- Elasticsearch Guide: other versions:
- What is Elasticsearch?
- What’s new in 7.14
- Quick start
- Set up Elasticsearch
- Installing Elasticsearch
- Configuring Elasticsearch
- Important Elasticsearch configuration
- Secure settings
- Auditing settings
- Circuit breaker settings
- Cluster-level shard allocation and routing settings
- Cross-cluster replication settings
- Discovery and cluster formation settings
- Field data cache settings
- Index lifecycle management settings
- Index management settings
- Index recovery settings
- Indexing buffer settings
- License settings
- Local gateway settings
- Logging
- Machine learning settings
- Monitoring settings
- Node
- Networking
- Node query cache settings
- Search settings
- Security settings
- Shard request cache settings
- Snapshot lifecycle management settings
- Transforms settings
- Thread pools
- Watcher settings
- Advanced configuration
- Important System Configuration
- Bootstrap Checks
- Heap size check
- File descriptor check
- Memory lock check
- Maximum number of threads check
- Max file size check
- Maximum size virtual memory check
- Maximum map count check
- Client JVM check
- Use serial collector check
- System call filter check
- OnError and OnOutOfMemoryError checks
- Early-access check
- G1GC check
- All permission check
- Discovery configuration check
- Bootstrap Checks for X-Pack
- Starting Elasticsearch
- Stopping Elasticsearch
- Discovery and cluster formation
- Add and remove nodes in your cluster
- Full-cluster restart and rolling restart
- Remote clusters
- Set up X-Pack
- Configuring X-Pack Java Clients
- Plugins
- Upgrade Elasticsearch
- Index modules
- Mapping
- Text analysis
- Overview
- Concepts
- Configure text analysis
- Built-in analyzer reference
- Tokenizer reference
- Token filter reference
- Apostrophe
- ASCII folding
- CJK bigram
- CJK width
- Classic
- Common grams
- Conditional
- Decimal digit
- Delimited payload
- Dictionary decompounder
- Edge n-gram
- Elision
- Fingerprint
- Flatten graph
- Hunspell
- Hyphenation decompounder
- Keep types
- Keep words
- Keyword marker
- Keyword repeat
- KStem
- Length
- Limit token count
- Lowercase
- MinHash
- Multiplexer
- N-gram
- Normalization
- Pattern capture
- Pattern replace
- Phonetic
- Porter stem
- Predicate script
- Remove duplicates
- Reverse
- Shingle
- Snowball
- Stemmer
- Stemmer override
- Stop
- Synonym
- Synonym graph
- Trim
- Truncate
- Unique
- Uppercase
- Word delimiter
- Word delimiter graph
- Character filters reference
- Normalizers
- Index templates
- Data streams
- Ingest pipelines
- Example: Parse logs
- Enrich your data
- Processor reference
- Append
- Bytes
- Circle
- Community ID
- Convert
- CSV
- Date
- Date index name
- Dissect
- Dot expander
- Drop
- Enrich
- Fail
- Fingerprint
- Foreach
- GeoIP
- Grok
- Gsub
- HTML strip
- Inference
- Join
- JSON
- KV
- Lowercase
- Network direction
- Pipeline
- Registered domain
- Remove
- Rename
- Script
- Set
- Set security user
- Sort
- Split
- Trim
- Uppercase
- URL decode
- URI parts
- User agent
- Aliases
- Search your data
- Query DSL
- Aggregations
- Bucket aggregations
- Adjacency matrix
- Auto-interval date histogram
- Children
- Composite
- Date histogram
- Date range
- Diversified sampler
- Filter
- Filters
- Geo-distance
- Geohash grid
- Geotile grid
- Global
- Histogram
- IP range
- Missing
- Multi Terms
- Nested
- Parent
- Range
- Rare terms
- Reverse nested
- Sampler
- Significant terms
- Significant text
- Terms
- Variable width histogram
- Subtleties of bucketing range fields
- Metrics aggregations
- Pipeline aggregations
- Average bucket
- Bucket script
- Bucket count K-S test
- Bucket correlation
- Bucket selector
- Bucket sort
- Cumulative cardinality
- Cumulative sum
- Derivative
- Extended stats bucket
- Inference bucket
- Max bucket
- Min bucket
