AWS Bedrock

Configure HolmesGPT to use AWS Bedrock foundation models.

Which Model to Use

We highly recommend using Sonnet 4.0 or Sonnet 4.5 as they give the best results by far. See examples below for configuration.

Setup

Prerequisites

1. Install boto3: AWS Bedrock requires boto3 version 1.28.57 or higher:

   pip install "boto3>=1.28.57"
   

2. AWS credentials: Ensure you have AWS credentials configured with access to Bedrock models. See AWS Docs.

Configuration

Holmes CLIHolmes Helm ChartRobusta Helm Chart

export AWS_REGION_NAME="us-east-1"  # Replace with your region
export AWS_ACCESS_KEY_ID="your-access-key"
export AWS_SECRET_ACCESS_KEY="your-secret-key"

holmes ask "what pods are failing?" --model="bedrock/<your-bedrock-model>"

For Claude Sonnet with 1M context window:

export AWS_REGION_NAME="us-east-1"
export AWS_ACCESS_KEY_ID="your-access-key"
export AWS_SECRET_ACCESS_KEY="your-secret-key"
export EXTRA_HEADERS="{\"anthropic-beta\": \"context-1m-2025-08-07\"}"
export OVERRIDE_MAX_CONTENT_SIZE="1000000"

holmes ask "what pods are failing?" --model="bedrock/eu.anthropic.claude-sonnet-4-20250514-v1:0"

Create Kubernetes Secret:

kubectl create secret generic holmes-secrets \
  --from-literal=aws-access-key-id="AKIA..." \
  --from-literal=aws-secret-access-key="your-secret-key" \
  -n <namespace>

Configure Helm Values:

# values.yaml
additionalEnvVars:
  - name: AWS_ACCESS_KEY_ID
    valueFrom:
      secretKeyRef:
        name: holmes-secrets
        key: aws-access-key-id
  - name: AWS_SECRET_ACCESS_KEY
    valueFrom:
      secretKeyRef:
        name: holmes-secrets
        key: aws-secret-access-key

# Configure at least one model using modelList
modelList:
  bedrock-claude-35-sonnet:
    aws_access_key_id: "{{ env.AWS_ACCESS_KEY_ID }}"
    aws_secret_access_key: "{{ env.AWS_SECRET_ACCESS_KEY }}"
    aws_region_name: us-east-1
    model: bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0
    temperature: 1

  bedrock-claude-sonnet-4:
    aws_access_key_id: "{{ env.AWS_ACCESS_KEY_ID }}"
    aws_secret_access_key: "{{ env.AWS_SECRET_ACCESS_KEY }}"
    aws_region_name: eu-south-2
    model: bedrock/eu.anthropic.claude-sonnet-4-20250514-v1:0
    temperature: 1
    thinking:
      budget_tokens: 10000
      type: enabled

  bedrock-claude-sonnet-4-1M-context:
    aws_access_key_id: "{{ env.AWS_ACCESS_KEY_ID }}"
    aws_secret_access_key: "{{ env.AWS_SECRET_ACCESS_KEY }}"
    aws_region_name: eu-south-2
    model: bedrock/eu.anthropic.claude-sonnet-4-20250514-v1:0
    temperature: 1
    thinking:
      budget_tokens: 10000
      type: enabled
    extra_headers:
      anthropic-beta: context-1m-2025-08-07
    custom_args:
      max_context_size: 1000000

# Optional: Set default model (use modelList key name)
config:
  model: "bedrock-claude-35-sonnet"  # This refers to the key name in modelList above

Create Kubernetes Secret:

kubectl create secret generic robusta-holmes-secret \
  --from-literal=aws-access-key-id="AKIA..." \
  --from-literal=aws-secret-access-key="your-secret-key" \
  -n <namespace>

Configure Helm Values:

# values.yaml
holmes:
  additionalEnvVars:
    - name: AWS_ACCESS_KEY_ID
      valueFrom:
        secretKeyRef:
          name: robusta-holmes-secret
          key: aws-access-key-id
    - name: AWS_SECRET_ACCESS_KEY
      valueFrom:
        secretKeyRef:
          name: robusta-holmes-secret
          key: aws-secret-access-key

