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.github/CODEOWNERS

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/deploy-manage/ @elastic/admin-docs
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/explore-analyze/ @elastic/core-docs @elastic/experience-docs
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/extend/ @elastic/core-docs
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/get-started/ @elastic/core-docs
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/get-started/ @elastic/core-docs @elastic/project-docs
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/manage-data/ @elastic/admin-docs
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/manage-data/data-store/ @elastic/admin-docs @elastic/developer-docs
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/release-notes/ @elastic/docs
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/release-notes/apm-agents/ @elastic/ingest-docs
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/release-notes/elastic-cloud-serverless/ @elastic/admin-docs
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/release-notes/elastic-cloud-serverless/ @elastic/admin-docs @elastic/docs-serverless-release-team
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/release-notes/elastic-observability/ @elastic/ski-docs
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/release-notes/elastic-security/ @elastic/ski-docs
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/release-notes/elasticsearch-clients/ @elastic/developer-docs
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/solutions/ @elastic/experience-docs @elastic/developer-docs
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/solutions/observability/ @elastic/experience-docs
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/solutions/observability/get-started/ @elastic/ski-docs
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/solutions/observability/get-started/ @elastic/ski-docs @elastic/project-docs
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/solutions/search/ @elastic/developer-docs
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/solutions/search/get-started/ @elastic/developer-docs @elastic/project-docs
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/solutions/security/ @elastic/experience-docs
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/solutions/security/get-started @elastic/experience-docs @elastic/project-docs
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/troubleshoot/ @elastic/docs
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/troubleshoot/deployments/ @elastic/admin-docs
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name: Update Kube-Stack Version
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on:
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schedule:
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# Run every Monday at 9:00 AM UTC
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- cron: '0 9 * * 1'
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workflow_dispatch: # Allow manual triggering
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jobs:
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update-kube-stack-version:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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with:
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token: ${{ secrets.GITHUB_TOKEN }}
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.9'
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- name: Run kube-stack version update script
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run: |
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cd scripts
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python update_kube_stack_version.py
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- name: Check for changes
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id: verify-changed-files
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run: |
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if [ -n "$(git status --porcelain)" ]; then
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echo "changed=true" >> $GITHUB_OUTPUT
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else
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echo "changed=false" >> $GITHUB_OUTPUT
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fi
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- name: Commit and push changes
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if: steps.verify-changed-files.outputs.changed == 'true'
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run: |
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git config --local user.email "[email protected]"
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git config --local user.name "GitHub Action"
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git add docs/docset.yml
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git commit -m "chore: update kube-stack version [skip ci]"
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git push
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- name: Create Pull Request
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if: steps.verify-changed-files.outputs.changed == 'true'
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uses: peter-evans/create-pull-request@v5
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with:
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token: ${{ secrets.GITHUB_TOKEN }}
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commit-message: "chore: update kube-stack version"
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title: "chore: update kube-stack version"
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body: |
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This PR automatically updates the kube-stack version in `docs/docset.yml` based on the latest version from the elastic-agent repository.
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**Changes:**
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- Updated kube-stack version in docset.yml
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This PR was created automatically by the weekly kube-stack version update workflow.
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branch: update-kube-stack-version
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delete-branch: true
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labels: |
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automated
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documentation

deploy-manage/api-keys.md

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ece: ga
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self: ga
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serverless: ga
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navigation_title: API keys
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---
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# API keys
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# Elastic API keys
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API keys are security mechanisms used to authenticate and authorize access to your deployments and {{es}} resources.
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deploy-manage/cloud-organization/billing/elasticsearch-billing-dimensions.md

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* **Machine learning trained model autoscaling**: [Trained model autoscaling](/deploy-manage/autoscaling/trained-model-autoscaling.md) is always enabled and cannot be disabled, ensuring efficient resource usage, reduced costs, and optimal performance without manual configuration.
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Trained model deployments automatically scale down to zero allocations after 24 hours without any inference requests. When they scale up again, they remain active for 5 minutes before they can scale down. During these cooldown periods, you will continue to be billed for the active resources.
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* **Indexing strategies** Consider your indexing strategies and how they might impact overall VCU usage and costs.
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* **Indexing strategies**: Consider your indexing strategies and how they might impact overall VCU usage and costs.
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To ensure optimal performance and cost-effectiveness for your project, it's important to consider how you structure your data.
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Consolidate small indices for better efficiency.
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Higher resource consumption can lead to higher costs and potentially impact the overall performance of your project.
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If your use case naturally generates many small, separate streams of data, the recommended approach is to implement a process to consolidate them into fewer, larger indices. This practice leads to more efficient resource utilization. By grouping your data into larger indices, you can ensure a more performant and cost-efficient experience with {{es-serverless}}.
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* **Project subtype or profile**: When you use the [API]({{cloud-serverless-apis}}operation/operation-createelasticsearchproject) to create projects, be aware that the `optimized_for` option affects the VCU allocation and costs.
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The `general_purpose` option is suitable for most search use cases. For example, it is the right profile for full-text search, sparse vectors, and dense vectors that use compression such as BBQ. It is used by default when you create projects from the UI.
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The `vector` option is recommended only for uncompressed dense vectors ([dense_vector](elasticsearch://reference/elasticsearch/mapping-reference/dense-vector.md) fields with `int4` or `int8` quantization strategies) and high dimensionality. Though the per VCU cost is the same for general purpose and vector profiles, the latter allocates more VCUs for searchable data. This leads to higher VCU consumption in order to improve the performance for uncompressed vector data.
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There are two options to create serverless projects:
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* If you are a new user, [sign up for a free 14-day trial](https://cloud.elastic.co/serverless-registration) to create a serverless project. For more information about the {{ecloud}} trials, check [Trial features](/deploy-manage/deploy/elastic-cloud/create-an-organization.md#general-sign-up-trial-what-is-included-in-my-trial).
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* If you are an existing customer, [log in to {{ecloud}}](https://cloud.elastic.co/login). On the home page, you will see a new option to create serverless projects. The `admin` predefined role or an equivalent custom role is required to create projects. Refer to [](/deploy-manage/users-roles/cloud-organization/user-roles.md).

