- 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
- 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
- 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
- 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
- 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
- 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
- Classic Token Filter
- Apostrophe Token Filter
- Decimal Digit Token Filter
- Fingerprint Token Filter
- Minhash Token Filter
- Character Filters
- Modules
- Index Modules
- Ingest Node
- Pipeline Definition
- Ingest APIs
- Accessing Data in Pipelines
- Handling Failures in Pipelines
- Processors
- Append Processor
- Convert Processor
- Date Processor
- Date Index Name Processor
- Fail Processor
- Foreach Processor
- Grok Processor
- Gsub Processor
- Join Processor
- JSON Processor
- KV Processor
- Lowercase Processor
- Remove Processor
- Rename Processor
- Script Processor
- Set Processor
- Split Processor
- Sort Processor
- Trim Processor
- Uppercase Processor
- Dot Expander Processor
- URL Decode Processor
- SQL Access
- Monitor a cluster
- Rolling up historical data
- 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
- Security settings
- Auditing settings
- Getting started with security
- How security works
- User authentication
- 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
- Reference
- Troubleshooting
- Can’t log in after upgrading to 6.3.2
- 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 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
- X-Pack APIs
- Info API
- Explore API
- Licensing APIs
- Migration APIs
- Machine Learning APIs
- Add Events to Calendar
- Add Jobs to Calendar
- Close Jobs
- Create Calendar
- Create Datafeeds
- Create Jobs
- Delete Calendar
- Delete Datafeeds
- Delete Events from Calendar
- Delete Jobs
- Delete Jobs from Calendar
- Delete Model Snapshots
- 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 Model Snapshots
- Get Scheduled Events
- Get Records
- Open Jobs
- Post Data to Jobs
- Preview Datafeeds
- Revert Model Snapshots
- Start Datafeeds
- Stop Datafeeds
- Update Datafeeds
- Update Jobs
- Update Model Snapshots
- Rollup APIs
- Security APIs
- Authenticate API
- Change passwords API
- Clear Cache API
- Create or update role mappings API
- Clear roles cache API
- Create or update roles API
- Create or update users API
- Delete role mappings API
- Delete roles API
- Delete users API
- Disable users API
- Enable users API
- Get role mappings API
- Get roles API
- Get token API
- Get users API
- Privilege APIs
- Invalidate token API
- SSL Certificate API
- Watcher APIs
- Definitions
- Command line tools
- How To
- Testing
- Glossary of terms
- Release Highlights
- Breaking changes
- Release Notes
- 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)
Collectors
editCollectors
editCollectors, as their name implies, collect things. Each collector runs once for each collection interval to obtain data from the public APIs in Elasticsearch and X-Pack that it chooses to monitor. When the data collection is finished, the data is handed in bulk to the exporters to be sent to the monitoring clusters. Regardless of the number of exporters, each collector only runs once per collection interval.
There is only one collector per data type gathered. In other words, for any monitoring document that is created, it comes from a single collector rather than being merged from multiple collectors. X-Pack monitoring for Elasticsearch currently has a few collectors because the goal is to minimize overlap between them for optimal performance.
Each collector can create zero or more monitoring documents. For example,
the index_stats
collector collects all index statistics at the same time to
avoid many unnecessary calls.
Collector | Data Types | Description |
---|---|---|
Cluster Stats |
|
Gathers details about the cluster state, including parts of the actual cluster
state (for example |
Index Stats |
|
Gathers details about the indices in the cluster, both in summary and
individually. This creates many documents that represent parts of the index
statistics output (for example, |
Index Recovery |
|
Gathers details about index recovery in the cluster. Index recovery represents the assignment of shards at the cluster level. If an index is not recovered, it is not usable. This also corresponds to shard restoration via snapshots. This information only needs to be collected once, so it is collected on the elected master node. The most common failure for this collector relates to an extreme number of shards — and therefore time to gather them — resulting in timeouts. This creates a single document that contains all recoveries by default, which can be quite large, but it gives the most accurate picture of recovery in the production cluster. |
Shards |
|
Gathers details about all allocated shards for all indices, particularly including what node the shard is allocated to. This information only needs to be collected once, so it is collected on the elected master node. The collector uses the local cluster state to get the routing table without any network timeout issues unlike most other collectors. Each shard is represented by a separate monitoring document. |
Jobs |
|
Gathers details about all machine learning job statistics (for example, |
Node Stats |
|
Gathers details about the running node, such as memory utilization and CPU
usage (for example, |
X-Pack monitoring uses a single threaded scheduler to run the collection of Elasticsearch
monitoring data by all of the appropriate collectors on each node. This
scheduler is managed locally by each node and its interval is controlled by
specifying the xpack.monitoring.collection.interval
, which defaults to 10
seconds (10s
), at either the node or cluster level.
Fundamentally, each collector works on the same principle. Per collection interval, each collector is checked to see whether it should run and then the appropriate collectors run. The failure of an individual collector does not impact any other collector.
Once collection has completed, all of the monitoring data is passed to the exporters to route the monitoring data to the monitoring clusters.
If gaps exist in the monitoring charts in Kibana, it is typically because either a collector failed or the monitoring cluster did not receive the data (for example, it was being restarted). In the event that a collector fails, a logged error should exist on the node that attempted to perform the collection.
Collection is currently done serially, rather than in parallel, to avoid extra overhead on the elected master node. The downside to this approach is that collectors might observe a different version of the cluster state within the same collection period. In practice, this does not make a significant difference and running the collectors in parallel would not prevent such a possibility.
For more information about the configuration options for the collectors, see Monitoring Collection Settings.
Collecting data from across the Elastic Stack
editX-Pack monitoring in Elasticsearch also receives monitoring data from other parts of the Elastic Stack. In this way, it serves as an unscheduled monitoring data collector for the stack.
By default, data collection is disabled. Elasticsearch monitoring data is not
collected and all monitoring data from other sources such as Kibana, Beats, and
Logstash is ignored. You must set xpack.monitoring.collection.enabled
to true
to enable the collection of monitoring data. See Monitoring Settings.
Once data is received, it is forwarded to the exporters to be routed to the monitoring cluster like all monitoring data.
Because this stack-level "collector" lives outside of the collection
interval of X-Pack monitoring for Elasticsearch, it is not impacted by the
xpack.monitoring.collection.interval
setting. Therefore, data is passed to the
exporters whenever it is received. This behavior can result in indices for Kibana,
Logstash, or Beats being created somewhat unexpectedly.
While the monitoring data is collected and processed, some production cluster metadata is added to incoming documents. This metadata enables Kibana to link the monitoring data to the appropriate cluster. If this linkage is unimportant to the infrastructure that you’re monitoring, it might be simpler to configure Logstash and Beats to report monitoring data directly to the monitoring cluster. This scenario also prevents the production cluster from adding extra overhead related to monitoring data, which can be very useful when there are a large number of Logstash nodes or Beats.
For more information about typical monitoring architectures, see Overview.
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