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deploy-manage/remote-clusters/ec-remote-cluster-ece.md

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@@ -204,13 +204,13 @@ On the local cluster, add the remote cluster using {{kib}} or the {{es}} API.
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* **Name**: This *cluster alias* is a unique identifier that represents the connection to the remote cluster and is used to distinguish local and remote indices.
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When using API key authentication, this alias must match the **Remote cluster name** you configured when adding the API key in the Cloud UI.
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* **Proxy address**: This value can be found on the **Security** page of the {{ech}} deployment you want to use as a remote.<br>
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* **Proxy address**: This value can be found on the **Security** page of the {{ece}} deployment you want to use as a remote.<br>
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::::{tip}
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If you’re using API keys as security model, change the port into `9443`.
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::::
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* **Server name**: This value can be found on the **Security** page of the {{ech}} deployment you want to use as a remote.
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* **Server name**: This value can be found on the **Security** page of the {{ece}} deployment you want to use as a remote.
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::::{note}
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If you’re having issues establishing the connection and the remote cluster is part of an {{ece}} environment with a private certificate, make sure that the proxy address and server name match with the the certificate information. For more information, refer to [Administering endpoints in {{ece}}](/deploy-manage/deploy/cloud-enterprise/change-endpoint-urls.md).

deploy-manage/remote-clusters/remote-clusters-api-key.md

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On the local cluster side, not every local user needs to access every piece of data allowed by the API key. An administrator of the local cluster can further configure additional permission constraints on local users so each user only gets access to the necessary remote data. Note it is only possible to further reduce the permissions allowed by the API key for individual local users. It is impossible to increase the permissions to go beyond what is allowed by the API key.
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In this model, cross-cluster operations use [a dedicated server port](elasticsearch://reference/elasticsearch/configuration-reference/networking-settings.md#remote_cluster.port) (remote cluster interface) for communication between clusters. A remote cluster must enable this port for local clusters to connect. Configure Transport Layer Security (TLS) for this port to maximize security (as explained in [Establish trust with a remote cluster](#remote-clusters-security-api-key)).
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In this model, cross-cluster operations use [a dedicated server port](elasticsearch://reference/elasticsearch/configuration-reference/networking-settings.md#remote_cluster.port) (remote cluster interface) for communication between clusters, which defaults to port `9443`. A remote cluster must enable this port for local clusters to connect. Configure Transport Layer Security (TLS) for this port to maximize security (as explained in [Establish trust with a remote cluster](#remote-clusters-security-api-key)).
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The local cluster must trust the remote cluster on the remote cluster interface. This means that the local cluster trusts the remote cluster’s certificate authority (CA) that signs the server certificate used by the remote cluster interface. When establishing a connection, all nodes from the local cluster that participate in cross-cluster communication verify certificates from nodes on the other side, based on the TLS trust configuration.
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## Establish trust with a remote cluster [remote-clusters-security-api-key]
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::::{note}
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If a remote cluster is part of an {{ech}} deployment, it has a valid certificate by default. You can therefore skip steps related to certificates in these instructions.
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If a remote cluster is part of an {{ech}} (ECH) deployment, the remote cluster server is enabled by default and it uses a publicly trusted certificate provided by the platform proxies. Therefore, you can skip the following steps in these instructions:
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**On the remote (ECH) cluster:** Skip steps 1-4 (enabling the service, generating certificates, configuring SSL settings, and restarting the cluster), and go directly to step 5 (create an API key).
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**On the local (self-managed) cluster:** Do not add the `xpack.security.remote_cluster_client.ssl.certificate_authorities` setting to the configuration file because ECH uses publicly trusted certificates that don't require custom CA configuration.
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xpack.security.remote_cluster_client.ssl.certificate_authorities: [ "remote-cluster-ca.crt" ]
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```
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::::{tip}
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If the remote cluster uses a publicly trusted certificate, don't include the `certificate_authorities` setting. This example assumes the remote is using the private certificates [created earlier](#remote-clusters-security-api-key-remote-action), which require the CA to be added.
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::::
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3. Add the cross-cluster API key, created on the remote cluster earlier, to the keystore:
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```sh
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2. Enter a name (*cluster alias*) for the remote cluster.
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3. Specify the {{es}} endpoint URL, or the IP address or host name of the remote cluster followed by the remote cluster port (defaults to `9443`). For example, `cluster.es.eastus2.staging.azure.foundit.no:9443` or `192.168.1.1:9443`.
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::::{note}
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If the remote cluster is part of an {{ech}}, {{ece}}, or {{eck}} deployment, configure the connection to use `proxy`. The default `sniff` mode doesn't work in these environments. Refer to the [connection modes](/deploy-manage/remote-clusters/remote-clusters-self-managed.md#sniff-proxy-modes) description for more information.
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::::
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Alternatively, use the [cluster update settings API](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-cluster-put-settings) to add a remote cluster. You can also use this API to dynamically configure remote clusters for *every* node in the local cluster. To configure remote clusters on individual nodes in the local cluster, define static settings in [`elasticsearch.yml`](/deploy-manage/stack-settings.md) for each node.
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The following request adds a remote cluster with an alias of `cluster_one`. This *cluster alias* is a unique identifier that represents the connection to the remote cluster and is used to distinguish between local and remote indices.