deploy-manage/deploy/cloud-enterprise.md

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The section covers the following tasks:
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* [Deploy ECE orchestrator](./cloud-enterprise/deploy-an-orchestrator.md)
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* [Deploy an ECE orchestrator](./cloud-enterprise/deploy-an-orchestrator.md)
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- [Prepare the environment](./cloud-enterprise/prepare-environment.md)
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- [Install ECE](./cloud-enterprise/install.md)
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- [Air gapped installations](./cloud-enterprise/air-gapped-install.md)

deploy-manage/deploy/cloud-enterprise/access-kibana.md

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---
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navigation_title: Access {{kib}}
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# Access {{kib}} [ece-access-kibana]
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# Access {{kib}} on {{ece}} [ece-access-kibana]
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{{kib}} is an open source analytics and visualization platform designed to search, view, and interact with data stored in {{es}} indices.
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deploy-manage/deploy/cloud-enterprise/add-plugins.md

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---
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navigation_title: Configure plugins and extensions
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navigation_title: Add plugins and extensions
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# Add plugins and extensions [ece-adding-plugins]
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# Add plugins and extensions in {{ece}} [ece-adding-plugins]
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Plugins extend the core functionality of {{es}}. {{ece}} makes it easy to add plugins to your deployment by providing a number of plugins that work with your version of {{es}}. One advantage of these plugins is that you generally don’t have to worry about upgrading plugins when upgrading to a new {{es}} version, unless there are breaking changes. The plugins are upgraded along with the rest of your deployment.
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deploy-manage/deploy/cloud-enterprise/deploy-an-orchestrator.md

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applies_to:
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navigation_title: Deploy an orchestrator
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# Deploy an orchestrator
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# Deploy an {{ece}} orchestrator
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{{ece}} (ECE) provides a centralized platform that allows organizations to run {{es}}, {{kib}}, and other {{stack}} components across multiple machines, whether in a private or public cloud, virtual machines, or your own premises.
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deploy-manage/deploy/cloud-enterprise/ece-configure-templates-index-management.md

