> ## Documentation Index
> Fetch the complete documentation index at: https://agent-observability-docs.splunk.com/llms.txt
> Use this file to discover all available pages before exploring further.

# AWS Bedrock Inference Profiles

> Learn how to use AWS Bedrock Inference Profiles with Splunk Agent Observability in an on-premises, standalone, or custom deployment.

Splunk Agent Observability supports AWS Bedrock integration via
[Inference Profiles](https://docs.aws.amazon.com/bedrock/latest/userguide/inference-profiles.html).
This enables the mapping of Splunk Agent Observability-supported model identifiers to an AWS Bedrock
Inference Profile ARN, providing greater flexibility and alignment
with existing Bedrock configurations.

This page explains what inference profiles are,
how Splunk Agent Observability integrates with them, and how to configure
the integration using a simple setup script.

## What are AWS Bedrock Inference Profiles?

An [AWS Bedrock Inference Profile](https://docs.aws.amazon.com/bedrock/latest/userguide/inference-profiles.html) is an AWS resource
that represents a way to invoke a foundation model
(such as Anthropic Claude, Meta Llama, or Mistral)
while tracking usage and cost under a named profile in your AWS account.

## How Splunk Agent Observability works with Inference Profiles

When you use inference profiles with Splunk Agent Observability:

* You [create an Inference Profile](https://docs.aws.amazon.com/bedrock/latest/userguide/inference-profiles-create.html)
  in AWS Bedrock.
* You create an IAM role in your AWS account that Splunk Agent Observability can assume.
* You register that role and your Inference Profile ARN with Splunk Agent Observability.

When you run evaluations or prompts in Splunk Agent Observability, Splunk Agent Observability:

* Invokes Bedrock using your Inference Profile
* Logs results and evaluators back to Splunk Agent Observability
* Your models, data, and billing remain fully in your AWS account.

## Prerequisites

Before running the setup script, make sure you have:

* A **Splunk Agent Observability API key**. The key is tied to a specific Splunk Agent Observability user, and the
  integration will be created or updated under that user.
* An **AWS IAM role** that Splunk Agent Observability can assume, with:
  * `bedrock:InvokeModel` permission on the models or inference profiles you intend to use.
  * A trust policy that allows Splunk Agent Observability to call `sts:AssumeRole`.
* One or more **Inference Profile ARNs** already
  [created in AWS Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/inference-profiles-create.html).

## Setting up the AWS Bedrock Inference Profile integration

The script below configures the AWS Bedrock integration in Splunk Agent Observability.
It does not create AWS resources.

```bash theme={null}

#!/bin/bash
#
# This is an example script for how to set AWS Bedrock integration in Splunk Agent Observability.
# Customize inference_profiles to your needs. The values below are just examples.
# You can use either a model alias or a model name, and map it to an
# inference profile ARN.
# SPLUNK_AO_API_KEY is only required for on-premises, standalone, or custom deployments

if [ -z "$SPLUNK_AO_API_KEY" ]; then
  echo "Error: SPLUNK_AO_API_KEY environment variable is not set"
  exit 1
fi

if [ -z "$AWS_ROLE_ARN" ]; then
  echo "Error: AWS_ROLE_ARN environment variable is not set"
  exit 1
fi

if [ -z "$SPLUNK_AO_API_URL" ]; then
  echo "Error: SPLUNK_AO_API_URL environment variable is not set"
  exit 1
fi

curl "${SPLUNK_AO_API_URL}/integrations/aws_bedrock" \
  -X PUT \
  -H "Splunk-AO-API-Key: ${SPLUNK_AO_API_KEY}" \
  -H "content-type: application/json" \
  --data-raw "$(cat <<EOF
{
  "credential_type": "assumed_role",
  "region": "us-east-1",
  "token": {
    "aws_role_arn": "${AWS_ROLE_ARN}"
  },
  "inference_profiles": {
    "anthropic.claude-3-sonnet-20240229-v1:0":
      "arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/my-sonnet-profile"
  }
}
EOF
)"
```

## Verifying the integration was updated

A successful `PUT` returns a JSON response like this:

```json theme={null}
{
  "id": "a0ce9eff-1290-41ae-b78d-a01118a1122c",
  "permissions": [],
  "name": "aws_bedrock",
  "created_at": "2026-03-20T22:36:57.225940Z",
  "updated_at": "2026-03-20T22:36:57.225946Z",
  "created_by": "e19dd8ef-c881-4c17-bc2a-fa549f691a5c",
  "is_selected": false
}
```

A few fields are worth checking:

* `created_by` is the Splunk Agent Observability user that owns this integration. If you have
  multiple users in your organization, this confirms which user's integration
  was just updated.
* `updated_at` confirms the change was persisted just now.

If the request returns a `4xx` or `5xx` error instead, the integration was
**not** updated. Resolve the error and re-run the script before testing
inference again.

## Sharing integrations across users

Each AWS Bedrock integration belongs to the Splunk Agent Observability user who created it.
Multiple users in the same organization can each create their own AWS Bedrock
integration, and each one stays associated only with the user who set it up.

A user can also share their integration with other users or with user groups.
Shared integrations appear in the recipient's Splunk Agent Observability UI labeled as
**Shared**. To start using a shared integration, the recipient must
**select** it in the UI. Once selected, they can use it for their inference
runs.