  # Configure at least one model using modelList
  modelList:
    bedrock-claude-35-sonnet:
      aws_access_key_id: "{{ env.AWS_ACCESS_KEY_ID }}"
      aws_secret_access_key: "{{ env.AWS_SECRET_ACCESS_KEY }}"
      aws_region_name: us-east-1
      model: bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0
      temperature: 1

    bedrock-claude-sonnet-4:
      aws_access_key_id: "{{ env.AWS_ACCESS_KEY_ID }}"
      aws_secret_access_key: "{{ env.AWS_SECRET_ACCESS_KEY }}"
      aws_region_name: eu-south-2
      model: bedrock/eu.anthropic.claude-sonnet-4-20250514-v1:0
      temperature: 1
      thinking:
        budget_tokens: 10000
        type: enabled

    bedrock-claude-sonnet-4-1M-context:
      aws_access_key_id: "{{ env.AWS_ACCESS_KEY_ID }}"
      aws_secret_access_key: "{{ env.AWS_SECRET_ACCESS_KEY }}"
      aws_region_name: eu-south-2
      model: bedrock/eu.anthropic.claude-sonnet-4-20250514-v1:0
      temperature: 1
      thinking:
        budget_tokens: 10000
        type: enabled
      extra_headers:
        anthropic-beta: context-1m-2025-08-07
      custom_args:
        max_context_size: 1000000

  # Optional: Set default model (use modelList key name)
  config:
    model: "bedrock-claude-35-sonnet"  # This refers to the key name in modelList above

Using Claude Sonnet with 1M Context Window

The bedrock-claude-sonnet-4-1M-context example above demonstrates how to enable the extended 1 million token context window for Claude Sonnet. This requires two configuration parameters:

1. Beta Feature Header:

extra_headers:
  anthropic-beta: context-1m-2025-08-07

This enables Anthropic's beta 1M context window feature.

2. Context Size Override:

custom_args:
  max_context_size: 1000000

This tells HolmesGPT the actual context window size (1M tokens) so it can properly manage conversation history.

Both Parameters Required

You must include both extra_headers and custom_args to use the 1M context window. The extra_headers enables the feature, while custom_args.max_context_size ensures HolmesGPT knows the correct window size.

Finding Your AWS Credentials

If the AWS CLI is already configured on your machine, you may be able to find the above values with:

cat ~/.aws/credentials ~/.aws/config

Finding Available Models

To list models your account can access (replacing us-east-1 with the relevant region):

aws bedrock list-foundation-models --region=us-east-1 | grep modelId

Important: Different models are available in different regions. For example, Claude Opus is only available in us-west-2.

Model Name Examples

Be sure to replace <your-bedrock-model> with a model you have access to, such as anthropic.claude-opus-4-1-20250805-v1:0 or anthropic.claude-sonnet-4-20250514-v1:0

Setting Extra Headers

You can enable various beta features in AWS Bedrock by setting custom headers.

For example, to enable 1M context windows.

You can enable Extra Headers in both the CLI (via env vars) and the Helm charts options.

For the CLI:

export EXTRA_HEADERS="{\"anthropic-beta\": \"context-1m-2025-08-07\"}"

Or, for Helm:

# values.yaml
holmes:
  ...
  modelList:
    ...
    bedrock-claude-sonnet-4-1M-context:
      aws_access_key_id: "{{ env.AWS_ACCESS_KEY_ID }}"
      aws_secret_access_key: "{{ env.AWS_SECRET_ACCESS_KEY }}"
      aws_region_name: eu-south-2
      model: bedrock/eu.anthropic.claude-sonnet-4-20250514-v1:0
      temperature: 1
      thinking:
        budget_tokens: 10000
        type: enabled
      extra_headers:
        anthropic-beta: context-1m-2025-08-07

Additional Resources

HolmesGPT uses the LiteLLM API to support AWS Bedrock provider. Refer to LiteLLM Bedrock docs for more details.