Moves LLM connector guides to explore-analyze section

solutions/security/ai/connect-to-amazon-bedrock.md → explore-analyze/ai-features/llm-guides/connect-to-amazon-bedrock.md

@@ -11,7 +11,7 @@
   - id: cloud-serverless
 ---
 
 # Connect to Amazon Bedrock
 
 This page provides step-by-step instructions for setting up an Amazon Bedrock connector for the first time. This connector type enables you to leverage large language models (LLMs) within {{kib}}. You’ll first need to configure AWS, then configure the connector in {{kib}}.
 
@@ -24,9 +24,9 @@
 ## Configure AWS [_configure_aws]
 
 
 ### Configure an IAM policy [_configure_an_iam_policy]
 
 First, configure an IAM policy with the necessary permissions:
 
 1. Log into the AWS console and search for Identity and Access Management (IAM).
 2. From the **IAM** menu, select **Policies** → **Create policy**.
@@ -61,9 +61,9 @@
 
 
 
 ### Configure an IAM User [_configure_an_iam_user]
 
-Next, assign the policy you just created to a new user:
+Next, assign the policy you created to a new user:
 
 1. Return to the **IAM** menu. Select **Users** from the navigation menu, then click **Create User**.
 2. Name the user, then click **Next**.
@@ -79,10 +79,10 @@
 
 ### Create an access key [_create_an_access_key]
 
 Create the access keys that will authenticate your Elastic connector:
 
 1. Return to the **IAM** menu. Select **Users** from the navigation menu.
-2. Search for the user you just created, and click its name.
+2. Search for the user you created, and click its name.
 3. Go to the **Security credentials** tab.
 4. Under **Access keys**, click **Create access key**.
 5. Select **Third-party service**, check the box under **Confirmation**, click **Next**, then click **Create access key**.
@@ -94,7 +94,7 @@
 
 
 
 ## Configure the Amazon Bedrock connector [_configure_the_amazon_bedrock_connector]
 
 Finally, configure the connector in {{kib}}:
 
@@ -102,7 +102,7 @@
 2. Find the **Connectors** page in the navigation menu or use the [global search field](/explore-analyze/find-and-organize/find-apps-and-objects.md). Then click **Create Connector**, and select **Amazon Bedrock**.
 3. Name your connector.
 4. (Optional) Configure the Amazon Bedrock connector to use a different AWS region where Anthropic models are supported by editing the **URL** field, for example by changing `us-east-1` to `eu-central-1`.
-5. (Optional) Add one of the following strings if you want to use a model other than the default. Note that these model IDs should have a prefix of `us.` or `eu.`, depending on your region, for example `us.anthropic.claude-3-5-sonnet-20240620-v1:0` or `eu.anthropic.claude-3-5-sonnet-20240620-v1:0`.
+5. (Optional) Add one of the following strings if you want to use a model other than the default. These model IDs should have a prefix of `us.` or `eu.`, depending on your region, for example `us.anthropic.claude-3-5-sonnet-20240620-v1:0` or `eu.anthropic.claude-3-5-sonnet-20240620-v1:0`.
 
     * Sonnet 3.5: `us.anthropic.claude-3-5-sonnet-20240620-v1:0` or `eu.anthropic.claude-3-5-sonnet-20240620-v1:0`
     * Sonnet 3.5 v2: `us.anthropic.claude-3-5-sonnet-20241022-v2:0` or `eu.anthropic.claude-3-5-sonnet-20241022-v2:0`

explore-analyze/ai-features/llm-guides/llm-connectors.md

@@ -0,0 +1,50 @@
+---
+mapped_pages:
+  - https://www.elastic.co/guide/en/security/current/llm-connector-guides.html
+  - https://www.elastic.co/guide/en/serverless/current/security-llm-connector-guides.html
+applies_to:
+  stack: all
+  serverless:
+    security: all
+    observability: all
+    elasticsearch: all
+products:
+  - id: observability
+  - id: elasticsearch
+  - id: security
+  - id: cloud-serverless
+---
+
+# Enable large language model (LLM) access
+
+Elastic uses large language model (LLM) connectors to power its [AI features](/explore-analyze/ai-features.md#ai-powered-features-in-elastic-sec). These features with the out-of-the-box Elastic Managed LLM or by configuring a third-party LLM connector.
+
+## Elastic Managed LLM
+
+:::{include} ../../../solutions/_snippets/elastic-managed-llm.md
+:::
+
+## Connect to a third-party LLM
+
+Follow these guides to connect to one or more third-party LLM providers:
+
+* [Azure OpenAI](/explore-analyze/ai-features/llm-guides/connect-to-azure-openai.md)
+* [Amazon Bedrock](/explore-analyze/ai-features/llm-guides/connect-to-amazon-bedrock.md)
+* [OpenAI](/explore-analyze/ai-features/llm-guides/connect-to-openai.md)
+* [Google Vertex](/explore-analyze/ai-features/llm-guides/connect-to-google-vertex.md)
+
+## Preconfigured connectors
+
+```{applies_to}
+stack: ga
+serverless: unavailable
+```
+
+You can also use [preconfigured connectors](kibana://reference/connectors-kibana/pre-configured-connectors.md) to set up a third-party LLM connector. 
+
+If you use a preconfigured connector for your LLM connector, we recommend adding the `exposeConfig: true` parameter to the `xpack.actions.preconfigured` section of the `kibana.yml` config file. This parameter makes debugging easier by adding configuration information to the debug logs, including which LLM the connector uses.
+
+
+
+
+

explore-analyze/toc.yml

@@ -170,6 +170,12 @@ toc:
     children:
       - file: ai-features/ai-assistant.md
       - file: ai-features/manage-access-to-ai-assistant.md
+      - file: ai-features/llm-guides/llm-connectors.md
+        children:
+          - file: ai-features/llm-guides/connect-to-azure-openai.md
+          - file: ai-features/llm-guides/connect-to-amazon-bedrock.md
+          - file: ai-features/llm-guides/connect-to-openai.md
+          - file: ai-features/llm-guides/connect-to-google-vertex.md
   - file: discover.md
     children:
       - file: discover/discover-get-started.md

redirects.yml

@@ -600,3 +600,10 @@ redirects:
 
