Elastic Inference Service for Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, and self-managed clusters

Elastic Inference Service (EIS) is available with zero setup on Elastic Cloud Hosted and Serverless deployments. To use EIS with Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, or self-managed clusters, you can use Cloud Connect. Cloud Connect enables you to use Elastic Cloud services in your Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, or self-managed cluster without having to install and maintain their infrastructure yourself.

You can use EIS to enable features such as:

For a full list of EIS-powered features, refer to AI features powered by EIS.

Prerequisites

Before you can use EIS with an Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, or self-managed cluster, ensure you meet the following requirements:

Your cluster runs Elasticsearch 9.3 or later.
Your cluster has an Enterprise self-managed license or an active self-managed trial license.
You have an Elastic Cloud account with either an active Cloud Trial or billing information configured. Note that you will not have full access to the model catalog.

Set up EIS with Cloud Connect

Open Cloud Connect

In Kibana on your Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, or self-managed cluster, navigate to the Cloud Connect page using the search bar.
Get your Cloud Connect API key

Sign up or log in to Elastic Cloud and get the Cloud Connect API key:
- If you don’t have an account yet, click Sign up and follow the prompts to create your account and start a free Cloud Trial.
- If you already have an Elastic Cloud account, click Log in.
Connect your cluster

Copy the Cloud Connect API key, paste it into your cluster's Cloud Connect page, then click Connect.
Enable Elastic Inference Service

On the Cloud connected services page, click Connect for Elastic Inference Service.

After you connect Elastic Inference Service through Cloud Connect, Elasticsearch automatically creates multiple inference endpoints for search and chat use cases. Supported Kibana features now use these endpoints automatically.

Test EIS through Cloud Connect with semantic search

In this example, you create an index with a semantic_text field, index a document, then run a query that returns a semantically related match.

In Dev Tools, run the following requests:

Create an index with a semantic_text field
JSON
```
PUT /semantic-search-eis
{
  "mappings": {
    "properties": {
      "text": {
        "type": "semantic_text"
      }
    }
  }
}
```
1. Because you already enabled EIS, the semantic_text field type uses EIS through the default inference endpoint.

Index a document

POST /semantic-search-eis/_doc
{
  "text": "Aberdeen Football Club"
}

Run a search query

GET /semantic-search-eis/_search
{
  "query": {
    "match": {
      "text": "soccer"
    }
  }
}

The response should include the indexed document:

{
  "took": 161,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 1,
      "relation": "eq"
    },
    "max_score": 4.729913,
    "hits": [
      {
        "_index": "semantic-search-eis",
        "_id": "oyH935sBG2FaZ-zOMrer",
        "_score": 4.729913,
        "_source": {
          "text": "Aberdeen Football Club"
        }
      }
    ]
  }
}

Supported models with EIS through Cloud Connect

Using Elastic Inference Service through Cloud Connect, you have access to all available models listed under Supported models, including LLMs, embedding models, and rerankers.

To use these models:

The Elastic Stack includes Elastic's core products such as Elasticsearch, Kibana, Logstash, and Beats. Availability Generally available since 9.3 This functionality is generally available and ready for production usage. Unless stated otherwise on the page, this functionality is available when your Elastic Stack is deployed on Elastic Cloud Hosted, Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, and self-managed environments. This documentation corresponds to the latest patch available for each minor version. If you're not using the latest patch, check the release notes for changes. You need Kibana connectors (for LLMs) or inference endpoints. There are preconfigured inference endpoints for all models. For some LLMs, connectors need to be created manually.
The Elastic Stack includes Elastic's core products such as Elasticsearch, Kibana, Logstash, and Beats. Availability Generally available since 9.4 This functionality is generally available and ready for production usage. Unless stated otherwise on the page, this functionality is available when your Elastic Stack is deployed on Elastic Cloud Hosted, Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, and self-managed environments. This documentation corresponds to the latest patch available for each minor version. If you're not using the latest patch, check the release notes for changes. Use the preconfigured inference endpoints or create custom endpoints as described in Elastic Inference Service.

Embedding and rerank models

Predefined inference endpoints and connectors are available for all models listed under Embedding models and Rerankers.

For these models, you only need to create new inference endpoints if you want to use custom settings.

Regions and billing

For information about EIS regions and request routing, refer to Region and hosting.

EIS is billed per million tokens and consumes ECUs. For details on pricing and usage tracking, refer to Pricing and Monitor your token usage.