---
title: Connect to Amazon Bedrock
description: 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...
url: https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/ai-features/llm-guides/connect-to-amazon-bedrock
products:
- Elastic Cloud Serverless
- Elastic Security
applies_to:
- Serverless Security projects: Generally available
- Elastic Stack: Generally available
---
# 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 Kibana. You’ll first need to configure AWS, then configure the connector in Kibana.
All models in Amazon Bedrock's `Claude` model group are supported.
## Configure AWS
### 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**.
3. To provide the necessary permissions, paste the following JSON into the **Specify permissions** menu.
```json
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "VisualEditor0",
"Effect": "Allow",
"Action": [
"bedrock:InvokeModel",
"bedrock:InvokeModelWithResponseStream"
],
"Resource": "*"
}
]
}
```
These are the minimum required permissions. IAM policies with additional permissions are also supported.
4. Click **Next**. Name your policy.
The following video demonstrates these steps (click to watch).
[](https://videos.elastic.co/watch/ek6NpHaj6u4keZyEjPWXcT?)
### Configure an IAM 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**.
3. Select **Attach policies directly**.
4. In the **Permissions policies** field, search for the policy you created earlier, select it, and click **Next**.
5. Review the configuration then click **Create user**.
The following video demonstrates these steps (click to watch).
[](https://videos.elastic.co/watch/5BQb2P818SMddRo6gA79hd?)
### 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 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**.
6. Click **Download .csv file** to download the key. Store it securely.
The following video demonstrates these steps (click to watch).
[](https://videos.elastic.co/watch/8oXgP1fbaQCqjWUgncF9at?)
## Configure the Amazon Bedrock connector
Finally, configure the connector in Kibana:
1. Log in to Kibana.
2. Find the **Connectors** page in the navigation menu or use the [global search field](https://www.elastic.co/elastic/docs-builder/docs/3028/explore-analyze/find-and-organize/find-apps-and-objects). 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. 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`
- Sonnet 3.7: `us.anthropic.claude-3-7-sonnet-20250219-v1:0` or `eu.anthropic.claude-3-7-sonnet-20250219-v1:0`
- Haiku 3.5: `us.anthropic.claude-3-5-haiku-20241022-v1:0` or `eu.anthropic.claude-3-5-haiku-20241022-v1:0`
- Opus: `us.anthropic.claude-3-opus-20240229-v1:0` or `eu.anthropic.claude-3-opus-20240229-v1:0`
6. Enter the **Access Key** and **Secret** that you generated earlier, then click **Save**.
Your LLM connector is now configured. For more information on using Elastic AI Assistant, refer to [AI Assistant](https://www.elastic.co/elastic/docs-builder/docs/3028/solutions/security/ai/ai-assistant).
If you’re using [provisioned throughput](https://docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html), your ARN becomes the model ID, and the connector settings **URL** value must be [encoded](https://www.urlencoder.org/) to work. For example, if the non-encoded ARN is `arn:aws:bedrock:us-east-2:123456789102:provisioned-model/3Ztr7hbzmkrqy1`, the encoded ARN would be `arn%3Aaws%3Abedrock%3Aus-east-2%3A123456789102%3Aprovisioned-model%2F3Ztr7hbzmkrqy1`.
The following video demonstrates these steps (click to watch).
[](https://videos.elastic.co/watch/QJe4RcTJbp6S6m9CkReEXs?)