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:::{dropdown} Can I use Cloud Connect to connect my {{ech}} clusters to AutoOps?
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This path is not supported. Currently, we only support using Cloud Connect to connect ECE, ECK, and self-managed clusters to AutoOps.
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For {{ech}} clusters, AutoOps is set up and enabled automatically in all supported [regions](/deploy-manage/monitor/autoops/ec-autoops-regions.md), and can be [accessed](/deploy-manage/monitor/autoops/ec-autoops-how-to-access.md) from the deployment overview page.
Copy file name to clipboardExpand all lines: deploy-manage/cloud-organization/billing/elasticsearch-billing-dimensions.md
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@@ -30,6 +30,7 @@ For detailed {{es-serverless}} project rates, see the [{{es-serverless}} pricing
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***Indexing:** The VCUs used to index incoming documents.
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***Search:** The VCUs used to return search results, with the latency and queries per second (QPS) you require.
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***Machine learning:** The VCUs used to perform inference, NLP tasks, and other ML activities.
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***Tokens:** The Elastic Managed LLM is charged per 1Mn Input and Output tokens. The LLM powers all AI Search features such as Playground and AI Assistant for Search, and is enabled by default.
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## Data storage and billing [elasticsearch-billing-information-about-the-search-ai-lake-dimension-gb]
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***Search Power setting:**[Search Power](../../deploy/elastic-cloud/project-settings.md#elasticsearch-manage-project-search-power-settings) controls the speed of searches against your data. With Search Power, you can improve search performance by adding more resources for querying, or you can reduce provisioned resources to cut costs.
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***Search boost window**: By limiting the number of days of [time series data](../../../solutions/search/ingest-for-search.md#elasticsearch-ingest-time-series-data) that are available for caching, you can reduce the number of search VCUs required.
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***Machine learning trained model autoscaling:** Configure your trained model deployment to allow it to scale down to zero allocations when there are no active inference requests:
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* When starting or updating a trained model deployment, [Enable adaptive resources](../../autoscaling/trained-model-autoscaling.md#enabling-autoscaling-in-kibana-adaptive-resources) and set the VCU usage level to **Low**.
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* When using the inference API for {{es}} or ELSER, [enable `adaptive_allocations`](../../autoscaling/trained-model-autoscaling.md#enabling-autoscaling-through-apis-adaptive-allocations).
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***Indexing Strategies:** Consider your indexing strategies and how they might impact overall VCU usage and costs:
You can download and install a specific version of the {{stack}} by replacing `<SPECIFIC.VERSION.NUMBER>` with the version number you want. For example, you can replace `<SPECIFIC.VERSION.NUMBER>` with {{version.stack.base}}.
Copy file name to clipboardExpand all lines: deploy-manage/deploy/self-managed/air-gapped-install.md
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@@ -87,10 +87,13 @@ Besides setting up the EPR service, you also need to [configure {{kib}}](/deploy
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### Additional {{package-registry}} examples
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:::{dropdown} Script to generate a SystemD service file on a RHEL 8 system
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:::::{dropdown} Script to generate a SystemD service file on a RHEL 8 system
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The following script generates a SystemD service file on a RHEL 8 system in order to run EPR with Podman in a production environment.
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::::{tab-set}
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:::{tab-item} Latest
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```sh subs=true
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#!/usr/bin/env bash
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```
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:::
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:::{dropdown} SystemD service file launched as a Podman service
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:::{tab-item} Specific version
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Replace `<SPECIFIC.VERSION.NUMBER>` with the {{stack}} version number you want. For example, you can replace `<SPECIFIC.VERSION.NUMBER>` with {{version.stack.base}}.
:::::{dropdown} SystemD service file launched as a Podman service
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The following is an example of an actual SystemD service file for an EPR, launched as a Podman service.
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::::{tab-set}
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```ini subs=true
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# container-elastic-epr.service
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# autogenerated by Podman 4.1.1
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```
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:::
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::::::{tab-item} Specific version
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Replace `<SPECIFIC.VERSION.NUMBER>` with the {{stack}} version number you want. For example, you can replace `<SPECIFIC.VERSION.NUMBER>` with {{version.stack.base}}.
Air-gapped install of the {{artifact-registry}} is necessary in order to enable {{agent}} deployments to perform self-upgrades and install certain components which are needed for some of the data integrations (that is, in addition to what is also retrieved from the EPR). To learn more, refer to [Host your own artifact registry for binary downloads](/reference/fleet/air-gapped.md#host-artifact-registry) in the {{fleet}} and {{elastic-agent}} Guide.
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### Additional {{artifact-registry}} examples
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:::{dropdown} Artifact download script
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:::::{dropdown} Artifact download script
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The following example script downloads artifacts from the internet to be later served as a private Elastic Package Registry.
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::::{tab-set}
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```sh subs=true
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#!/usr/bin/env bash
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set -o nounset -o errexit -o pipefail
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```
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:::
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::::::{tab-item} Specific version
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Replace `<SPECIFIC.VERSION.NUMBER>` with the {{stack}} version number you want. For example, you can replace `<SPECIFIC.VERSION.NUMBER>` with {{version.stack.base}}.
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