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dedemorton committed Nov 20, 2024
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2 changes: 1 addition & 1 deletion docs/en/serverless/index.asciidoc
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Expand Up @@ -197,7 +197,7 @@ include::./ai-assistant/ai-assistant.asciidoc[leveloffset=+2]

//Machine learning

include::./machine-learning/aiops.asciidoc[leveloffset=+2]
include::./machine-learning/machine-learning.asciidoc[leveloffset=+2]
include::./machine-learning/aiops-detect-anomalies.asciidoc[leveloffset=+3]
include::./machine-learning/aiops-tune-anomaly-detection-job.asciidoc[leveloffset=+4]
include::./machine-learning/aiops-forecast-anomaly.asciidoc[leveloffset=+4]
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preview:[]

The AIOps capabilities available in {obs-serverless} enable you to consume and process large observability data sets at scale, reducing the time and effort required to detect, understand, investigate, and resolve incidents.
The machine learning capabilities available in {obs-serverless} enable you to consume and process large observability data sets at scale, reducing the time and effort required to detect, understand, investigate, and resolve incidents.
Built on predictive analytics and {ml}, our AIOps capabilities require no prior experience with {ml}.
DevOps engineers, SREs, and security analysts can get started right away using these AIOps features with little or no advanced configuration:

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4 changes: 2 additions & 2 deletions docs/en/serverless/observability-overview.asciidoc
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Expand Up @@ -136,7 +136,7 @@ image::images/cases.png[Screenshot showing list of cases]

[discrete]
[[observability-serverless-observability-overview-aiops]]
== AIOps
== Machine learning and AIOps

Reduce the time and effort required to detect, understand, investigate, and resolve incidents at scale
by leveraging predictive analytics and machine learning:
Expand All @@ -148,4 +148,4 @@ by leveraging predictive analytics and machine learning:
[role="screenshot"]
image::images/log-rate-analysis.png[Log rate analysis page showing log rate spike ]

<<observability-aiops,Learn more about AIOps →>>
<<observability-machine-learning,Learn more about machine learning and AIOps →>>
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Expand Up @@ -119,7 +119,7 @@ You can also:
** <<observability-monitor-datasets,Monitor log data set quality>> to find degraded documents.
** <<observability-run-log-pattern-analysis,Run a pattern analysis>> to find patterns in unstructured log messages.
** <<observability-alerting,Create alerts>> that notify you when an Observability data type reaches or exceeds a given value.
* Use <<observability-aiops,AIOps features>> to apply predictive analytics and machine learning to your data:
* Use <<observability-machine-learning,machine learning and AIOps features>> to apply predictive analytics and machine learning to your data:
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** <<observability-aiops-detect-anomalies,Detect anomalies>> by comparing real-time and historical data from different sources to look for unusual, problematic patterns.
** <<observability-aiops-analyze-spikes,Analyze log spikes and drops>>.
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