- Moving average
- Moving function
- Moving percentiles
- Normalize
- Percentiles bucket
- Serial differencing
- Stats bucket
- Sum bucket
- Bucket aggregations
- EQL
- SQL
- Overview
- Getting Started with SQL
- Conventions and Terminology
- Security
- SQL REST API
- SQL Translate API
- SQL CLI
- SQL JDBC
- SQL ODBC
- SQL Client Applications
- SQL Language
- Functions and Operators
- Comparison Operators
- Logical Operators
- Math Operators
- Cast Operators
- LIKE and RLIKE Operators
- 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
- Overview
- Concepts
- Automate rollover
- Customize built-in ILM policies
- 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
- 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
- Configuring security
- Updating node security certificates
- User authentication
- Built-in users
- Service accounts
- Internal users
- Token-based authentication services
- Realms
- Realm chains
- Active Directory user authentication
- File-based user authentication
- LDAP user authentication
- Native user authentication
- OpenID Connect authentication
- PKI user authentication
- SAML authentication
- Kerberos authentication
- Integrating with other authentication systems
- Enabling anonymous access
- 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
- Granting access to Stack Management features
- 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
- Cross cluster search, 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
- Command line tools
- How to
- REST APIs
- API conventions
- Autoscaling APIs
- Compact and aligned text (CAT) APIs
- cat aliases
- cat allocation
- cat anomaly detectors
- 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
- Cluster reroute
- Cluster state
- Cluster stats
- Cluster update settings
- Nodes feature usage
- Nodes hot threads
- Nodes info
- Nodes reload secure settings
- Nodes stats
- Pending cluster tasks
- Remote cluster info
- Task management
- Voting configuration exclusions
- Cross-cluster replication APIs
- Data stream APIs
- Document APIs
- Enrich APIs
- EQL APIs
- Features APIs
- Fleet APIs
- Find structure API
- Graph explore API
- Index APIs
- Alias exists
- Aliases
- Analyze
- Clear cache
- Clone index
- Close index
- Create index
- Create or update alias
- Create or update component template
- Create or update index template
- Create or update index template (legacy)
- Delete component template
- Delete dangling index
- Delete alias
- Delete index
- Delete index template
- Delete index template (legacy)
- Exists
- Flush
- Force merge
- Freeze index
- 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
- Resolve index
- Rollover
- Shrink index
- Simulate index
- Simulate template
- Split index
- Synced flush
- Type exists
- Unfreeze index
- Update index settings
- Update mapping
- Index lifecycle management APIs
- Ingest APIs
- Info API
- Licensing APIs
- Logstash APIs
- Machine learning anomaly detection APIs
- Add events to calendar
- Add jobs to calendar
- Close jobs
- Create jobs
- Create calendars
- Create datafeeds
- Create filters
- Delete calendars
- Delete datafeeds
- Delete events from calendar
- Delete filters
- Delete forecasts
- Delete jobs
- Delete jobs from calendar
- Delete model snapshots
- Delete expired data
- Estimate model memory
- Find file structure
- Flush jobs
- Forecast jobs
- Get buckets
- Get calendars
- Get categories
- Get datafeeds
- Get datafeed statistics
- Get influencers
- Get jobs
- Get job statistics
- Get machine learning info
- Get model snapshots
- Get overall buckets
- Get scheduled events
- Get filters
- Get records
- Open jobs
- Post data to jobs
- Preview datafeeds
- Reset jobs
- Revert model snapshots
- Set upgrade mode
- Start datafeeds
- Stop datafeeds
- Update datafeeds
- Update filters
- Update jobs
- Update model snapshots
- Upgrade model snapshots