explore-analyze/elastic-inference/eis.md

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ELSER on EIS enables you to use the ELSER model on GPUs, without having to manage your own ML nodes. We expect significantly better performance for throughput and consistent search latency as compared to ML nodes, and will continue to benchmark, remove limitations and address concerns as we move towards General Availability.
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### Usage
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### Using the ELSER on EIS endpoint
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You can now use `semantic_text` with the new ELSER endpoint on EIS, see the [instructions to change the inference id](https://www.elastic.co/docs/reference/elasticsearch/mapping-reference/semantic-text#using-elser-on-eis) to use the `.elser-2-elastic` inference endpoint.
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You can now use `semantic_text` with the new ELSER endpoint on EIS. To learn how to use the `.elser-2-elastic` inference endpoint, refer to [Using ELSER on EIS](elasticsearch://reference/elasticsearch/mapping-reference/semantic-tex.md#using-elser-on-eis).
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#### Get started with semantic search with ELSER on EIS
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[Semantic Search with `semantic_text`](/solutions/search/semantic-search/semantic-search-semantic-text.md) has a detailed tutorial on using the `semantic_text` field and using the ELSER endpoint on EIS instead of the default endpoint. This is a great way to get started and try the new endpoint.
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### Limitations
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solutions/search/semantic-search/semantic-search-semantic-text.md

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1. The name of the field to contain the generated embeddings.
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2. The field to contain the embeddings is a `semantic_text` field. Since no `inference_id` is provided, the default endpoint `.elser-2-elasticsearch` for the `elasticsearch` service is used. To use a different {{infer}} service, you must create an {{infer}} endpoint first using the [Create {{infer}} API](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-inference-put) and then specify it in the `semantic_text` field mapping using the `inference_id` parameter.
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To try the ELSER model on the Elastic Inference Service, explicitly set the `inference_id` to `.elser-2-elastic`. For instructions, refer to [Using `semantic_text` with ELSER on EIS](https://www.elastic.co/docs/reference/elasticsearch/mapping-reference/semantic-text#using-elser-on-eis).
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::::{note}
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If you’re using web crawlers or connectors to generate indices, you have to [update the index mappings](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-indices-put-mapping) for these indices to include the `semantic_text` field. Once the mapping is updated, you’ll need to run a full web crawl or a full connector sync. This ensures that all existing documents are reprocessed and updated with the new semantic embeddings, enabling semantic search on the updated data.
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* If you want to use `semantic_text` in hybrid search, refer to [this notebook](https://colab.research.google.com/github/elastic/elasticsearch-labs/blob/main/notebooks/search/09-semantic-text.ipynb) for a step-by-step guide.
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* For more information on how to optimize your ELSER endpoints, refer to [the ELSER recommendations](/explore-analyze/machine-learning/nlp/ml-nlp-elser.md#elser-recommendations) section in the model documentation.
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* To learn more about model autoscaling, refer to the [trained model autoscaling](../../../deploy-manage/autoscaling/trained-model-autoscaling.md) page.
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* To learn more about model autoscaling, refer to the [trained model autoscaling](../../../deploy-manage/autoscaling/trained-model-autoscaling.md) page.

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