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Copy file name to clipboardExpand all lines: deploy-manage/cloud-organization/tools-and-apis.md
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@@ -18,7 +18,7 @@ Most Elastic resources can be accessed and managed through RESTful APIs. While t
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Elasticsearch APIs
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: This set of APIs allows you to interact directly with the Elasticsearch nodes in your deployment. You can ingest data, run search queries, check the health of your clusters, manage snapshots, and more.
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To use these APIs on {{ecloud}} read our topic [Access the API console](asciidocalypse://docs/cloud/docs/reference/cloud-hosted/ec-api-console.md), and to learn about all of the available endpoints check the [Elasticsearch API reference documentation](asciidocalypse://docs/elasticsearch/docs/reference/elasticsearch/rest-apis/index.md).
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To use these APIs on {{ecloud}} read our topic [Access the API console](asciidocalypse://docs/cloud/docs/reference/cloud-hosted/ec-api-console.md), and to learn about all of the available endpoints check the [Elasticsearch API reference documentation](elasticsearch://reference/elasticsearch/rest-apis/index.md).
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Some [restrictions](../deploy/elastic-cloud/restrictions-known-problems.md#ec-restrictions-apis-elasticsearch) apply when using the Elasticsearch APIs on {{ecloud}}.
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}
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```
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4. To use this bundle, you can refer it in the [GeoIP processor](asciidocalypse://docs/elasticsearch/docs/reference/ingestion-tools/enrich-processor/geoip-processor.md) of an ingest pipeline as `MyGeoLite2-City.mmdb` under `database_file` such as:
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4. To use this bundle, you can refer it in the [GeoIP processor](elasticsearch://reference/ingestion-tools/enrich-processor/geoip-processor.md) of an ingest pipeline as `MyGeoLite2-City.mmdb` under `database_file` such as:
Copy file name to clipboardExpand all lines: deploy-manage/deploy/cloud-enterprise/ce-add-support-for-node-roles-autoscaling.md
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@@ -17,7 +17,7 @@ The `node_roles` field defines the roles that an Elasticsearch topology element
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There are a number of fields that need to be added to each Elasticsearch node in order to support `node_roles`:
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***id**: Unique identifier of the topology element. This field, along with the `node_roles`, identifies an Elasticsearch topology element.
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***node_roles**: The list of node roles. Allowable roles are: `master`, `ingest`, `ml`, `data_hot`, `data_content`, `data_warm`, `data_cold`, `data_frozen`, `remote_cluster_client`, and `transform`. For details, check [Node roles](asciidocalypse://docs/elasticsearch/docs/reference/elasticsearch/configuration-reference/node-settings.md#node-roles).
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***node_roles**: The list of node roles. Allowable roles are: `master`, `ingest`, `ml`, `data_hot`, `data_content`, `data_warm`, `data_cold`, `data_frozen`, `remote_cluster_client`, and `transform`. For details, check [Node roles](elasticsearch://reference/elasticsearch/configuration-reference/node-settings.md#node-roles).
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***topology_element_control**: Controls for the topology element.
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***min**: The absolute minimum size limit for a topology element. If the value is `0`, that means the topology element can be disabled.
Copy file name to clipboardExpand all lines: deploy-manage/deploy/cloud-enterprise/ece-ha.md
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## Master nodes [ece-ece-ha-2-master-nodes]
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$$$ece-ha-tiebreaker$$$Tiebreakers are used in distributed clusters to avoid cases of [split brain](https://en.wikipedia.org/wiki/Split-brain_(computing)), where an {{es}} cluster splits into multiple, autonomous parts that continue to handle requests independently of each other, at the risk of affecting cluster consistency and data loss. A split-brain scenario is avoided by making sure that a minimum number of [master-eligible nodes](asciidocalypse://docs/elasticsearch/docs/reference/elasticsearch/configuration-reference/node-settings.md#master-node) must be present in order for any part of the cluster to elect a master node and accept user requests. To prevent multiple parts of a cluster from being eligible, there must be a [quorum-based majority](/deploy-manage/distributed-architecture/discovery-cluster-formation/modules-discovery-quorums.md) of `(n/2)+1` nodes, where `n` is the number of master-eligible nodes in the cluster. The minimum number of master nodes to reach quorum in a two-node cluster is the same as for a three-node cluster: two nodes must be available.
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$$$ece-ha-tiebreaker$$$Tiebreakers are used in distributed clusters to avoid cases of [split brain](https://en.wikipedia.org/wiki/Split-brain_(computing)), where an {{es}} cluster splits into multiple, autonomous parts that continue to handle requests independently of each other, at the risk of affecting cluster consistency and data loss. A split-brain scenario is avoided by making sure that a minimum number of [master-eligible nodes](elasticsearch://reference/elasticsearch/configuration-reference/node-settings.md#master-node) must be present in order for any part of the cluster to elect a master node and accept user requests. To prevent multiple parts of a cluster from being eligible, there must be a [quorum-based majority](/deploy-manage/distributed-architecture/discovery-cluster-formation/modules-discovery-quorums.md) of `(n/2)+1` nodes, where `n` is the number of master-eligible nodes in the cluster. The minimum number of master nodes to reach quorum in a two-node cluster is the same as for a three-node cluster: two nodes must be available.