 # Related to https://github.com/elastic/docs-content/pull/3808
   'solutions/observability/get-started/other-tutorials/add-data-from-splunk.md': 'solutions/observability/get-started.md'
+
+
+# Related to https://github.com/elastic/docs-content/pull/4224
+  'solutions/security/ai/connect-to-amazon-bedrock.md': 'explore-analyze/ai-features/llm-guides/connect-to-amazon-bedrock.md'
+  'solutions/security/ai/connect-to-azure-openai.md': 'explore-analyze/ai-features/llm-guides/connect-to-azure-openai.md'
+  'solutions/security/ai/connect-to-google-vertex.md': 'explore-analyze/ai-features/llm-guides/connect-to-google-vertex.md'
+  'solutions/security/ai/connect-to-openai.md': 'explore-analyze/ai-features/llm-guides/connect-to-openai.md'

solutions/_snippets/elastic-managed-llm.md

@@ -1,6 +1,6 @@
-[Elastic Managed LLM](https://www.elastic.co/docs/reference/kibana/connectors-kibana/elastic-managed-llm) is the default large language model (LLM) connector available in the AI Assistant for eligible users. It provides immediate access to generative AI features without requiring any setup or external model integration.
+[Elastic Managed LLM](https://www.elastic.co/docs/reference/kibana/connectors-kibana/elastic-managed-llm) is the default large language model (LLM) connector available in {{kib}} for eligible users. It provides immediate access to generative AI features without requiring any setup or external model integration.
 
-The Elastic Managed LLM is available out-of-the box; no manual connector setup or API key management is required for initial use. However, you can configure and use a third-party LLM connector, such as OpenAI, Azure, or Amazon Bedrock if you prefer.
+Elastic Managed LLM is available out-of-the box; it does not require manual connector setup or API key management. However, you can configure and use a third-party LLM connector, such as OpenAI, Azure, or Amazon Bedrock if you prefer.
 
 To learn more about security and data privacy, refer to the [connector documentation](https://www.elastic.co/docs/reference/kibana/connectors-kibana/elastic-managed-llm) and [download the model card](https://raw.githubusercontent.com/elastic/kibana/refs/heads/main/docs/reference/resources/Elastic_Managed_LLM_model_card.pdf).
 

solutions/security/ai/set-up-connectors-for-large-language-models-llm.md

@@ -1,7 +1,4 @@
 ---
-mapped_pages:
-  - https://www.elastic.co/guide/en/security/current/llm-connector-guides.html
-  - https://www.elastic.co/guide/en/serverless/current/security-llm-connector-guides.html
 applies_to:
   stack: all
   serverless:
@@ -13,7 +10,7 @@ products:
 
 # Enable large language model (LLM) access
 
-{{elastic-sec}} uses large language models (LLMs) for some of its advanced analytics features. To enable these features, you can connect a third-party LLM provider or a custom local LLM.
+{{elastic-sec}} uses large language model (LLM) connectors to power it's [AI features](/explore-analyze/ai-features.md#ai-powered-features-in-elastic-sec). To use these features, you can use Elastic Managed LLM, configure a third-party LLM connector, or a custom local LLM.
 
 :::{important}
 Different LLMs have varying performance when used to power different features and use-cases. For more information about how various models perform on different tasks in {{elastic-sec}}, refer to the [Large language model performance matrix](/solutions/security/ai/large-language-model-performance-matrix.md).
@@ -28,10 +25,10 @@ Different LLMs have varying performance when used to power different features an
 
 Follow these guides to connect to one or more third-party LLM providers:
 
-* [Azure OpenAI](/solutions/security/ai/connect-to-azure-openai.md)
-* [Amazon Bedrock](/solutions/security/ai/connect-to-amazon-bedrock.md)
-* [OpenAI](/solutions/security/ai/connect-to-openai.md)
-* [Google Vertex](/solutions/security/ai/connect-to-google-vertex.md)
+* [Azure OpenAI](/explore-analyze/ai-features/llm-guides/connect-to-azure-openai.md)
+* [Amazon Bedrock](/explore-analyze/ai-features/llm-guides/connect-to-amazon-bedrock.md)
+* [OpenAI](/explore-analyze/ai-features/llm-guides/connect-to-openai.md)
+* [Google Vertex](/explore-analyze/ai-features/llm-guides/connect-to-google-vertex.md)
 
 ## Connect to a self-managed LLM
 

solutions/toc.yml

@@ -1,3 +1,3 @@
 project: "Solutions and use cases"
 toc:
   - file: index.md
@@ -568,10 +568,6 @@
           - file: security/ai/set-up-connectors-for-large-language-models-llm.md
             children:
               - file: security/ai/large-language-model-performance-matrix.md
-              - file: security/ai/connect-to-azure-openai.md
-              - file: security/ai/connect-to-amazon-bedrock.md
-              - file: security/ai/connect-to-openai.md
-              - file: security/ai/connect-to-google-vertex.md
               - file: security/ai/connect-to-own-local-llm.md
               - file: security/ai/connect-to-vLLM.md
           - file: security/ai/use-cases.md