- Elasticsearch Guide: other versions:
- What’s new in 8.17
- Elasticsearch basics
- Quick starts
- Set up Elasticsearch
- Run Elasticsearch locally
- Installing Elasticsearch
- Configuring Elasticsearch
- Important Elasticsearch configuration
- Secure settings
- Auditing settings
- Circuit breaker settings
- Cluster-level shard allocation and routing settings
- Miscellaneous cluster settings
- Cross-cluster replication settings
- Discovery and cluster formation settings
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- Bootstrap Checks
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- Token count
- Unsigned long
- Version
- Metadata fields
- Mapping parameters
analyzer
coerce
copy_to
doc_values
dynamic
eager_global_ordinals
enabled
format
ignore_above
index.mapping.ignore_above
ignore_malformed
index
index_options
index_phrases
index_prefixes
meta
fields
normalizer
norms
null_value
position_increment_gap
properties
search_analyzer
similarity
store
subobjects
term_vector
- Mapping limit settings
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- Text analysis
- Overview
- Concepts
- Configure text analysis
- Built-in analyzer reference
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- Apostrophe
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- Processor reference
- Append
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- Terms
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- Subtleties of bucketing range fields
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- Average bucket
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- Extended stats bucket
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- Connectors
- EQL
- ES|QL
- SQL
- Overview
- Getting Started with SQL
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- SQL REST API
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- Comparison Operators
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- Aggregate Functions
- Grouping Functions
- Date/Time and Interval Functions and Operators
- Full-Text Search Functions
- Mathematical Functions
- String Functions
- Type Conversion Functions
- Geo Functions
- Conditional Functions And Expressions
- System Functions
- Reserved keywords
- SQL Limitations
- Scripting
- Data management
- ILM: Manage the index lifecycle
- Tutorial: Customize built-in policies
- Tutorial: Automate rollover
- Index management in Kibana
- Overview
- Concepts
- Index lifecycle actions
- Configure a lifecycle policy
- Migrate index allocation filters to node roles
- Troubleshooting index lifecycle management errors
- Start and stop index lifecycle management
- Manage existing indices
- Skip rollover
- Restore a managed data stream or index
- Data tiers
- Autoscaling
- Monitor a cluster
- Roll up or transform your data
- Set up a cluster for high availability
- Snapshot and restore
- Secure the Elastic Stack
- Elasticsearch security principles
- Start the Elastic Stack with security enabled automatically
- Manually configure security
- Updating node security certificates
- User authentication
- Built-in users
- Service accounts
- Internal users
- Token-based authentication services
- User profiles
- Realms
- Realm chains
- Security domains
- Active Directory user authentication
- File-based user authentication
- LDAP user authentication
- Native user authentication
- OpenID Connect authentication
- PKI user authentication
- SAML authentication
- Kerberos authentication
- JWT authentication
- Integrating with other authentication systems
- Enabling anonymous access
- Looking up users without authentication
- Controlling the user cache
- Configuring SAML single-sign-on on the Elastic Stack
- Configuring single sign-on to the Elastic Stack using OpenID Connect
- User authorization
- Built-in roles
- Defining roles
- Role restriction
- Security privileges
- Document level security
- Field level security
- Granting privileges for data streams and aliases
- Mapping users and groups to roles
- Setting up field and document level security
- Submitting requests on behalf of other users
- Configuring authorization delegation
- Customizing roles and authorization
- Enable audit logging
- Restricting connections with IP filtering
- Securing clients and integrations
- Operator privileges
- Troubleshooting
- Some settings are not returned via the nodes settings API
- Authorization exceptions
- Users command fails due to extra arguments
- Users are frequently locked out of Active Directory
- Certificate verification fails for curl on Mac
- SSLHandshakeException causes connections to fail
- Common SSL/TLS exceptions
- Common Kerberos exceptions
- Common SAML issues
- Internal Server Error in Kibana
- Setup-passwords command fails due to connection failure
- Failures due to relocation of the configuration files
- Limitations
- Watcher
- Cross-cluster replication
- Data store architecture
- REST APIs
- API conventions
- Common options
- REST API compatibility
- Autoscaling APIs
- Behavioral Analytics APIs
- Compact and aligned text (CAT) APIs
- cat aliases
- cat allocation
- cat anomaly detectors
- cat component templates
- cat count
- cat data frame analytics
- cat datafeeds
- cat fielddata
- cat health
- cat indices
- cat master
- cat nodeattrs
- cat nodes
- cat pending tasks
- cat plugins
- cat recovery
- cat repositories
- cat segments
- cat shards
- cat snapshots
- cat task management