## Supported models

Splunk Agent Observability supports the following AWS Bedrock model aliases. Use any of these
as a key in the `inference_profiles` map of the setup script.

* `AI21 - Jamba 1.5 Large (Bedrock)`
* `AI21 - Jamba 1.5 Mini (Bedrock)`
* `Amazon - Nova 2 Lite (Bedrock)`
* `Amazon - Nova Lite (Bedrock)`
* `Amazon - Nova Micro (Bedrock)`
* `Amazon - Nova Premier (Bedrock)`
* `Amazon - Nova Pro (Bedrock)`
* `Anthropic - Claude 3 Haiku (Bedrock)`
* `Anthropic - Claude 3.5 Sonnet (Bedrock)`
* `Anthropic - Claude 3.5 Sonnet v2 (Bedrock)`
* `Anthropic - Claude 3.7 Sonnet (Bedrock)`
* `Anthropic - Claude 4 Opus (Bedrock)`
* `Anthropic - Claude 4 Sonnet (Bedrock)`
* `Anthropic - Claude Haiku 4.5 (Bedrock)`
* `Anthropic - Claude Opus 4.1 (Bedrock)`
* `Anthropic - Claude Opus 4.5 (Bedrock)`
* `Anthropic - Claude Opus 4.6 (Bedrock)`
* `Anthropic - Claude Opus 4.7 (Bedrock)`
* `Anthropic - Claude Sonnet 4.5 (Bedrock)`
* `Anthropic - Claude Sonnet 4.6 (Bedrock)`
* `Cohere - Command R v1 (Bedrock)`
* `Cohere - Command R+ v1 (Bedrock)`
* `DeepSeek - R1 (Bedrock)`
* `Google - Gemma 3 12B (Bedrock)`
* `Google - Gemma 3 27B (Bedrock)`
* `Google - Gemma 3 4B (Bedrock)`
* `Meta - Llama 3 70B Instruct v1 (Bedrock)`
* `Meta - Llama 3 8B Instruct v1 (Bedrock)`
* `Meta - Llama 3.1 70B Instruct v1 (Bedrock)`
* `Meta - Llama 3.1 8B Instruct v1 (Bedrock)`
* `Meta - Llama 3.2 11B Instruct (Bedrock)`
* `Meta - Llama 3.2 1B Instruct (Bedrock)`
* `Meta - Llama 3.2 3B Instruct (Bedrock)`
* `Meta - Llama 3.2 90B Instruct (Bedrock)`
* `Meta - Llama 3.3 70B Instruct (Bedrock)`
* `Meta - Llama 4 Maverick 17B Instruct (Bedrock)`
* `Meta - Llama 4 Scout 17B Instruct (Bedrock)`
* `MiniMax - M2 (Bedrock)`
* `Mistral - 7B Instruct (Bedrock)`
* `Mistral - Large (Bedrock)`
* `Mistral - Large 3 (Bedrock)`
* `Mistral - Magistral Small (Bedrock)`
* `Mistral - Ministral 14B (Bedrock)`
* `Mistral - Ministral 3B (Bedrock)`
* `Mistral - Ministral 8B (Bedrock)`
* `Mistral - Pixtral Large 25.02 (Bedrock)`
* `Mistral - Small 24.02 (Bedrock)`
* `Mixtral - 8x7B Instruct (Bedrock)`
* `Moonshot - Kimi K2 Thinking (Bedrock)`
* `NVIDIA - Nemotron Nano 12B (Bedrock)`
* `NVIDIA - Nemotron Nano 9B (Bedrock)`
* `OpenAI - GPT OSS 120B (Bedrock)`
* `OpenAI - GPT OSS 20B (Bedrock)`
* `Qwen - Qwen3 32B (Bedrock)`
* `Qwen - Qwen3 Coder 30B (Bedrock)`
* `Qwen - Qwen3 Next 80B (Bedrock)`
* `Qwen - Qwen3 VL 235B A22B (Bedrock)`
* `Writer - Palmyra X4 (Bedrock)`
* `Writer - Palmyra X5 (Bedrock)`

## Troubleshooting

If you've updated the integration but inference is still using the old
configuration, walk through this checklist:

* Confirm the `PUT` request returned a success response (see
  [Verifying the integration was updated](#verifying-the-integration-was-updated)),
  not a `4xx` or `5xx` error.
* Check **which Splunk Agent Observability API key** was used in the script — it corresponds to
  a specific Splunk Agent Observability user.
* Check **which AWS Role ARN** was used, and verify it has
  `bedrock:InvokeModel` and `sts:AssumeRole` permissions.
* Check the **model aliases** in the request body. Each one must be a
  Bedrock model alias supported by Splunk Agent Observability (see
  [Supported models](#supported-models)).
* Check the **inference profile ARNs** in the request body. Each ARN must
  point to an inference profile that exists in your AWS account and that the
  provided IAM role has permission to invoke (`bedrock:InvokeModel` on the
  profile, plus permission to invoke its underlying foundation model).
* Confirm the integration belonging to the API key's user is the one
  being used for inference.
* If the integration is shared with other users, confirm those users have
  **selected** the shared integration in the Splunk Agent Observability UI.