Merge pull request #23167 from newrelic/Daily-Merge-2-24-26/evening

Daily merge 2 24 26/evening

Author: PallaviWrite

.gitignore

@@ -94,3 +94,8 @@ src/images/infrastructure_screenshot_full_sonarqube-dashboard.webp
 
 # Claude Code documentation (local only)
 .claude/
+
+# Documentation reference files (local only)
+EMAIL_TEMPLATE_AGENT_TEAMS.md
+OTEL_DOCS_STATUS.md
+SME_QUESTIONS_OTEL_API_SUPPORT.md

src/content/docs/agentic-ai/knowledge-integration/overview.mdx

@@ -7,12 +7,6 @@ redirects:
   - /docs/agentic-ai/knowledge-integration/knowledge-connector
 ---
 
-<Callout title="preview">
-  We're still working on this feature, but we'd love for you to try it out!
-
-  This feature is currently provided as part of a preview program pursuant to our [pre-release policies](/docs/licenses/license-information/referenced-policies/new-relic-pre-release-policy).
-</Callout>
-
 To provide more context-specific answers, New Relic AI can use a technique called Retrieval Augmented Generation (RAG) through the New Relic AI knowledge connector. While New Relic AI LLMs have a vast general knowledge, RAG enhances their responses.
 
 By setting up the New Relic AI knowledge connector, you can expect tangible outcomes such as faster alert event resolution, more accurate and context-aware AI responses, and reduced manual searching across multiple documents. This unified approach helps your team make better decisions and respond to issues more efficiently.

src/content/docs/alerts/create-alert/create-alert-condition/alert-conditions.mdx

@@ -240,12 +240,6 @@ For all methods except for our guided mode, the process for creating an alert co
         title="Outlier detection"
       >
 
-      <Callout title="preview">
-        We're still working on this feature, but we'd love for you to try it out!
-
-        This feature is currently provided as part of a preview program pursuant to our [pre-release policies](/docs/licenses/license-information/referenced-policies/new-relic-pre-release-policy).
-      </Callout>
-
         Outlier detection identifies entities that are behaving significantly differently from their peers at a specific moment in time. Unlike anomaly detection that looks for unusual patterns over time, outlier detection focuses on deviations within a group using DBSCAN clustering.
 
         This threshold type is ideal for:

src/content/docs/alerts/create-alert/set-thresholds/outlier-detection.mdx

@@ -4,12 +4,6 @@ metaDescription: "Learn how outlier detection identifies entities behaving diffe
 freshnessValidatedDate: never
 ---
 
-<Callout title="preview">
-  We're still working on this feature, but we'd love for you to try it out!
-
-  This feature is currently provided as part of a preview program pursuant to our [pre-release policies](/docs/licenses/license-information/referenced-policies/new-relic-pre-release-policy).
-</Callout>
-
 New Relic's outlier detection is an advanced feature designed to automatically identify entities that are behaving significantly differently from their peers. Unlike traditional anomaly detection, which looks for unusual patterns over time, outlier detection focuses on deviations within a group at a specific moment.
 
 This functionality helps you proactively identify potential issues, such as: