Authenticate to Cloud-Hosted Models Using their Native Authentication - Plugin - unreleased

You are browsing unreleased documentation.

This feature requires Kong Gateway Enterprise.

This guide walks you through setting up the AI Proxy Advanced plugin with a cloud-hosted model, using the cloud’s native authentication mechanism.

Overview

When running software on a cloud-hosted virtual machine or container instance, the provider offers a keyless role-based access mechanism, allowing you to call services native to that cloud provider without having to store any keys inside the running instance (or in the Kong configuration).

This operates like a single-sign-on (SSO) mechanism for your cloud applications.

Kong’s AI Gateway (AI Proxy Advanced) can take advantage of the authentication mechanisms for many different cloud providers and, where available, can also use this authentication to call LLM-based services using those same methods.

Supported providers

Kong’s AI Gateway currently supports the following cloud authentication:

AI-Proxy Advanced LLM Provider	Cloud Provider	Type
`azure`	Azure OpenAI	Entra / Managed Identity Authentication

Azure OpenAI

When hosting your LLMs with Azure OpenAI Service and running them through AI Proxy Advanced, it is possible to use the assigned Azure Managed Identity or User-Assigned Identity of the VM, Kubernetes service-account, or ACS container, to call the Azure OpenAI models.

You can also use an Entra principal or App Registration (client_id, client_secret, and tenant_id triplet) when Kong is hosted outside of Azure.

How you do this depends on where and how you are running Kong Gateway.

Prerequisites

You must be running a Kong Gateway Enterprise instance.

Ensure that the Azure principal that you have assigned to the Compute resource (that is running your Kong Gateway) has the necessary Entra or IAM permissions to execute commands on the desired OpenAI instances. It must have one of the following permissions:

Cognitive Services OpenAI User
Cognitive Services OpenAI Contributor

See Azure’s documentation on managed identity to set this up.

Configuring the AI Proxy Advanced Plugin to use Azure Identity

When running Kong inside of your Azure subscription, AI Proxy Advanced is usually able to detect the designated Managed Identity or User-Assigned Identity of that Azure Compute resource, and use it accordingly.

Azure-Assigned Managed Identity

To use an Azure-Assigned Managed Identity, set up your plugin config like this:

Enable on a route

Enable on a consumer group

Enable globally

Kong Admin API

Konnect API

Kubernetes

Declarative (YAML)

Konnect Terraform

Make the following request:

curl -X POST http://localhost:8001/routes/{routeName|Id}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "route_type": "llm/v1/chat",
    "auth": {
      "azure_use_managed_identity": true
    },
    "model": {
      "provider": "azure",
      "name": "gpt-35-turbo",
      "options": {
        "azure_instance": "my-openai-instance",
        "azure_deployment_id": "kong-gpt-3-5"
      }
    }
  }
}
    '

Replace ROUTE_NAME|ID with the id or name of the route that this plugin configuration will target.

Make the following request, substituting your own access token, region, control plane ID, and route ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/routes/{routeId}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"route_type":"llm/v1/chat","auth":{"azure_use_managed_identity":true},"model":{"provider":"azure","name":"gpt-35-turbo","options":{"azure_instance":"my-openai-instance","azure_deployment_id":"kong-gpt-3-5"}}}}'

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

First, create a KongPlugin resource:

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy-advanced-example
plugin: ai-proxy-advanced
config:
  route_type: llm/v1/chat
  auth:
    azure_use_managed_identity: true
  model:
    provider: azure
    name: gpt-35-turbo
    options:
      azure_instance: my-openai-instance
      azure_deployment_id: kong-gpt-3-5
" | kubectl apply -f -

Next, apply the KongPlugin resource to an ingress by annotating the ingress as follows:

kubectl annotate ingress INGRESS_NAME konghq.com/plugins=ai-proxy-advanced-example

Replace INGRESS_NAME with the name of the ingress that this plugin configuration will target. You can see your available ingresses by running kubectl get ingress.

Note: The KongPlugin resource only needs to be defined once and can be applied to any service, consumer, or route in the namespace. If you want the plugin to be available cluster-wide, create the resource as a KongClusterPlugin instead of KongPlugin.

Add this section to your declarative configuration file:

plugins:
- name: ai-proxy-advanced
  route: ROUTE_NAME|ID
  config:
    route_type: llm/v1/chat
    auth:
      azure_use_managed_identity: true
    model:
      provider: azure
      name: gpt-35-turbo
      options:
        azure_instance: my-openai-instance
        azure_deployment_id: kong-gpt-3-5

Replace ROUTE_NAME|ID with the id or name of the route that this plugin configuration will target.

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    auth = {
      azure_use_managed_identity = true
    }
    model = {
      provider = "azure"
      name = "gpt-35-turbo"
      options = {
        azure_instance = "my-openai-instance"
        azure_deployment_id = "kong-gpt-3-5"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
  route = {
    id = konnect_gateway_route.my_route.id
  }
}

Kong Admin API

Konnect API

Kubernetes

Declarative (YAML)

Konnect Terraform

Make the following request:

curl -X POST http://localhost:8001/consumer_groups/{consumerGroupName|Id}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "route_type": "llm/v1/chat",
    "auth": {
      "azure_use_managed_identity": true
    },
    "model": {
      "provider": "azure",
      "name": "gpt-35-turbo",
      "options": {
        "azure_instance": "my-openai-instance",
        "azure_deployment_id": "kong-gpt-3-5"
      }
    }
  }
}
    '

Replace CONSUMER_GROUP_NAME|ID with the id or name of the consumer group that this plugin configuration will target.

Make the following request, substituting your own access token, region, control plane ID, and consumer group ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/consumer_groups/{consumerGroupId}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"route_type":"llm/v1/chat","auth":{"azure_use_managed_identity":true},"model":{"provider":"azure","name":"gpt-35-turbo","options":{"azure_instance":"my-openai-instance","azure_deployment_id":"kong-gpt-3-5"}}}}'

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

First, create a KongPlugin resource:

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy-advanced-example
plugin: ai-proxy-advanced
config:
  route_type: llm/v1/chat
  auth:
    azure_use_managed_identity: true
  model:
    provider: azure
    name: gpt-35-turbo
    options:
      azure_instance: my-openai-instance
      azure_deployment_id: kong-gpt-3-5
" | kubectl apply -f -

Next, apply the KongPlugin resource to an ingress by annotating the KongConsumerGroup object as follows:

kubectl annotate KongConsumerGroup CONSUMER_GROUP_NAME konghq.com/plugins=ai-proxy-advanced-example

Replace CONSUMER_GROUP_NAME with the name of the consumer group that this plugin configuration will target. You can see your available consumer groups by running kubectl get KongConsumerGroup.

Note: The KongPlugin resource only needs to be defined once and can be applied to any service, consumer, consumer group, or route in the namespace. If you want the plugin to be available cluster-wide, create the resource as a KongClusterPlugin instead of KongPlugin.

Add this section to your declarative configuration file:

plugins:
- name: ai-proxy-advanced
  consumer_group: CONSUMER_GROUP_NAME|ID
  config:
    route_type: llm/v1/chat
    auth:
      azure_use_managed_identity: true
    model:
      provider: azure
      name: gpt-35-turbo
      options:
        azure_instance: my-openai-instance
        azure_deployment_id: kong-gpt-3-5

Replace CONSUMER_GROUP_NAME|ID with the id or name of the consumer group that this plugin configuration will target.

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    auth = {
      azure_use_managed_identity = true
    }
    model = {
      provider = "azure"
      name = "gpt-35-turbo"
      options = {
        azure_instance = "my-openai-instance"
        azure_deployment_id = "kong-gpt-3-5"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
  consumer_group = {
    id = konnect_gateway_consumer_group.my_consumer_group.id
  }
}

Kong Admin API

Konnect API

Kubernetes

Declarative (YAML)

Konnect Terraform

Make the following request:

curl -X POST http://localhost:8001/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "route_type": "llm/v1/chat",
    "auth": {
      "azure_use_managed_identity": true
    },
    "model": {
      "provider": "azure",
      "name": "gpt-35-turbo",
      "options": {
        "azure_instance": "my-openai-instance",
        "azure_deployment_id": "kong-gpt-3-5"
      }
    }
  }
}
    '

Make the following request, substituting your own access token, region, and control plane ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"route_type":"llm/v1/chat","auth":{"azure_use_managed_identity":true},"model":{"provider":"azure","name":"gpt-35-turbo","options":{"azure_instance":"my-openai-instance","azure_deployment_id":"kong-gpt-3-5"}}}}'

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

Create a KongClusterPlugin resource and label it as global:

apiVersion: configuration.konghq.com/v1
kind: KongClusterPlugin
metadata:
  name: <global-ai-proxy-advanced>
  annotations:
    kubernetes.io/ingress.class: kong
  labels:
    global: "true"
config:
  route_type: llm/v1/chat
  auth:
    azure_use_managed_identity: true
  model:
    provider: azure
    name: gpt-35-turbo
    options:
      azure_instance: my-openai-instance
      azure_deployment_id: kong-gpt-3-5
plugin: ai-proxy-advanced

Add a plugins entry in the declarative configuration file:

plugins:
- name: ai-proxy-advanced
  config:
    route_type: llm/v1/chat
    auth:
      azure_use_managed_identity: true
    model:
      provider: azure
      name: gpt-35-turbo
      options:
        azure_instance: my-openai-instance
        azure_deployment_id: kong-gpt-3-5

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    auth = {
      azure_use_managed_identity = true
    }
    model = {
      provider = "azure"
      name = "gpt-35-turbo"
      options = {
        azure_instance = "my-openai-instance"
        azure_deployment_id = "kong-gpt-3-5"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
}

User-Assigned Identity

To use a User-Assigned Identity, specify its client ID like this:

Enable on a route

Enable on a consumer group

Enable globally

Kong Admin API

Konnect API

Kubernetes

Declarative (YAML)

Konnect Terraform

Make the following request:

curl -X POST http://localhost:8001/routes/{routeName|Id}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "route_type": "llm/v1/chat",
    "auth": {
      "azure_use_managed_identity": true,
      "azure_client_id": "aabdecea-fc38-40ca-9edd-263878b290fe"
    },
    "model": {
      "provider": "azure",
      "name": "gpt-35-turbo",
      "options": {
        "azure_instance": "my-openai-instance",
        "azure_deployment_id": "kong-gpt-3-5"
      }
    }
  }
}
    '

Replace ROUTE_NAME|ID with the id or name of the route that this plugin configuration will target.

Make the following request, substituting your own access token, region, control plane ID, and route ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/routes/{routeId}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"route_type":"llm/v1/chat","auth":{"azure_use_managed_identity":true,"azure_client_id":"aabdecea-fc38-40ca-9edd-263878b290fe"},"model":{"provider":"azure","name":"gpt-35-turbo","options":{"azure_instance":"my-openai-instance","azure_deployment_id":"kong-gpt-3-5"}}}}'

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

First, create a KongPlugin resource:

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy-advanced-example
plugin: ai-proxy-advanced
config:
  route_type: llm/v1/chat
  auth:
    azure_use_managed_identity: true
    azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
  model:
    provider: azure
    name: gpt-35-turbo
    options:
      azure_instance: my-openai-instance
      azure_deployment_id: kong-gpt-3-5
" | kubectl apply -f -

Next, apply the KongPlugin resource to an ingress by annotating the ingress as follows:

kubectl annotate ingress INGRESS_NAME konghq.com/plugins=ai-proxy-advanced-example

Replace INGRESS_NAME with the name of the ingress that this plugin configuration will target. You can see your available ingresses by running kubectl get ingress.

Note: The KongPlugin resource only needs to be defined once and can be applied to any service, consumer, or route in the namespace. If you want the plugin to be available cluster-wide, create the resource as a KongClusterPlugin instead of KongPlugin.

Add this section to your declarative configuration file:

plugins:
- name: ai-proxy-advanced
  route: ROUTE_NAME|ID
  config:
    route_type: llm/v1/chat
    auth:
      azure_use_managed_identity: true
      azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
    model:
      provider: azure
      name: gpt-35-turbo
      options:
        azure_instance: my-openai-instance
        azure_deployment_id: kong-gpt-3-5

Replace ROUTE_NAME|ID with the id or name of the route that this plugin configuration will target.

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    auth = {
      azure_use_managed_identity = true
      azure_client_id = "aabdecea-fc38-40ca-9edd-263878b290fe"
    }
    model = {
      provider = "azure"
      name = "gpt-35-turbo"
      options = {
        azure_instance = "my-openai-instance"
        azure_deployment_id = "kong-gpt-3-5"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
  route = {
    id = konnect_gateway_route.my_route.id
  }
}

Kong Admin API

Konnect API

Kubernetes

Declarative (YAML)

Konnect Terraform

Make the following request:

curl -X POST http://localhost:8001/consumer_groups/{consumerGroupName|Id}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "route_type": "llm/v1/chat",
    "auth": {
      "azure_use_managed_identity": true,
      "azure_client_id": "aabdecea-fc38-40ca-9edd-263878b290fe"
    },
    "model": {
      "provider": "azure",
      "name": "gpt-35-turbo",
      "options": {
        "azure_instance": "my-openai-instance",
        "azure_deployment_id": "kong-gpt-3-5"
      }
    }
  }
}
    '

Replace CONSUMER_GROUP_NAME|ID with the id or name of the consumer group that this plugin configuration will target.

Make the following request, substituting your own access token, region, control plane ID, and consumer group ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/consumer_groups/{consumerGroupId}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"route_type":"llm/v1/chat","auth":{"azure_use_managed_identity":true,"azure_client_id":"aabdecea-fc38-40ca-9edd-263878b290fe"},"model":{"provider":"azure","name":"gpt-35-turbo","options":{"azure_instance":"my-openai-instance","azure_deployment_id":"kong-gpt-3-5"}}}}'

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

First, create a KongPlugin resource:

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy-advanced-example
plugin: ai-proxy-advanced
config:
  route_type: llm/v1/chat
  auth:
    azure_use_managed_identity: true
    azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
  model:
    provider: azure
    name: gpt-35-turbo
    options:
      azure_instance: my-openai-instance
      azure_deployment_id: kong-gpt-3-5
" | kubectl apply -f -

Next, apply the KongPlugin resource to an ingress by annotating the KongConsumerGroup object as follows:

kubectl annotate KongConsumerGroup CONSUMER_GROUP_NAME konghq.com/plugins=ai-proxy-advanced-example

Replace CONSUMER_GROUP_NAME with the name of the consumer group that this plugin configuration will target. You can see your available consumer groups by running kubectl get KongConsumerGroup.

Note: The KongPlugin resource only needs to be defined once and can be applied to any service, consumer, consumer group, or route in the namespace. If you want the plugin to be available cluster-wide, create the resource as a KongClusterPlugin instead of KongPlugin.

Add this section to your declarative configuration file:

plugins:
- name: ai-proxy-advanced
  consumer_group: CONSUMER_GROUP_NAME|ID
  config:
    route_type: llm/v1/chat
    auth:
      azure_use_managed_identity: true
      azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
    model:
      provider: azure
      name: gpt-35-turbo
      options:
        azure_instance: my-openai-instance
        azure_deployment_id: kong-gpt-3-5

Replace CONSUMER_GROUP_NAME|ID with the id or name of the consumer group that this plugin configuration will target.

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    auth = {
      azure_use_managed_identity = true
      azure_client_id = "aabdecea-fc38-40ca-9edd-263878b290fe"
    }
    model = {
      provider = "azure"
      name = "gpt-35-turbo"
      options = {
        azure_instance = "my-openai-instance"
        azure_deployment_id = "kong-gpt-3-5"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
  consumer_group = {
    id = konnect_gateway_consumer_group.my_consumer_group.id
  }
}

Kong Admin API

Konnect API

Kubernetes

Declarative (YAML)

Konnect Terraform

Make the following request:

curl -X POST http://localhost:8001/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "route_type": "llm/v1/chat",
    "auth": {
      "azure_use_managed_identity": true,
      "azure_client_id": "aabdecea-fc38-40ca-9edd-263878b290fe"
    },
    "model": {
      "provider": "azure",
      "name": "gpt-35-turbo",
      "options": {
        "azure_instance": "my-openai-instance",
        "azure_deployment_id": "kong-gpt-3-5"
      }
    }
  }
}
    '

Make the following request, substituting your own access token, region, and control plane ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"route_type":"llm/v1/chat","auth":{"azure_use_managed_identity":true,"azure_client_id":"aabdecea-fc38-40ca-9edd-263878b290fe"},"model":{"provider":"azure","name":"gpt-35-turbo","options":{"azure_instance":"my-openai-instance","azure_deployment_id":"kong-gpt-3-5"}}}}'

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

Create a KongClusterPlugin resource and label it as global:

apiVersion: configuration.konghq.com/v1
kind: KongClusterPlugin
metadata:
  name: <global-ai-proxy-advanced>
  annotations:
    kubernetes.io/ingress.class: kong
  labels:
    global: "true"
config:
  route_type: llm/v1/chat
  auth:
    azure_use_managed_identity: true
    azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
  model:
    provider: azure
    name: gpt-35-turbo
    options:
      azure_instance: my-openai-instance
      azure_deployment_id: kong-gpt-3-5
plugin: ai-proxy-advanced

Add a plugins entry in the declarative configuration file:

plugins:
- name: ai-proxy-advanced
  config:
    route_type: llm/v1/chat
    auth:
      azure_use_managed_identity: true
      azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
    model:
      provider: azure
      name: gpt-35-turbo
      options:
        azure_instance: my-openai-instance
        azure_deployment_id: kong-gpt-3-5

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    auth = {
      azure_use_managed_identity = true
      azure_client_id = "aabdecea-fc38-40ca-9edd-263878b290fe"
    }
    model = {
      provider = "azure"
      name = "gpt-35-turbo"
      options = {
        azure_instance = "my-openai-instance"
        azure_deployment_id = "kong-gpt-3-5"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
}

Using Entra or app registration

If running outside of Azure, to use an Entra principal or app registration, specify all properties like this:

Enable on a route

Enable on a consumer group

Enable globally

Kong Admin API

Konnect API

Kubernetes

Declarative (YAML)

Konnect Terraform

Make the following request:

curl -X POST http://localhost:8001/routes/{routeName|Id}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "route_type": "llm/v1/chat",
    "auth": {
      "azure_use_managed_identity": true,
      "azure_client_id": "aabdecea-fc38-40ca-9edd-263878b290fe",
      "azure_client_secret": "be0c34b6-b5f1-4343-99a3-140df73e0c1c",
      "azure_tenant_id": "1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"
    },
    "model": {
      "provider": "azure",
      "name": "gpt-35-turbo",
      "options": {
        "azure_instance": "my-openai-instance",
        "azure_deployment_id": "kong-gpt-3-5"
      }
    }
  }
}
    '

Replace ROUTE_NAME|ID with the id or name of the route that this plugin configuration will target.

Make the following request, substituting your own access token, region, control plane ID, and route ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/routes/{routeId}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"route_type":"llm/v1/chat","auth":{"azure_use_managed_identity":true,"azure_client_id":"aabdecea-fc38-40ca-9edd-263878b290fe","azure_client_secret":"be0c34b6-b5f1-4343-99a3-140df73e0c1c","azure_tenant_id":"1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"},"model":{"provider":"azure","name":"gpt-35-turbo","options":{"azure_instance":"my-openai-instance","azure_deployment_id":"kong-gpt-3-5"}}}}'

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

First, create a KongPlugin resource:

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy-advanced-example
plugin: ai-proxy-advanced
config:
  route_type: llm/v1/chat
  auth:
    azure_use_managed_identity: true
    azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
    azure_client_secret: be0c34b6-b5f1-4343-99a3-140df73e0c1c
    azure_tenant_id: 1e583ecd-9293-4db1-b1c0-2b6126cb5fdd
  model:
    provider: azure
    name: gpt-35-turbo
    options:
      azure_instance: my-openai-instance
      azure_deployment_id: kong-gpt-3-5
" | kubectl apply -f -

Next, apply the KongPlugin resource to an ingress by annotating the ingress as follows:

kubectl annotate ingress INGRESS_NAME konghq.com/plugins=ai-proxy-advanced-example

Replace INGRESS_NAME with the name of the ingress that this plugin configuration will target. You can see your available ingresses by running kubectl get ingress.

Note: The KongPlugin resource only needs to be defined once and can be applied to any service, consumer, or route in the namespace. If you want the plugin to be available cluster-wide, create the resource as a KongClusterPlugin instead of KongPlugin.

Add this section to your declarative configuration file:

plugins:
- name: ai-proxy-advanced
  route: ROUTE_NAME|ID
  config:
    route_type: llm/v1/chat
    auth:
      azure_use_managed_identity: true
      azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
      azure_client_secret: be0c34b6-b5f1-4343-99a3-140df73e0c1c
      azure_tenant_id: 1e583ecd-9293-4db1-b1c0-2b6126cb5fdd
    model:
      provider: azure
      name: gpt-35-turbo
      options:
        azure_instance: my-openai-instance
        azure_deployment_id: kong-gpt-3-5

Replace ROUTE_NAME|ID with the id or name of the route that this plugin configuration will target.

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    auth = {
      azure_use_managed_identity = true
      azure_client_id = "aabdecea-fc38-40ca-9edd-263878b290fe"
      azure_client_secret = "be0c34b6-b5f1-4343-99a3-140df73e0c1c"
      azure_tenant_id = "1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"
    }
    model = {
      provider = "azure"
      name = "gpt-35-turbo"
      options = {
        azure_instance = "my-openai-instance"
        azure_deployment_id = "kong-gpt-3-5"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
  route = {
    id = konnect_gateway_route.my_route.id
  }
}

Kong Admin API

Konnect API

Kubernetes

Declarative (YAML)

Konnect Terraform

Make the following request:

curl -X POST http://localhost:8001/consumer_groups/{consumerGroupName|Id}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "route_type": "llm/v1/chat",
    "auth": {
      "azure_use_managed_identity": true,
      "azure_client_id": "aabdecea-fc38-40ca-9edd-263878b290fe",
      "azure_client_secret": "be0c34b6-b5f1-4343-99a3-140df73e0c1c",
      "azure_tenant_id": "1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"
    },
    "model": {
      "provider": "azure",
      "name": "gpt-35-turbo",
      "options": {
        "azure_instance": "my-openai-instance",
        "azure_deployment_id": "kong-gpt-3-5"
      }
    }
  }
}
    '

Replace CONSUMER_GROUP_NAME|ID with the id or name of the consumer group that this plugin configuration will target.

Make the following request, substituting your own access token, region, control plane ID, and consumer group ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/consumer_groups/{consumerGroupId}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"route_type":"llm/v1/chat","auth":{"azure_use_managed_identity":true,"azure_client_id":"aabdecea-fc38-40ca-9edd-263878b290fe","azure_client_secret":"be0c34b6-b5f1-4343-99a3-140df73e0c1c","azure_tenant_id":"1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"},"model":{"provider":"azure","name":"gpt-35-turbo","options":{"azure_instance":"my-openai-instance","azure_deployment_id":"kong-gpt-3-5"}}}}'

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

First, create a KongPlugin resource:

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy-advanced-example
plugin: ai-proxy-advanced
config:
  route_type: llm/v1/chat
  auth:
    azure_use_managed_identity: true
    azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
    azure_client_secret: be0c34b6-b5f1-4343-99a3-140df73e0c1c
    azure_tenant_id: 1e583ecd-9293-4db1-b1c0-2b6126cb5fdd
  model:
    provider: azure
    name: gpt-35-turbo
    options:
      azure_instance: my-openai-instance
      azure_deployment_id: kong-gpt-3-5
" | kubectl apply -f -

Next, apply the KongPlugin resource to an ingress by annotating the KongConsumerGroup object as follows:

kubectl annotate KongConsumerGroup CONSUMER_GROUP_NAME konghq.com/plugins=ai-proxy-advanced-example

Replace CONSUMER_GROUP_NAME with the name of the consumer group that this plugin configuration will target. You can see your available consumer groups by running kubectl get KongConsumerGroup.

