- Elasticsearch Guide: other versions:
- Getting Started
- Set up Elasticsearch
- Installing Elasticsearch
- Configuring Elasticsearch
- Important Elasticsearch 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
- Starting Elasticsearch
- Stopping Elasticsearch
- Adding nodes to your cluster
- Installing X-Pack
- Set up X-Pack
- Configuring X-Pack Java Clients
- X-Pack Settings
- Bootstrap Checks for X-Pack
- Upgrade Elasticsearch
- API Conventions
- Document APIs
- Search APIs
- Aggregations
- Metrics Aggregations
- Avg Aggregation
- Weighted Avg Aggregation
- Cardinality Aggregation
- Extended Stats Aggregation
- Geo Bounds Aggregation
- Geo Centroid Aggregation
- Max Aggregation
- Min Aggregation
- Percentiles Aggregation
- Percentile Ranks Aggregation
- Scripted Metric Aggregation
- Stats Aggregation
- Sum Aggregation
- Top Hits Aggregation
- Value Count Aggregation
- Bucket Aggregations
- Adjacency Matrix Aggregation
- Auto-interval Date Histogram Aggregation
- Intervals
- Children Aggregation
- Composite Aggregation
- Date Histogram Aggregation
- Date Range Aggregation
- Diversified Sampler Aggregation
- Filter Aggregation
- Filters Aggregation
- Geo Distance Aggregation
- GeoHash grid Aggregation
- Global Aggregation
- Histogram Aggregation
- IP Range Aggregation
- Missing Aggregation
- Nested Aggregation
- Range Aggregation
- Reverse nested Aggregation
- Sampler Aggregation
- Significant Terms Aggregation
- Significant Text Aggregation
- Terms Aggregation
- Pipeline Aggregations
- Avg Bucket Aggregation
- Derivative Aggregation
- Max Bucket Aggregation
- Min Bucket Aggregation
- Sum Bucket Aggregation
- Stats Bucket Aggregation
- Extended Stats Bucket Aggregation
- Percentiles Bucket Aggregation
- Moving Average Aggregation
- Moving Function Aggregation
- Cumulative Sum Aggregation
- Bucket Script Aggregation
- Bucket Selector Aggregation
- Bucket Sort Aggregation
- Serial Differencing Aggregation
- Matrix Aggregations
- Caching heavy aggregations
- Returning only aggregation results
- Aggregation Metadata
- Returning the type of the aggregation
- Metrics Aggregations
- Indices APIs
- Create Index
- Delete Index
- Get Index
- Indices Exists
- Open / Close Index API
- Shrink Index
- Split Index
- Rollover Index
- Put Mapping
- Get Mapping
- Get Field Mapping
- Types Exists
- Index Aliases
- Update Indices Settings
- Get Settings
- Analyze
- Index Templates
- Indices Stats
- Indices Segments
- Indices Recovery
- Indices Shard Stores
- Clear Cache
- Flush
- Refresh
- Force Merge
- cat APIs
- Cluster APIs
- Query DSL
- Mapping
- Analysis
- Anatomy of an analyzer
- Testing analyzers
- Analyzers
- Normalizers
- Tokenizers
- Standard Tokenizer
- Letter Tokenizer
- Lowercase Tokenizer
- Whitespace Tokenizer
- UAX URL Email Tokenizer
- Classic Tokenizer
- Thai Tokenizer
- NGram Tokenizer
- Edge NGram Tokenizer
- Keyword Tokenizer
- Pattern Tokenizer
- Char Group Tokenizer
- Simple Pattern Tokenizer
- Simple Pattern Split Tokenizer
- Path Hierarchy Tokenizer
- Path Hierarchy Tokenizer Examples
- Token Filters
- Standard Token Filter
- ASCII Folding Token Filter
- Flatten Graph Token Filter
- Length Token Filter
- Lowercase Token Filter
- Uppercase Token Filter
- NGram Token Filter
- Edge NGram Token Filter
- Porter Stem Token Filter
- Shingle Token Filter
- Stop Token Filter
- Word Delimiter Token Filter
- Word Delimiter Graph Token Filter
- Multiplexer Token Filter
- Conditional Token Filter
- Predicate Token Filter Script
- Stemmer Token Filter
- Stemmer Override Token Filter
- Keyword Marker Token Filter
- Keyword Repeat Token Filter
- KStem Token Filter
- Snowball Token Filter
- Phonetic Token Filter
- Synonym Token Filter
- Synonym Graph Token Filter
- Compound Word Token Filters
- Reverse Token Filter
- Elision Token Filter
- Truncate Token Filter
- Unique Token Filter
- Pattern Capture Token Filter
- Pattern Replace Token Filter
- Trim Token Filter
- Limit Token Count Token Filter
- Hunspell Token Filter
- Common Grams Token Filter
- Normalization Token Filter
- CJK Width Token Filter
- CJK Bigram Token Filter
- Delimited Payload Token Filter
- Keep Words Token Filter
- Keep Types Token Filter
- Exclude mode settings example
- Classic Token Filter
- Apostrophe Token Filter
- Decimal Digit Token Filter
- Fingerprint Token Filter
- Minhash Token Filter
- Remove Duplicates Token Filter
- Character Filters
- Modules
- Index Modules
- Ingest Node
- Pipeline Definition
- Ingest APIs
- Accessing Data in Pipelines
- Conditional Execution in Pipelines
- Handling Failures in Pipelines
- Processors
- Append Processor
- Bytes Processor
- Convert Processor
- Date Processor
- Date Index Name Processor
- Dissect Processor
- Drop Processor
- Dot Expander Processor
- Fail Processor
- Foreach Processor
- Grok Processor
- Gsub Processor
- Join Processor
- JSON Processor
- KV Processor
- Lowercase Processor
- Pipeline Processor
- Remove Processor
- Rename Processor
- Script Processor
- Set Processor
- Set Security User Processor
- Split Processor
- Sort Processor
- Trim Processor
- Uppercase Processor
- URL Decode Processor
- SQL Access
- Monitor a cluster
- Rolling up historical data