- cat templates
- cat thread pool
- cat trained model
- cat transforms
- Cluster APIs
- Cluster allocation explain
- Cluster get settings
- Cluster health
- Health
- Cluster reroute
- Cluster state
- Cluster stats
- Cluster update settings
- Nodes feature usage
- Nodes hot threads
- Nodes info
- Prevalidate node removal
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- Nodes stats
- Cluster Info
- Pending cluster tasks
- Remote cluster info
- Task management
- Voting configuration exclusions
- Create or update desired nodes
- Get desired nodes
- Delete desired nodes
- Get desired balance
- Reset desired balance
- Cross-cluster replication APIs
- Connector APIs
- Create connector
- Delete connector
- Get connector
- List connectors
- Update connector API key id
- Update connector configuration
- Update connector index name
- Update connector features
- Update connector filtering
- Update connector name and description
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- Check in a connector
- Update connector error
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- Update connector status
- Check in connector sync job
- Claim connector sync job
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- Data stream APIs
- Document APIs
- Enrich APIs
- EQL APIs
- ES|QL APIs
- Features APIs
- Fleet APIs
- Graph explore API
- Index APIs
- Alias exists
- Aliases
- Analyze
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- Create index
- Create or update alias
- Create or update component template
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- Create or update index template (legacy)
- Delete component template
- Delete dangling index
- Delete alias
- Delete index
- Delete index template
- Delete index template (legacy)
- Exists
- Field usage stats
- Flush
- Force merge
- Get alias
- Get component template
- Get field mapping
- Get index
- Get index settings
- Get index template
- Get index template (legacy)
- Get mapping
- Import dangling index
- Index recovery
- Index segments
- Index shard stores
- Index stats
- Index template exists (legacy)
- List dangling indices
- Open index
- Refresh
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- Resolve cluster
- Rollover
- Shrink index
- Simulate index
- Simulate template
- Split index
- Unfreeze index
- Update index settings
- Update mapping
- Index lifecycle management APIs
- Create or update lifecycle policy
- Get policy
- Delete policy
- Move to step
- Remove policy
- Retry policy
- Get index lifecycle management status
- Explain lifecycle
- Start index lifecycle management
- Stop index lifecycle management
- Migrate indices, ILM policies, and legacy, composable and component templates to data tiers routing
- Inference APIs
- Delete inference API
- Get inference API
- Perform inference API
- Create inference API
- Stream inference API
- Update inference API
- AlibabaCloud AI Search inference service
- Amazon Bedrock inference service
- Anthropic inference service
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- Elasticsearch inference service
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- Google AI Studio inference service
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- Info API
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- Logstash APIs
- Machine learning APIs
- Machine learning anomaly detection APIs
- Add events to calendar
- Add jobs to calendar
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- Delete forecasts
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- Delete expired data
- Estimate model memory
- Flush jobs
- Forecast jobs
- Get buckets
- Get calendars
- Get categories
- Get datafeeds
- Get datafeed statistics
- Get influencers
- Get jobs
- Get job statistics
- Get model snapshots
- Get model snapshot upgrade statistics
- Get overall buckets
- Get scheduled events
- Get filters
- Get records
- Open jobs
- Post data to jobs
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- Start datafeeds
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- Machine learning data frame analytics APIs
- Create data frame analytics jobs
- Delete data frame analytics jobs
- Evaluate data frame analytics
- Explain data frame analytics
- Get data frame analytics jobs
- Get data frame analytics jobs stats
- Preview data frame analytics
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- Machine learning trained model APIs
- Clear trained model deployment cache
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- Migration APIs
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- Security APIs
- Authenticate
- Change passwords
- Clear cache
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- Delete application privileges
- Delete role mappings
- Delete roles
- Delete service account token
- Delete users
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- Enroll node
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- Get builtin privileges
- Get role mappings
- Get roles
- Query Role
- Get service accounts
- Get service account credentials
- Get Security settings
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- Get user privileges
- Get users
- Grant API keys
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- Invalidate API key
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- Query User
- Update API key
- Update Security settings
- Bulk update API keys