Note: The KongPlugin resource only needs to be defined once and can be applied to any service, consumer, consumer group, or route in the namespace. If you want the plugin to be available cluster-wide, create the resource as a KongClusterPlugin instead of KongPlugin.

Add this section to your declarative configuration file:

plugins:
- name: ai-proxy-advanced
  consumer_group: CONSUMER_GROUP_NAME|ID
  config:
    route_type: llm/v1/chat
    auth:
      azure_use_managed_identity: true
      azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
      azure_client_secret: be0c34b6-b5f1-4343-99a3-140df73e0c1c
      azure_tenant_id: 1e583ecd-9293-4db1-b1c0-2b6126cb5fdd
    model:
      provider: azure
      name: gpt-35-turbo
      options:
        azure_instance: my-openai-instance
        azure_deployment_id: kong-gpt-3-5

Replace CONSUMER_GROUP_NAME|ID with the id or name of the consumer group that this plugin configuration will target.

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    auth = {
      azure_use_managed_identity = true
      azure_client_id = "aabdecea-fc38-40ca-9edd-263878b290fe"
      azure_client_secret = "be0c34b6-b5f1-4343-99a3-140df73e0c1c"
      azure_tenant_id = "1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"
    }
    model = {
      provider = "azure"
      name = "gpt-35-turbo"
      options = {
        azure_instance = "my-openai-instance"
        azure_deployment_id = "kong-gpt-3-5"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
  consumer_group = {
    id = konnect_gateway_consumer_group.my_consumer_group.id
  }
}

Kong Admin API

Konnect API

Kubernetes

Declarative (YAML)

Konnect Terraform

Make the following request:

curl -X POST http://localhost:8001/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "route_type": "llm/v1/chat",
    "auth": {
      "azure_use_managed_identity": true,
      "azure_client_id": "aabdecea-fc38-40ca-9edd-263878b290fe",
      "azure_client_secret": "be0c34b6-b5f1-4343-99a3-140df73e0c1c",
      "azure_tenant_id": "1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"
    },
    "model": {
      "provider": "azure",
      "name": "gpt-35-turbo",
      "options": {
        "azure_instance": "my-openai-instance",
        "azure_deployment_id": "kong-gpt-3-5"
      }
    }
  }
}
    '

Make the following request, substituting your own access token, region, and control plane ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"route_type":"llm/v1/chat","auth":{"azure_use_managed_identity":true,"azure_client_id":"aabdecea-fc38-40ca-9edd-263878b290fe","azure_client_secret":"be0c34b6-b5f1-4343-99a3-140df73e0c1c","azure_tenant_id":"1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"},"model":{"provider":"azure","name":"gpt-35-turbo","options":{"azure_instance":"my-openai-instance","azure_deployment_id":"kong-gpt-3-5"}}}}'

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

Create a KongClusterPlugin resource and label it as global:

apiVersion: configuration.konghq.com/v1
kind: KongClusterPlugin
metadata:
  name: <global-ai-proxy-advanced>
  annotations:
    kubernetes.io/ingress.class: kong
  labels:
    global: "true"
config:
  route_type: llm/v1/chat
  auth:
    azure_use_managed_identity: true
    azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
    azure_client_secret: be0c34b6-b5f1-4343-99a3-140df73e0c1c
    azure_tenant_id: 1e583ecd-9293-4db1-b1c0-2b6126cb5fdd
  model:
    provider: azure
    name: gpt-35-turbo
    options:
      azure_instance: my-openai-instance
      azure_deployment_id: kong-gpt-3-5
plugin: ai-proxy-advanced

Add a plugins entry in the declarative configuration file:

plugins:
- name: ai-proxy-advanced
  config:
    route_type: llm/v1/chat
    auth:
      azure_use_managed_identity: true
      azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
      azure_client_secret: be0c34b6-b5f1-4343-99a3-140df73e0c1c
      azure_tenant_id: 1e583ecd-9293-4db1-b1c0-2b6126cb5fdd
    model:
      provider: azure
      name: gpt-35-turbo
      options:
        azure_instance: my-openai-instance
        azure_deployment_id: kong-gpt-3-5

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    auth = {
      azure_use_managed_identity = true
      azure_client_id = "aabdecea-fc38-40ca-9edd-263878b290fe"
      azure_client_secret = "be0c34b6-b5f1-4343-99a3-140df73e0c1c"
      azure_tenant_id = "1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"
    }
    model = {
      provider = "azure"
      name = "gpt-35-turbo"
      options = {
        azure_instance = "my-openai-instance"
        azure_deployment_id = "kong-gpt-3-5"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
}

Environment variables

You can also specify some (or all) of these properties as environment variables. For example:

