Amazon Bedrock provider

You can proxy requests to Amazon Bedrock AI models through AI Gateway using the AI Proxy and AI Proxy Advanced plugins. This reference documents all supported AI capabilities, configuration requirements, and provider-specific details needed for proper integration.

AI Gateway automatically routes requests to the appropriate Amazon Bedrock API endpoints. The following table shows the upstream paths used for each capability.

The following tables show the AI capabilities supported by Amazon Bedrock provider when used with the AI Proxy or the AI Proxy Advanced plugin.

Set the plugin’s route_type based on the capability you want to use. See the tables below for supported route types.

Text generation

Support for Amazon Bedrock basic text generation capabilities including chat, completions, and embeddings:

Advanced text generation

Support for Amazon Bedrock function calling to allow Amazon Bedrock models to use external tools and APIs:

Processing

Support for Amazon Bedrock file operations, batch operations, assistants, and response handling:

¹ Amazon Bedrock does not have a dedicated files API. File storage uses Google Cloud Storage, similar to AWS S3.

² Batches processing for Bedrock is supported in the native format from SDK only

Image

Support for Amazon Bedrock image generation and editing capabilities:

For requests with large payloads, consider increasing config.max_request_body_size to three times the raw binary size.

Supported image sizes and formats vary by model. Refer to your provider’s documentation for allowed dimensions and requirements.

Video

Support for Amazon Bedrock video generation capabilities:

For requests with large payloads (video generation), consider increasing config.max_request_body_size to three times the raw binary size.

The base URL is https://bedrock-runtime.{region}.amazonaws.com, where {route_type_path} is determined by the capability.

AI Gateway uses this URL automatically. You only need to configure a URL if you’re using a self-hosted or Amazon Bedrock-compatible endpoint, in which case set the upstream_url plugin option.

By default, the AI Proxy plugin uses OpenAI-compatible request formats. Set config.llm_format to a native format to use Amazon Bedrock-specific APIs and features.

The following native Amazon Bedrock APIs are supported:

Statistics logging limitations for native formats

• Statistics logging is not available for image generation or editing APIs for Amazon Bedrock

To use Amazon Bedrock with AI Gateway, configure the AI Proxy or AI Proxy Advanced.

Here’s a minimal configuration for chat completions:

_format_version: "3.0"
plugins:
  - name: ai-proxy
    config:
      route_type: llm/v1/chat
      auth:
        allow_override: false
        aws_access_key_id: ${{ env "DECK_AWS_ACCESS_KEY_ID" }}
        aws_secret_access_key: ${{ env "DECK_AWS_SECRET_ACCESS_KEY" }}
      model:
        provider: bedrock
        name: meta.llama3-70b-instruct-v1:0
        options:
          bedrock:
            aws_region: us-east-1

curl -i -X POST http://localhost:8001/plugins/ \
    --header "Accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "auth": {
          "allow_override": false,
          "aws_access_key_id": "'$AWS_ACCESS_KEY_ID'",
          "aws_secret_access_key": "'$AWS_SECRET_ACCESS_KEY'"
        },
        "model": {
          "provider": "bedrock",
          "name": "meta.llama3-70b-instruct-v1:0",
          "options": {
            "bedrock": {
              "aws_region": "us-east-1"
            }
          }
        }
      }
    }
    '

curl -X POST https://{region}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "auth": {
          "allow_override": false,
          "aws_access_key_id": "'$AWS_ACCESS_KEY_ID'",
          "aws_secret_access_key": "'$AWS_SECRET_ACCESS_KEY'"
        },
        "model": {
          "provider": "bedrock",
          "name": "meta.llama3-70b-instruct-v1:0",
          "options": {
            "bedrock": {
              "aws_region": "us-east-1"
            }
          }
        }
      }
    }
    '

echo "
apiVersion: configuration.konghq.com/v1
kind: KongClusterPlugin
metadata:
  name: ai-proxy
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
  labels:
    global: 'true'
config:
  route_type: llm/v1/chat
  auth:
    allow_override: false
    aws_access_key_id: '$AWS_ACCESS_KEY_ID'
    aws_secret_access_key: '$AWS_SECRET_ACCESS_KEY'
  model:
    provider: bedrock
    name: meta.llama3-70b-instruct-v1:0
    options:
      bedrock:
        aws_region: us-east-1
plugin: ai-proxy
" | kubectl apply -f -

resource "konnect_gateway_plugin_ai_proxy" "my_ai_proxy" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"

    auth = {
      allow_override = false
      aws_access_key_id = var.aws_access_key_id
      aws_secret_access_key = var.aws_secret_access_key
    }

    model = {
      provider = "bedrock"
      name = "meta.llama3-70b-instruct-v1:0"

      options = {

        bedrock = {
          aws_region = "us-east-1"
        }
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
}

variable "aws_secret_access_key" {
  type = string
}

For more configuration options and examples, see:

• AI Proxy examples
• AI Proxy Advanced examples

• Use the AI AWS Guardrails plugin View →
• Use AWS Bedrock rerank API with AI Proxy View →
• Route Claude CLI traffic through AI Gateway and AWS Bedrock View →