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- Activate user profile
- Disable user profile
- Enable user profile
- Get user profiles
- Suggest user profile
- Update user profile data
- Has privileges user profile
- Create Cross-Cluster API key
- Update Cross-Cluster API key
- Snapshot and restore APIs
- Snapshot lifecycle management APIs
- SQL APIs
- Synonyms APIs
- Text structure APIs
- Transform APIs
- Usage API
- Watcher APIs
- Definitions
- Command line tools
- elasticsearch-certgen
- elasticsearch-certutil
- elasticsearch-create-enrollment-token
- elasticsearch-croneval
- elasticsearch-keystore
- elasticsearch-node
- elasticsearch-reconfigure-node
- elasticsearch-reset-password
- elasticsearch-saml-metadata
- elasticsearch-service-tokens
- elasticsearch-setup-passwords
- elasticsearch-shard
- elasticsearch-syskeygen
- elasticsearch-users
- Optimizations
- Troubleshooting
- Fix common cluster issues
- Diagnose unassigned shards
- Add a missing tier to the system
- Allow Elasticsearch to allocate the data in the system
- Allow Elasticsearch to allocate the index
- Indices mix index allocation filters with data tiers node roles to move through data tiers
- Not enough nodes to allocate all shard replicas
- Total number of shards for an index on a single node exceeded
- Total number of shards per node has been reached
- Troubleshooting corruption
- Fix data nodes out of disk
- Fix master nodes out of disk
- Fix other role nodes out of disk
- Start index lifecycle management
- Start Snapshot Lifecycle Management
- Restore from snapshot
- Troubleshooting broken repositories
- Addressing repeated snapshot policy failures
- Troubleshooting an unstable cluster
- Troubleshooting discovery
- Troubleshooting monitoring
- Troubleshooting transforms
- Troubleshooting Watcher
- Troubleshooting searches
- Troubleshooting shards capacity health issues
- Troubleshooting an unbalanced cluster
- Capture diagnostics
- Migration guide
- Release notes
- Elasticsearch version 8.17.0
- Elasticsearch version 8.16.1
- Elasticsearch version 8.16.0
- Elasticsearch version 8.15.5
- Elasticsearch version 8.15.4
- Elasticsearch version 8.15.3
- Elasticsearch version 8.15.2
- Elasticsearch version 8.15.1
- Elasticsearch version 8.15.0
- Elasticsearch version 8.14.3
- Elasticsearch version 8.14.2
- Elasticsearch version 8.14.1
- Elasticsearch version 8.14.0
- Elasticsearch version 8.13.4
- Elasticsearch version 8.13.3
- Elasticsearch version 8.13.2
- Elasticsearch version 8.13.1
- Elasticsearch version 8.13.0
- Elasticsearch version 8.12.2
- Elasticsearch version 8.12.1
- Elasticsearch version 8.12.0
- Elasticsearch version 8.11.4
- Elasticsearch version 8.11.3
- Elasticsearch version 8.11.2
- Elasticsearch version 8.11.1
- Elasticsearch version 8.11.0
- Elasticsearch version 8.10.4
- Elasticsearch version 8.10.3
- Elasticsearch version 8.10.2
- Elasticsearch version 8.10.1
- Elasticsearch version 8.10.0
- Elasticsearch version 8.9.2
- Elasticsearch version 8.9.1
- Elasticsearch version 8.9.0
- Elasticsearch version 8.8.2
- Elasticsearch version 8.8.1
- Elasticsearch version 8.8.0
- Elasticsearch version 8.7.1
- Elasticsearch version 8.7.0
- Elasticsearch version 8.6.2
- Elasticsearch version 8.6.1
- Elasticsearch version 8.6.0
- Elasticsearch version 8.5.3
- Elasticsearch version 8.5.2
- Elasticsearch version 8.5.1
- Elasticsearch version 8.5.0
- Elasticsearch version 8.4.3
- Elasticsearch version 8.4.2
- Elasticsearch version 8.4.1
- Elasticsearch version 8.4.0
- Elasticsearch version 8.3.3
- Elasticsearch version 8.3.2
- Elasticsearch version 8.3.1
- Elasticsearch version 8.3.0
- Elasticsearch version 8.2.3
- Elasticsearch version 8.2.2
- Elasticsearch version 8.2.1
- Elasticsearch version 8.2.0
- Elasticsearch version 8.1.3
- Elasticsearch version 8.1.2
- Elasticsearch version 8.1.1
- Elasticsearch version 8.1.0
- Elasticsearch version 8.0.1
- Elasticsearch version 8.0.0
- Elasticsearch version 8.0.0-rc2
- Elasticsearch version 8.0.0-rc1
- Elasticsearch version 8.0.0-beta1
- Elasticsearch version 8.0.0-alpha2
- Elasticsearch version 8.0.0-alpha1
- Dependencies and versions
Exporters
editExporters
editElastic Agent and Metricbeat are the recommended methods for collecting and shipping monitoring data to a monitoring cluster.
If you have previously configured legacy collection methods, you should migrate to using Elastic Agent or Metricbeat collection. Do not use legacy collection alongside other collection methods.
The purpose of exporters is to take data collected from any Elastic Stack source and route it to the monitoring cluster. It is possible to configure more than one exporter, but the general and default setup is to use a single exporter.
There are two types of exporters in Elasticsearch:
-
local
- The default exporter used by Elasticsearch monitoring features. This exporter routes data back into the same cluster. See Local exporters.
-
http
- The preferred exporter, which you can use to route data into any supported Elasticsearch cluster accessible via HTTP. Production environments should always use a separate monitoring cluster. See HTTP exporters.
Both exporters serve the same purpose: to set up the monitoring cluster and route monitoring data. However, they perform these tasks in very different ways. Even though things happen differently, both exporters are capable of sending all of the same data.
