b14224c030
It is currently the case that the discovery information for elasticsearch nodes is generated using the elasticsearch node and kibana node groups internally. This means that one cannot connect to a remote cluster that is not managed by the same ansible inventory. This commit exposes the configuration to allow this to occur, permitting the elasticsearch discovery nodes to be optionally defined with further information. The associated internal variables have been renamed from zen_nodes as zen is used within Elasticsearch for discovery only internally, and the associated elasticsearch config file setting has been renamed to 'discovery.seed_hosts'. Change-Id: I76532c185e991eddcb1111fc58e7120a52c0120c
167 lines
6.2 KiB
Django/Jinja
167 lines
6.2 KiB
Django/Jinja
# ======================== Elasticsearch Configuration =========================
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#
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# NOTE: Elasticsearch comes with reasonable defaults for most settings.
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# Before you set out to tweak and tune the configuration, make sure you
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# understand what are you trying to accomplish and the consequences.
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#
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# The primary way of configuring a node is via this file. This template lists
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# the most important settings you may want to configure for a production cluster.
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#
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# Please consult the documentation for further information on configuration options:
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# https://www.elastic.co/guide/en/elasticsearch/reference/index.html
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#
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# ---------------------------------- Cluster -----------------------------------
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#
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# Use a descriptive name for your cluster:
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#
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cluster.name: {{ cluster_name }}
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#
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# ------------------------------------ Node ------------------------------------
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#
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# Use a descriptive name for the node:
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#
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# ansible_nodename may be appropriate for your instance
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# If you're having issues with bootstrap skipping, check this.
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node.name: {{ inventory_hostname }}
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#
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# Add custom attributes to the node:
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# Set to true to enable machine learning on the node.
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node.ml: false
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#
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# ----------------------------------- Paths ------------------------------------
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#
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# Path to directory where to store the data (separate multiple locations by comma):
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#
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path.data: {{ elastic_data_path }}
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#
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# Path to log files:
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#
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path.logs: /var/log/elasticsearch/
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#
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# Path to shared filesystem repos
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#
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{% if elastic_shared_fs_repos is defined and elastic_shared_fs_repos|length > 0 %}
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path.repo: {{ elastic_shared_fs_repos | json_query("[*].path") | to_json }}
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{% endif %}
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#
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# Set the global default index store. More information on these settings can be
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# found here:
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# <https://www.elastic.co/guide/en/elasticsearch/reference/current/index-modules-store.html>
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#
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index.store.type: niofs
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#
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# ----------------------------------- Memory -----------------------------------
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#
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# Lock the memory on startup:
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#
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bootstrap.memory_lock: {{ elastic_memory_lock }}
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#
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# Make sure that the heap size is set to about half the memory available
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# on the system and that the owner of the process is allowed to use this
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# limit.
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#
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# Elasticsearch performs poorly when the system is swapping the memory.
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#
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# ---------------------------------- Network -----------------------------------
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#
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# Set the bind address to a specific IP (IPv4 or IPv6):
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#
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network.host: {{ elasticsearch_bind_addresses | list | to_json }}
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{% if elasticsearch_publish_host is defined %}
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network.publish_host: "{{ elasticsearch_publish_host }}"
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{% endif %}
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#
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# Set a custom port for HTTP:
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#
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http.port: {{ elastic_port }}
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#
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# For more information, consult the network module documentation.
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#
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# --------------------------------- Discovery ----------------------------------
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#
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# Pass an initial list of hosts to perform discovery when this node is started:
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# The default list of hosts is ["127.0.0.1", "[::1]"]
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#
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discovery.seed_hosts: {{ _elasticsearch_discovery_seed_hosts | shuffle(seed=inventory_hostname) | to_json }}
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#
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# Bootstrap the cluster using an initial set of master-eligible nodes:
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#
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cluster.initial_master_nodes: {{ master_nodes | to_json }}
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#
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# For more information, consult the discovery and cluster formation module documentation.
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#
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# The first set of nodes in the master_node_count are marked as such
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#
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node.master: {{ elasticsearch_node_master | default(master_node) }}
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# Every node in the master list and every other node after will be a data node
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#
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node.data: {{ elasticsearch_node_data | default(data_node) }}
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#
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# Ingest nodes can execute pre-processing pipelines. To override automatic
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# determination, the option `elasticsearch_node_ingest` can be defined as a
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# Boolean which will enable or disable ingest nodes. When using automatic
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# determination, ingest nodes will follow data nodes.
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#
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# NOTE(cloudnull): The use of "search remote connect" will follow the enablement
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# of an ingest nodes.
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#
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{% if elasticsearch_node_ingest is defined %}
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node.ingest: {{ elasticsearch_node_ingest }}
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cluster.remote.connect: {{ elasticsearch_node_ingest }}
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{% else %}
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node.ingest: {{ data_node }}
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cluster.remote.connect: {{ data_node }}
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{% endif %}
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#
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# ---------------------------------- Gateway -----------------------------------
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#
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# Block initial recovery after a full cluster restart until N nodes are started:
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#
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gateway.recover_after_nodes: {{ elasticsearch_master_node_count | default(((master_node_count | int) // 2) + 1) }}
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#
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# For more information, consult the gateway module documentation.
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#
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# ---------------------------------- Various -----------------------------------
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#
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# Require explicit names when deleting indices:
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#
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action.destructive_requires_name: true
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{% set processors = ((elastic_thread_pool_size | int) > 0) | ternary(elastic_thread_pool_size, 1) %}
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{% if not (elastic_coordination_node | default(false)) | bool %}
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# Thread pool settings. For more on this see the documentation at:
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# <https://www.elastic.co/guide/en/elasticsearch/reference/current/modules-threadpool.html>
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thread_pool:
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get:
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queue_size: {{ (processors | int) * 256 }}
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write:
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queue_size: {{ (processors | int) * 512 }}
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{% else %}
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# The number of processors is automatically detected, and the thread pool
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# settings are automatically set based on it. In some cases it can be useful to
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# override the number of detected processors. This can be done by explicitly
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# setting the processors setting. On Kibana hosts where elasticsearch is running
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# as a coordination node, the processor count is limited.
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processors: {{ processors }}
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{% endif %}
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# Accepts either a percentage or a byte size value. Set to 20%, meaning that 20%
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# of the total heap allocated to a node will be used as the indexing buffer size
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# shared across all shards.
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indices.memory.index_buffer_size: 20%
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# Connection throttling on recovery is limited to 20% of the detected interface
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# speed with a cap of 750mb. This will improce search speeds and reduce general
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# cluster pressure.
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indices.recovery.max_bytes_per_sec: {{ elasticserch_interface_speed }}mb
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# ---------------------------------- X-Pack ------------------------------------
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# X-Pack Monitoring
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#
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xpack.monitoring.collection.enabled: true
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xpack.monitoring.collection.interval: 30s
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# Set to true to enable machine learning on the node.
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xpack.ml.enabled: false
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