denote a DDoS attack. This may lead to an investigation of IP addresses from incoming requests. -You can also view log anomalies directly in the [{{ml-app}} app](/explore-analyze/machine-learning/machine-learning-in-kibana/xpack-ml-anomalies.md). +You can also view log anomalies directly in the [{{ml-app}} app](/explore-analyze/machine-learning/anomaly-detection/ml-ad-view-results.md). ::::{note} This feature makes use of {{ml}} {{anomaly-jobs}}. To set up jobs, you must have `all` {{kib}} feature privileges for **{{ml-app}}**. Users that have full or read-only access to {{ml-features}} within a {{kib}} space can view the results of *all* {{anomaly-jobs}} that are visible in that space, even if they do not have access to the source indices of those jobs. You must carefully consider who is given access to {{ml-features}}; {{anomaly-job}} results may propagate field values that contain sensitive information from the source indices to the results. For more details, refer to [Set up {{ml-features}}](/explore-analyze/machine-learning/setting-up-machine-learning.md).