- Set up a cluster for high availability
- Secure a cluster
- Overview
- Configuring security
- Encrypting communications in Elasticsearch
- Encrypting communications in an Elasticsearch Docker Container
- Enabling cipher suites for stronger encryption
- Separating node-to-node and client traffic
- Configuring an Active Directory realm
- Configuring a file realm
- Configuring an LDAP realm
- Configuring a native realm
- Configuring a PKI realm
- Configuring a SAML realm
- Configuring a Kerberos realm
- FIPS 140-2
- Security settings
- Security files
- Auditing settings
- How security works
- User authentication
- Built-in users
- Internal users
- Realms
- Realm chains
- Active Directory user authentication
- File-based user authentication
- LDAP user authentication
- Native user 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
- User authorization
- Auditing security events
- Encrypting communications
- Restricting connections with IP filtering
- Cross cluster search, tribe, clients, and integrations
- Tutorial: Getting started with security
- Tutorial: Encrypting communications
- Troubleshooting
- Can’t log in after upgrading to 6.5.4
- 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
- Alerting on Cluster and Index Events
- Command line tools
- How To
- Testing
- Glossary of terms
- X-Pack APIs
- Info API
- Cross-cluster replication APIs
- Explore API
- Licensing APIs
- Migration APIs
- Machine learning APIs
- Add events to calendar
- Add jobs to calendar
- Close jobs
- Create calendar
- Create datafeeds
- Create filter
- Create jobs
- Delete calendar
- Delete datafeeds
- Delete events from calendar
- Delete filter
- Delete forecast
- Delete jobs
- Delete jobs from calendar
- Delete model snapshots
- Find file structure
- Flush jobs
- Forecast jobs
- Get calendars
- Get buckets
- Get overall buckets
- Get categories
- Get datafeeds
- Get datafeed statistics
- Get influencers
- Get jobs
- Get job statistics
- Get machine learning info
- Get model snapshots
- Get scheduled events
- Get filters
- Get records
- Open jobs
- Post data to jobs
- Preview datafeeds
- Revert model snapshots
- Start datafeeds
- Stop datafeeds
- Update datafeeds
- Update filter
- Update jobs
- Update model snapshots
- Rollup APIs
- Security APIs
- Authenticate
- Change passwords
- Clear cache
- Clear roles cache
- Create or update application privileges
- Create or update role mappings
- Create or update roles
- Create or update users
- Delete application privileges
- Delete role mappings
- Delete roles
- Delete users
- Disable users
- Enable users
- Get application privileges
- Get role mappings
- Get roles
- Get token
- Get users
- Has privileges
- Invalidate token
- SSL certificate
- Watcher APIs
- Definitions
- Release Highlights
- Breaking changes
- Release Notes
- Elasticsearch version 6.5.4
- Elasticsearch version 6.5.3
- Elasticsearch version 6.5.2
- Elasticsearch version 6.5.1
- Elasticsearch version 6.5.0
- Elasticsearch version 6.4.3
- Elasticsearch version 6.4.2
- Elasticsearch version 6.4.1
- Elasticsearch version 6.4.0
- Elasticsearch version 6.3.2
- Elasticsearch version 6.3.1
- Elasticsearch version 6.3.0
- Elasticsearch version 6.2.4
- Elasticsearch version 6.2.3
- Elasticsearch version 6.2.2
- Elasticsearch version 6.2.1
- Elasticsearch version 6.2.0
- Elasticsearch version 6.1.4
- Elasticsearch version 6.1.3
- Elasticsearch version 6.1.2
- Elasticsearch version 6.1.1
- Elasticsearch version 6.1.0
- Elasticsearch version 6.0.1
- Elasticsearch version 6.0.0
- Elasticsearch version 6.0.0-rc2
- Elasticsearch version 6.0.0-rc1
- Elasticsearch version 6.0.0-beta2
- Elasticsearch version 6.0.0-beta1
- Elasticsearch version 6.0.0-alpha2
- Elasticsearch version 6.0.0-alpha1
- Elasticsearch version 6.0.0-alpha1 (Changes previously released in 5.x)
Exporters
editExporters
editThe 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 X-Pack monitoring for Elasticsearch. 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.
When using cluster alerts, Watcher creates daily .watcher_history*
indices.
These are not managed by X-Pack monitoring and they are not curated automatically. It
is therefore critical that you curate these indices to avoid an undesirable and
unexpected increase in the number of shards and indices and eventually the
amount of disk usage. If you are using a local
exporter, you can set the
xpack.watcher.history.cleaner_service.enabled
setting to true
and curate the
.watcher_history*
indices by using the
cleaner service. See General Watcher Settings.
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.
Default exporters
editIf a node or cluster does not explicitly define an X-Pack monitoring 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,
X-Pack monitoring for Kibana does 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 X-Pack monitoring 5.5. |
|
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 X-Pack monitoring 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 X-Pack monitoring that changed the
resource. If a resource is edited by someone or something external to
X-Pack monitoring, those changes are lost the next time an automatic update occurs.