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When you create a cluster with nodes in two availability zones when a third zone is available, Elastic Cloud Enterprise can create a tiebreaker in the third availability zone to help establish quorum in case of loss of an availability zone. The extra tiebreaker node that helps to provide quorum does not have to be a full-fledged and expensive node, as it does not hold data. For example: By tagging allocators hosts in Elastic Cloud Enterprise, can you create a cluster with eight nodes each in zones `ece-1a` and `ece-1b`, for a total of 16 nodes, and one tiebreaker node in zone `ece-1c`. This cluster can lose any of the three availability zones whilst maintaining quorum, which means that the cluster can continue to process user requests, provided that there is sufficient capacity available when an availability zone goes down.
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By default, each node in an {{es}} cluster is a master-eligible node and a data node. In larger clusters, such as production clusters, it’s a good practice to split the roles, so that master nodes are not handling search or indexing work. When you create a cluster, you can specify to use dedicated [master-eligible nodes](asciidocalypse://docs/elasticsearch/docs/reference/elasticsearch/configuration-reference/node-settings.md#master-node), one per availability zone.
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By default, each node in an {{es}} cluster is a master-eligible node and a data node. In larger clusters, such as production clusters, it’s a good practice to split the roles, so that master nodes are not handling search or indexing work. When you create a cluster, you can specify to use dedicated [master-eligible nodes](elasticsearch://reference/elasticsearch/configuration-reference/node-settings.md#master-node), one per availability zone.
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::::{warning}
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Clusters that only have two or fewer master-eligible node are not [highly available](/deploy-manage/production-guidance/availability-and-resilience.md) and are at risk of data loss. You must have [at least three master-eligible nodes](/deploy-manage/distributed-architecture/discovery-cluster-formation/modules-discovery-quorums.md).
Copy file name to clipboardExpand all lines: deploy-manage/deploy/cloud-enterprise/ece-manage-capacity.md
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*[Storage](#ece-alloc-storage)
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## Memory [ece-alloc-memory]
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## Memory [ece-alloc-memory]
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You should plan your deployment size based on the amount of data you ingest. Memory is the main scaling unit for a deployment. Other units, like CPU and disks, are proportional to the memory size. The memory available for an allocator is called *capacity*.
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During installation, the allocator capacity defaults to 85% of the host physical memory, as the rest is reserved for ECE system services.
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::::{note}
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ECE does not support hot-adding of resources to a running node. When increasing CPU/memory allocated to a ECE node, a restart is needed to utilize the additional resources.
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For more information on how to use API keys for authentication, check the section [Access the API from the Command Line](asciidocalypse://docs/cloud/docs/reference/cloud-enterprise/ece-api-command-line.md).
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Prior to ECE 3.5.0, regardless of the use of this API, the [CPU quota](#ece-alloc-cpu) used the memory specified at installation time.
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### Examples [ece_examples]
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### Examples [ece_examples]
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Here are some examples to make Elastic deployments and ECE system services run smoothly on your host:
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These fluctuations should not be a concern in practice. To get actual limits that could be used in alerts, you could add 4GB to the recommended values above.
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## CPU quotas [ece-alloc-cpu]
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## CPU quotas [ece-alloc-cpu]
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ECE uses CPU quotas to assign shares of the allocator host to the instances that are running on it. To calculate the CPU quota, use the following formula:
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`CPU quota = DeploymentRAM / HostCapacity`
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### Examples [ece_examples_2]
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### Examples [ece_examples_2]
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Consider a 32GB deployment hosted on a 128GB allocator.
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Those percentages represent the upper limit of the % of the total CPU resources available in a given 100ms period.
In addition to the [CPU quotas](#ece-alloc-cpu), the `processors` setting also plays a relevant role.
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The allocated `processors` setting originates from Elasticsearch and is responsible for calculating your [thread pools](asciidocalypse://docs/elasticsearch/docs/reference/elasticsearch/configuration-reference/thread-pool-settings.md#node.processors). While the CPU quota defines the percentage of the total CPU resources of an allocator that are assigned to an instance, the allocated `processors` define how the thread pools are calculated in Elasticsearch, and therefore how many concurrent search and indexing requests an instance can process. In other words, the CPU ratio defines how fast a single task can be completed, while the `processors` setting defines how many different tasks can be completed at the same time.