Exporters are configurable at both the node and cluster level. Cluster-wide
settings, which are updated with the
_cluster/settings
API, take precedence over
settings in the elasticsearch.yml
file on each node. When you update an
exporter, it is completely replaced by the updated version of the exporter.
It is critical that all nodes share the same setup. Otherwise, monitoring data might be routed in different ways or to different places.
When the exporters route monitoring data into the monitoring cluster, they use
_bulk
indexing for optimal performance. All monitoring data is forwarded in
bulk to all enabled exporters on the same node. From there, the exporters
serialize the monitoring data and send a bulk request to the monitoring cluster.
There is no queuing—in memory or persisted to disk—so any failure during the
export results in the loss of that batch of monitoring data. This design limits
the impact on Elasticsearch and the assumption is that the next pass will succeed.
Routing monitoring data involves indexing it into the appropriate monitoring
indices. Once the data is indexed, it exists in a monitoring index that, by
default, is named with a daily index pattern. For Elasticsearch monitoring data, this is
an index that matches .monitoring-es-6-*
. From there, the data lives inside
the monitoring cluster and must be curated or cleaned up as necessary. If you do
not curate the monitoring data, it eventually fills up the nodes and the cluster
might fail due to lack of disk space.
You are strongly recommended to manage the curation of indices and particularly the monitoring indices. To do so, you can take advantage of the cleaner service or Elastic Curator.
There is also a disk watermark (known as the flood stage watermark), which protects clusters from running out of disk space. When this feature is triggered, it makes all indices (including monitoring indices) read-only until the issue is fixed and a user manually makes the index writeable again. While an active monitoring index is read-only, it will naturally fail to write (index) new data and will continuously log errors that indicate the write failure. For more information, see Disk-based shard allocation settings.
Default exporters
editIf a node or cluster does not explicitly define an exporter, the following default exporter is used:
The exporter name uniquely defines the exporter, but it is otherwise unused.
When you specify your own exporters, you do not need to explicitly overwrite
or reference |
If another exporter is already defined, the default exporter is not created. When you define a new exporter, if the default exporter exists, it is automatically removed.
Exporter templates and ingest pipelines
editBefore exporters can route monitoring data, they must set up certain Elasticsearch resources. These resources include templates and ingest pipelines. The following table lists the templates that are required before an exporter can route monitoring data:
Template | Purpose |
---|---|
|
All cluster alerts for monitoring data. |
|
All Beats monitoring data. |
|
All Elasticsearch monitoring data. |
|
All Kibana monitoring data. |
|
All Logstash monitoring data. |
The templates are ordinary Elasticsearch templates that control the default settings and mappings for the monitoring indices.
By default, monitoring indices are created daily (for example,
.monitoring-es-6-2017.08.26
). You can change the default date suffix for
monitoring indices with the index.name.time_format
setting. You can use this
setting to control how frequently monitoring indices are created by a specific
http
exporter. You cannot use this setting with local
exporters. For more
information, see HTTP exporter settings.
Some users create their own templates that match all index patterns,
which therefore impact the monitoring indices that get created. It is critical
that you do not disable _source
storage for the monitoring indices. If you do,
Kibana monitoring features do not work and you cannot visualize monitoring data
for your cluster.
The following table lists the ingest pipelines that are required before an exporter can route monitoring data:
Pipeline | Purpose |
---|---|
|
Upgrades X-Pack monitoring data coming from X-Pack 5.0 - 5.4 to be compatible with the format used in 5.5 monitoring features. |
|
A placeholder pipeline that is empty. |
Exporters handle the setup of these resources before ever sending data. If resource setup fails (for example, due to security permissions), no data is sent and warnings are logged.
Empty pipelines are evaluated on the coordinating node during indexing and they are ignored without any extra effort. This inherently makes them a safe, no-op operation.
For monitoring clusters that have disabled node.ingest
on all nodes, it is
possible to disable the use of the ingest pipeline feature. However, doing so
blocks its purpose, which is to upgrade older monitoring data as our mappings
improve over time. Beginning in 6.0, the ingest pipeline feature is a
requirement on the monitoring cluster; you must have node.ingest
enabled on at
least one node.
Once any node running 5.5 or later has set up the templates and ingest
pipeline on a monitoring cluster, you must use Kibana 5.5 or later to view all
subsequent data on the monitoring cluster. The easiest way to determine
whether this update has occurred is by checking for the presence of indices
matching .monitoring-es-6-*
(or more concretely the existence of the
new pipeline). Versions prior to 5.5 used .monitoring-es-2-*
.
Each resource that is created by an exporter has a version
field,
which is used to determine whether the resource should be replaced. The version
field value represents the latest version of monitoring features that changed the
resource. If a resource is edited by someone or something external to the
monitoring features, those changes are lost the next time an automatic update
occurs.