Environment variable:

AZURE_CLIENT_SECRET="be0c34b6-b5f1-4343-99a3-140df73e0c1c"

Plugin configuration:

Enable on a route

Enable on a consumer group

Enable globally

Kong Admin API

Konnect API

Kubernetes

Declarative (YAML)

Konnect Terraform

Make the following request:

curl -X POST http://localhost:8001/routes/{routeName|Id}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "route_type": "llm/v1/chat",
    "auth": {
      "azure_use_managed_identity": true,
      "azure_client_id": "aabdecea-fc38-40ca-9edd-263878b290fe",
      "azure_tenant_id": "1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"
    },
    "model": {
      "provider": "azure",
      "name": "gpt-35-turbo",
      "options": {
        "azure_instance": "my-openai-instance",
        "azure_deployment_id": "kong-gpt-3-5"
      }
    }
  }
}
    '

Replace ROUTE_NAME|ID with the id or name of the route that this plugin configuration will target.

Make the following request, substituting your own access token, region, control plane ID, and route ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/routes/{routeId}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"route_type":"llm/v1/chat","auth":{"azure_use_managed_identity":true,"azure_client_id":"aabdecea-fc38-40ca-9edd-263878b290fe","azure_tenant_id":"1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"},"model":{"provider":"azure","name":"gpt-35-turbo","options":{"azure_instance":"my-openai-instance","azure_deployment_id":"kong-gpt-3-5"}}}}'

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

First, create a KongPlugin resource:

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy-advanced-example
plugin: ai-proxy-advanced
config:
  route_type: llm/v1/chat
  auth:
    azure_use_managed_identity: true
    azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
    azure_tenant_id: 1e583ecd-9293-4db1-b1c0-2b6126cb5fdd
  model:
    provider: azure
    name: gpt-35-turbo
    options:
      azure_instance: my-openai-instance
      azure_deployment_id: kong-gpt-3-5
" | kubectl apply -f -

Next, apply the KongPlugin resource to an ingress by annotating the ingress as follows:

kubectl annotate ingress INGRESS_NAME konghq.com/plugins=ai-proxy-advanced-example

Replace INGRESS_NAME with the name of the ingress that this plugin configuration will target. You can see your available ingresses by running kubectl get ingress.

Note: The KongPlugin resource only needs to be defined once and can be applied to any service, consumer, or route in the namespace. If you want the plugin to be available cluster-wide, create the resource as a KongClusterPlugin instead of KongPlugin.

Add this section to your declarative configuration file:

plugins:
- name: ai-proxy-advanced
  route: ROUTE_NAME|ID
  config:
    route_type: llm/v1/chat
    auth:
      azure_use_managed_identity: true
      azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
      azure_tenant_id: 1e583ecd-9293-4db1-b1c0-2b6126cb5fdd
    model:
      provider: azure
      name: gpt-35-turbo
      options:
        azure_instance: my-openai-instance
        azure_deployment_id: kong-gpt-3-5

Replace ROUTE_NAME|ID with the id or name of the route that this plugin configuration will target.

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    auth = {
      azure_use_managed_identity = true
      azure_client_id = "aabdecea-fc38-40ca-9edd-263878b290fe"
      azure_tenant_id = "1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"
    }
    model = {
      provider = "azure"
      name = "gpt-35-turbo"
      options = {
        azure_instance = "my-openai-instance"
        azure_deployment_id = "kong-gpt-3-5"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
  route = {
    id = konnect_gateway_route.my_route.id
  }
}

Kong Admin API

Konnect API

Kubernetes

Declarative (YAML)

Konnect Terraform

Make the following request:

curl -X POST http://localhost:8001/consumer_groups/{consumerGroupName|Id}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "route_type": "llm/v1/chat",
    "auth": {
      "azure_use_managed_identity": true,
      "azure_client_id": "aabdecea-fc38-40ca-9edd-263878b290fe",
      "azure_tenant_id": "1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"
    },
    "model": {
      "provider": "azure",
      "name": "gpt-35-turbo",
      "options": {
        "azure_instance": "my-openai-instance",
        "azure_deployment_id": "kong-gpt-3-5"
      }
    }
  }
}
    '

Replace CONSUMER_GROUP_NAME|ID with the id or name of the consumer group that this plugin configuration will target.