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The allocated `processors` setting originates from Elasticsearch and is responsible for calculating your [thread pools](elasticsearch://reference/elasticsearch/configuration-reference/thread-pool-settings.md#node.processors). While the CPU quota defines the percentage of the total CPU resources of an allocator that are assigned to an instance, the allocated `processors` define how the thread pools are calculated in Elasticsearch, and therefore how many concurrent search and indexing requests an instance can process. In other words, the CPU ratio defines how fast a single task can be completed, while the `processors` setting defines how many different tasks can be completed at the same time.
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We rely on Elasticsearch and the `-XX:ActiveProcessorCount` JVM setting to automatically detect the allocated `processors`.
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In earlier versions of ECE and Elasticsearch, the [Elasticsearch processors](asciidocalypse://docs/elasticsearch/docs/reference/elasticsearch/configuration-reference/thread-pool-settings.md#node.processors) setting was used to configure the allocated `processors` according to the following formula:
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In earlier versions of ECE and Elasticsearch, the [Elasticsearch processors](elasticsearch://reference/elasticsearch/configuration-reference/thread-pool-settings.md#node.processors) setting was used to configure the allocated `processors` according to the following formula:
The following table gives an overview of the allocated `processors` that are used to calculate the Elasticsearch [thread pools](asciidocalypse://docs/elasticsearch/docs/reference/elasticsearch/configuration-reference/thread-pool-settings.md) based on the preceding formula:
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The following table gives an overview of the allocated `processors` that are used to calculate the Elasticsearch [thread pools](elasticsearch://reference/elasticsearch/configuration-reference/thread-pool-settings.md) based on the preceding formula:
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| instance size | vCPU |
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| --- | --- |
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This table also provides a rough indication of what the auto-detected value could be on newer versions of ECE and Elasticsearch.
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## Storage [ece-alloc-storage]
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## Storage [ece-alloc-storage]
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ECE has specific [hardware prerequisites](ece-hardware-prereq.md) for storage. Disk space is consumed by system logs, container overhead, and deployment data.
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The main factor for selecting a disk quota is the deployment data, that is, data from your Elasticsearch, Kibana, and APM nodes. The biggest portion of data is consumed by the Elasticsearch nodes.
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ECE uses [XFS](ece-software-prereq.md#ece-xfs) to enforce specific disk space quotas to control the disk consumption for the deployment nodes running on your allocator.
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You must use XFS and have quotas enabled on all allocators, otherwise disk usage won’t display correctly.
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3. Adjust the disk quota to your needs.
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The override only persists during the lifecycle of the instance container. If a new container is created, for example during a `grow_and_shrink` plan or a vacate operation, the quota is reset to its default. To increase the storage ratio in a persistent way, [edit the instance configurations](ece-configuring-ece-instance-configurations-edit.md).
Copy file name to clipboardExpand all lines: deploy-manage/deploy/cloud-enterprise/post-installation-steps.md
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After your Elastic Cloud Enterprise installation is up, some additional steps might be required:
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* Add your own load balancer. Load balancers are user supplied and we do not currently provide configuration steps for you.
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*[Add more capacity](../../maintenance/ece/scale-out-installation.md) to your Elastic Cloud Enterprise installation, [resize your deployment](resize-deployment.md), [upgrade to a newer Elasticsearch version](../../upgrade/deployment-or-cluster.md), and [add some plugins](asciidocalypse://docs/elasticsearch/docs/reference/elasticsearch-plugins/cloud-enterprise/ece-add-plugins.md).
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*[Add more capacity](../../maintenance/ece/scale-out-installation.md) to your Elastic Cloud Enterprise installation, [resize your deployment](resize-deployment.md), [upgrade to a newer Elasticsearch version](../../upgrade/deployment-or-cluster.md), and [add some plugins](elasticsearch://reference/elasticsearch-plugins/cloud-enterprise/ece-add-plugins.md).
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*[Configure ECE system deployments](system-deployments-configuration.md) to ensure a highly available and resilient setup.
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*[Configure ECE for deployment templates](configure-deployment-templates.md) to indicate what kind of hardware you have available for Elastic Stack deployments.
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*[Install your security certificates](../../security/secure-your-elastic-cloud-enterprise-installation/manage-security-certificates.md) to enable TLS/SSL authentication for secure connections over HTTPS.
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* Learn how to work around host maintenance or a host failure by [moving nodes off of an allocator](../../maintenance/ece/move-nodes-instances-from-allocators.md).
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* If you received a license from Elastic, [manage the licenses](../../license/manage-your-license-in-ece.md) for your Elastic Cloud Enterprise installation.
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::::{warning}
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::::{warning}
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During installation, the system generates secrets that are placed into the `/mnt/data/elastic/bootstrap-state/bootstrap-secrets.json` secrets file, unless you passed in a different path with the --host-storage-path parameter. Keep the information in the `bootstrap-secrets.json` file secure by removing it from its default location and placing it into a secure storage location.
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