- Machine learning data frame analytics APIs
- Create data frame analytics jobs
- Create or update trained model aliases
- Create trained models
- Update data frame analytics jobs
- Delete data frame analytics jobs
- Delete trained models
- Delete trained model aliases
- Evaluate data frame analytics
- Explain data frame analytics
- Get data frame analytics jobs
- Get data frame analytics jobs stats
- Get trained models
- Get trained models stats
- Preview data frame analytics
- Start data frame analytics jobs
- Stop data frame analytics jobs
- Migration APIs
- Reload search analyzers API
- Repositories metering APIs
- Rollup APIs
- Script APIs
- Search APIs
- Searchable snapshots APIs
- Security APIs
- Authenticate
- Change passwords
- Clear cache
- Clear roles cache
- Clear privileges cache
- Clear API key cache
- Clear service account token caches
- Create API keys
- Create or update application privileges
- Create or update role mappings
- Create or update roles
- Create or update users
- Create service account tokens
- Delegate PKI authentication
- Delete application privileges
- Delete role mappings
- Delete roles
- Delete service account token
- Delete users
- Disable users
- Enable users
- Get API key information
- Get application privileges
- Get builtin privileges
- Get role mappings
- Get roles
- Get service accounts
- Get service account credentials
- Get token
- Get user privileges
- Get users
- Grant API keys
- Has privileges
- Invalidate API key
- Invalidate token
- OpenID Connect prepare authentication
- OpenID Connect authenticate
- OpenID Connect logout
- SAML prepare authentication
- SAML authenticate
- SAML logout
- SAML invalidate
- SAML complete logout
- SAML service provider metadata
- SSL certificate
- Snapshot and restore APIs
- Snapshot lifecycle management APIs
- SQL APIs
- Transform APIs
- Usage API
- Watcher APIs
- Definitions
- Migration guide
- Release notes
- Elasticsearch version 7.14.2
- Elasticsearch version 7.14.1
- Elasticsearch version 7.14.0
- Elasticsearch version 7.13.4
- Elasticsearch version 7.13.3
- Elasticsearch version 7.13.2
- Elasticsearch version 7.13.1
- Elasticsearch version 7.13.0
- Elasticsearch version 7.12.1
- Elasticsearch version 7.12.0
- Elasticsearch version 7.11.2
- Elasticsearch version 7.11.1
- Elasticsearch version 7.11.0
- Elasticsearch version 7.10.2
- Elasticsearch version 7.10.1
- Elasticsearch version 7.10.0
- Elasticsearch version 7.9.3
- Elasticsearch version 7.9.2
- Elasticsearch version 7.9.1
- Elasticsearch version 7.9.0
- Elasticsearch version 7.8.1
- Elasticsearch version 7.8.0
- Elasticsearch version 7.7.1
- Elasticsearch version 7.7.0
- Elasticsearch version 7.6.2
- Elasticsearch version 7.6.1
- Elasticsearch version 7.6.0
- Elasticsearch version 7.5.2
- Elasticsearch version 7.5.1
- Elasticsearch version 7.5.0
- Elasticsearch version 7.4.2
- Elasticsearch version 7.4.1
- Elasticsearch version 7.4.0
- Elasticsearch version 7.3.2
- Elasticsearch version 7.3.1
- Elasticsearch version 7.3.0
- Elasticsearch version 7.2.1
- Elasticsearch version 7.2.0
- Elasticsearch version 7.1.1
- Elasticsearch version 7.1.0
- Elasticsearch version 7.0.0
- Elasticsearch version 7.0.0-rc2
- Elasticsearch version 7.0.0-rc1
- Elasticsearch version 7.0.0-beta1
- Elasticsearch version 7.0.0-alpha2
- Elasticsearch version 7.0.0-alpha1
- Dependencies and versions
Exporters
editExporters
editMetricbeat is the recommended method for collecting and shipping monitoring data to a monitoring cluster.
If you have previously configured legacy collection methods, you should migrate to using Metricbeat collection methods. Use either Metricbeat collection or legacy collection methods; do not use both.
Learn more about Collecting monitoring data with Metricbeat.
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.