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If you create a deployment template that includes more than one data configuration, you must also specify how {{ece}} should manage indices for your users when they create their deployments. For time-series use cases such as logging, metrics, and APM, providing a template that enables index management ensures that data is being stored in the most cost-effective way possible as it ages.
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In a template that creates a hot-warm architecture, you can use index curation to specify where new indices are created initially and where they are moved to later on. However, index curation has been deprecated in favor of index lifecycle management, which offers additional features and more fine-grained control over indices. For instance, using ILM you can enable automatic roll-over of index aliases to new indices when existing indices become too large or too old, and you can set indices to be deleted when they are no longer useful.
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Configuring index management is part of the larger task of [creating deployment templates](ece-configuring-ece-create-templates.md) or editing them. The choices you make here determine which index management methods are available to your users when they create deployments.
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You should configure all index management methods that you want your users to be able to choose from when they create their deployments from your template. You can configure index curation, index lifecycle management, or both.
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## Before you begin [ece_before_you_begin_4]
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Configuring index management is part of the larger task of [creating deployment templates](ece-configuring-ece-create-templates.md) or editing them. The choices you make here determine which index management methods are available to your users when they create deployments.
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## Available index management strategies
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You should configure all index management methods that you want your users to be able to choose from when they create their deployments from your template. You can configure index curation, index lifecycle management, or both.
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Index lifecycle management
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: Uses the [{{ilm}}](/manage-data/lifecycle/index-lifecycle-management.md) feature of the {{stack}} that provides an integrated and streamlined way to manage time-based data, making it easier to follow best practices for managing your indices. Compared to index curation, ILM gives you more fine-grained control over the lifecycle of each index.
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::::{note}
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Index curation has been deprecated in favor of [index lifecycle management](/manage-data/lifecycle/index-lifecycle-management.md). For {{stack}} version 6.7 and later, any deployments using index curation will be prompted to [migrate to ILM](/manage-data/lifecycle/index-lifecycle-management/migrate-index-management.md).
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::::
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Index curation (Curator) {applies_to}`stack: deprecated 6.7`
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: Creates new indices on hot nodes first and moves them to warm nodes later on, based on the data views (formerly *index patterns*) you specify. Also manages replica counts for you, so that all shards of an index can fit on the right data nodes. Compared to index lifecycle management, index curation for time-based indices supports only one action, to move indices from nodes on one data configuration to another, but it is more straightforward to set up initially and all setup can be done directly from the Cloud UI.
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If your users need to delete indices once they are no longer useful to them, they can run [Curator](curator://reference/index.md) on-premise to manage indices for {{es}} clusters hosted on {{ece}}.
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## Steps [ece_steps_2]
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::::{note}
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Index curation has been deprecated in favor of [index lifecycle management](/manage-data/lifecycle/index-lifecycle-management.md). For {{stack}} version 6.7 and later, any deployments using index curation will be prompted to [migrate to ILM](/manage-data/lifecycle/index-lifecycle-management/migrate-index-management.md).
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To configure index management when you create a deployment template:
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## Configure {{ilm}}
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Index lifecycle management
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: Uses the ILM feature of the {{stack}} that provides an integrated and streamlined way to manage time-based data, making it easier to follow best practices for managing your indices. Compared to index curation, ILM gives you more fine-grained control over the lifecycle of each index.
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To configure {{ilm}} as part of your deployment template:
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On the **Index Management** page, under **{{ilm}} ({{ilm-init}})**, specify the node attributes for your data configurations.
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1. Specify the node attributes for your data configurations.
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Node attributes are simple key-value pairs, such as `node_type: hot`, `node_type: warm`, and `node_type: cold`. These node attributes add defining metadata attributes to each data configuration in your template that tell your users what they can be used for. What you define here should help guide your users when they set up their index lifecycle management policy in {{kib}}, such as a hot-warm policy.
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Node attributes are simple key-value pairs, such as `node_type: hot`, `node_type: warm`, and `node_type: cold`. These node attributes add defining metadata attributes to each data configuration in your template that tell your users what they can be used for. What you define here should help guide your users when they set up their index lifecycle management policy in {{kib}}, such as a hot-warm policy.
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For each data tier, specify an attribute key-value pair in the **Node attributes** field, with the key and value separated by a colon. Repeat this process until you have added all the node attributes that you want to be available to your users when they create an index lifecycle policy later on.
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1. Specify an attribute key-value pair in the **Node attributes** field, with the key and value separated by a colon.
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2. Repeat the previous step until you have added all the node attributes that you want to be available to your users when they create an index lifecycle policy later on.
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## Configure index curation
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```{applies_to}
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stack: deprecated 6.7
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```
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::::{note}
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Index curation has been deprecated in favor of [index lifecycle management](/manage-data/lifecycle/index-lifecycle-management.md). For {{stack}} version 6.7 and later, any deployments using index curation will be prompted to [migrate to ILM](/manage-data/lifecycle/index-lifecycle-management/migrate-index-management.md).
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Index curation
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: Creates new indices on hot nodes first and moves them to warm nodes later on, based on the data views (formerly *index patterns*) you specify. Also manages replica counts for you, so that all shards of an index can fit on the right data nodes. Compared to index lifecycle management, index curation for time-based indices supports only one action, to move indices from nodes on one data configuration to another, but it is more straightforward to set up initially and all setup can be done directly from the Cloud UI.
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To configure index curation as part of your deployment template:
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If your user need to delete indices once they are no longer useful to them, they can run [Curator](curator://reference/index.md) on-premise to manage indices for {{es}} clusters hosted on {{ece}}.
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1. On the **Index Management** page, under **Index curation**, click **Configure**.
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To configure index curation:
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2. Configure index curation by adding an index pattern:
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1. Select the hot data configuration where new indices get created initially.
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2. Select the warm nodes where older indices get moved to later on when they get curated.
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3. Specify which indices get curated by including at least one data view.
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1. Select the hot data configuration where new indices get created initially.
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2. Select the warm nodes where older indices get moved to later on when they get curated.
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3. Specify which indices get curated by including at least one index pattern.
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By default, the pattern is `*`, which means that all indices get curated. For logging use cases, you could specify to curate only the `logstash-*`, `metricbeat-*`, or `filebeat-*` data views, for example.
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By default, the pattern is `*`, which means that all indices get curated. For logging use cases, you could specify to curate only the `logstash-*`, `metricbeat-*`, or `filebeat-*` data views, for example.
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4. Specify the time interval after which indices get curated.
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4. Specify the time interval after which indices get curated.
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2. Select **Next**.
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## Next steps
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After you have completed these steps, continue with [creating your deployment template](ece-configuring-ece-create-templates.md#ece-configuring-ece-create-templates-ui).
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