Make the following request, substituting your own access token, region, control plane ID, and consumer group ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/consumer_groups/{consumerGroupId}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"route_type":"llm/v1/chat","auth":{"azure_use_managed_identity":true,"azure_client_id":"aabdecea-fc38-40ca-9edd-263878b290fe","azure_tenant_id":"1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"},"model":{"provider":"azure","name":"gpt-35-turbo","options":{"azure_instance":"my-openai-instance","azure_deployment_id":"kong-gpt-3-5"}}}}'

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

First, create a KongPlugin resource:

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy-advanced-example
plugin: ai-proxy-advanced
config:
  route_type: llm/v1/chat
  auth:
    azure_use_managed_identity: true
    azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
    azure_tenant_id: 1e583ecd-9293-4db1-b1c0-2b6126cb5fdd
  model:
    provider: azure
    name: gpt-35-turbo
    options:
      azure_instance: my-openai-instance
      azure_deployment_id: kong-gpt-3-5
" | kubectl apply -f -

Next, apply the KongPlugin resource to an ingress by annotating the KongConsumerGroup object as follows:

kubectl annotate KongConsumerGroup CONSUMER_GROUP_NAME konghq.com/plugins=ai-proxy-advanced-example

Replace CONSUMER_GROUP_NAME with the name of the consumer group that this plugin configuration will target. You can see your available consumer groups by running kubectl get KongConsumerGroup.

Note: The KongPlugin resource only needs to be defined once and can be applied to any service, consumer, consumer group, or route in the namespace. If you want the plugin to be available cluster-wide, create the resource as a KongClusterPlugin instead of KongPlugin.

Add this section to your declarative configuration file:

plugins:
- name: ai-proxy-advanced
  consumer_group: CONSUMER_GROUP_NAME|ID
  config:
    route_type: llm/v1/chat
    auth:
      azure_use_managed_identity: true
      azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
      azure_tenant_id: 1e583ecd-9293-4db1-b1c0-2b6126cb5fdd
    model:
      provider: azure
      name: gpt-35-turbo
      options:
        azure_instance: my-openai-instance
        azure_deployment_id: kong-gpt-3-5

Replace CONSUMER_GROUP_NAME|ID with the id or name of the consumer group that this plugin configuration will target.

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    auth = {
      azure_use_managed_identity = true
      azure_client_id = "aabdecea-fc38-40ca-9edd-263878b290fe"
      azure_tenant_id = "1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"
    }
    model = {
      provider = "azure"
      name = "gpt-35-turbo"
      options = {
        azure_instance = "my-openai-instance"
        azure_deployment_id = "kong-gpt-3-5"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
  consumer_group = {
    id = konnect_gateway_consumer_group.my_consumer_group.id
  }
}

Kong Admin API

Konnect API

Kubernetes

Declarative (YAML)

Konnect Terraform

Make the following request:

curl -X POST http://localhost:8001/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "route_type": "llm/v1/chat",
    "auth": {
      "azure_use_managed_identity": true,
      "azure_client_id": "aabdecea-fc38-40ca-9edd-263878b290fe",
      "azure_tenant_id": "1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"
    },
    "model": {
      "provider": "azure",
      "name": "gpt-35-turbo",
      "options": {
        "azure_instance": "my-openai-instance",
        "azure_deployment_id": "kong-gpt-3-5"
      }
    }
  }
}
    '

Make the following request, substituting your own access token, region, and control plane ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"route_type":"llm/v1/chat","auth":{"azure_use_managed_identity":true,"azure_client_id":"aabdecea-fc38-40ca-9edd-263878b290fe","azure_tenant_id":"1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"},"model":{"provider":"azure","name":"gpt-35-turbo","options":{"azure_instance":"my-openai-instance","azure_deployment_id":"kong-gpt-3-5"}}}}'

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

Create a KongClusterPlugin resource and label it as global:

apiVersion: configuration.konghq.com/v1
kind: KongClusterPlugin
metadata:
  name: <global-ai-proxy-advanced>
  annotations:
    kubernetes.io/ingress.class: kong
  labels:
    global: "true"
config:
  route_type: llm/v1/chat
  auth:
    azure_use_managed_identity: true
    azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
    azure_tenant_id: 1e583ecd-9293-4db1-b1c0-2b6126cb5fdd
  model:
    provider: azure
    name: gpt-35-turbo
    options:
      azure_instance: my-openai-instance
      azure_deployment_id: kong-gpt-3-5
plugin: ai-proxy-advanced

Add a plugins entry in the declarative configuration file:

plugins:
- name: ai-proxy-advanced
  config:
    route_type: llm/v1/chat
    auth:
      azure_use_managed_identity: true
      azure_client_id: aabdecea-fc38-40ca-9edd-263878b290fe
      azure_tenant_id: 1e583ecd-9293-4db1-b1c0-2b6126cb5fdd
    model:
      provider: azure
      name: gpt-35-turbo
      options:
        azure_instance: my-openai-instance
        azure_deployment_id: kong-gpt-3-5

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    auth = {
      azure_use_managed_identity = true
      azure_client_id = "aabdecea-fc38-40ca-9edd-263878b290fe"
      azure_tenant_id = "1e583ecd-9293-4db1-b1c0-2b6126cb5fdd"
    }
    model = {
      provider = "azure"
      name = "gpt-35-turbo"
      options = {
        azure_instance = "my-openai-instance"
        azure_deployment_id = "kong-gpt-3-5"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
}

Previous Basic config examples for AI Proxy Advanced

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