- Elasticsearch Guide: other versions:
- What is Elasticsearch?
- What’s new in 8.4
- Set up Elasticsearch
- Installing Elasticsearch
- Run Elasticsearch locally
- 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
- Health Diagnostic 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 and restore 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
- 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
- Attachment
- 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
- Collapse search results
- Filter search results
- Highlighting
- Long-running searches
- Near real-time search
- Paginate search results
- Retrieve inner hits
- Retrieve selected fields
- Search across clusters
- Search multiple data streams and indices
- Search shard routing
- Search templates
- Sort search results
- kNN search
- Query DSL
- Aggregations
- Bucket aggregations
- Adjacency matrix
- Auto-interval date histogram
- Categorize text
- Children
- Composite
- Date histogram
- Date range
- Diversified sampler
- Filter
- Filters
- Frequent items
- Geo-distance
- Geohash grid
- Geohex grid
- Geotile grid
- Global
- Histogram
- IP prefix
- IP range
- Missing
- Multi Terms
- Nested
- Parent
- Random sampler
- 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
- Change point
- Cumulative cardinality
- Cumulative sum
- Derivative
- Extended stats bucket
- Inference bucket
- Max bucket
- Min bucket
- 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
- 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
- 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
- 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
- How to
- 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
- Start index lifecycle management
- Start Snapshot Lifecycle Management
- Restore from snapshot
- Multiple deployments writing to the same snapshot repository
- Troubleshooting discovery
- Troubleshooting monitoring
- Troubleshooting transforms
- Troubleshooting Watcher
- Troubleshooting searches
- REST APIs
- API conventions
- Common options
- REST API compatibility
- 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
- 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
- Create or update desired nodes
- Get desired nodes
- Delete desired nodes
- 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
- Analyze index disk usage
- 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
- 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
- Resolve index
- 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
- Ingest APIs
- Info API
- Licensing APIs
- Logstash APIs
- Machine learning 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
- 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
- Preview datafeeds
- Reset jobs
- Revert model snapshots
- 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
- 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
- Start data frame analytics jobs
- Stop data frame analytics jobs
- Update data frame analytics jobs
- Machine learning trained model APIs
- Migration APIs
- Node lifecycle 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
- Enroll Kibana
- Enroll node
- 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
- Query API key information
- Update API key
- SAML prepare authentication
- SAML authenticate
- SAML logout
- SAML invalidate
- SAML complete logout
- SAML service provider metadata
- SSL certificate
- Activate user profile
- Disable user profile
- Enable user profile
- Get user profile
- Suggest user profile
- Update user profile data
- Has privileges user profile
- Snapshot and restore APIs
- Snapshot lifecycle management APIs
- SQL APIs
- Transform APIs
- Usage API
- Watcher APIs
- Definitions
- Migration guide
- Release notes
- 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
Logging
editLogging
editYou can use Elasticsearch’s application logs to monitor your cluster and diagnose issues. If you run Elasticsearch as a service, the default location of the logs varies based on your platform and installation method:
On Docker, log messages go to the console and are handled by the
configured Docker logging driver. To access logs, run docker logs
.
For Debian installations, Elasticsearch writes logs to /var/log/elasticsearch
.
For RPM installations, Elasticsearch writes logs to /var/log/elasticsearch
.
For macOS .tar.gz
installations, Elasticsearch writes logs to
$ES_HOME/logs
.
Files in $ES_HOME
risk deletion during an upgrade. In production, we strongly
recommend you set path.logs
to a location outside of $ES_HOME
.
See Path settings.
For Linux .tar.gz
installations, Elasticsearch writes logs to
$ES_HOME/logs
.
Files in $ES_HOME
risk deletion during an upgrade. In production, we strongly
recommend you set path.logs
to a location outside of $ES_HOME
.
See Path settings.
For Windows .zip
installations, Elasticsearch writes logs to
%ES_HOME%\logs
.
Files in %ES_HOME%
risk deletion during an upgrade. In production, we strongly
recommend you set path.logs
to a location outside of %ES_HOME%`
.
See Path settings.
If you run Elasticsearch from the command line, Elasticsearch prints logs to the standard output
(stdout
).
Logging configuration
editElastic strongly recommends using the Log4j 2 configuration that is shipped by default.
Elasticsearch uses Log4j 2 for
logging. Log4j 2 can be configured using the log4j2.properties
file. Elasticsearch exposes three properties, ${sys:es.logs.base_path}
,
${sys:es.logs.cluster_name}
, and ${sys:es.logs.node_name}
that can be
referenced in the configuration file to determine the location of the log
files. The property ${sys:es.logs.base_path}
will resolve to the log directory,
${sys:es.logs.cluster_name}
will resolve to the cluster name (used as the
prefix of log filenames in the default configuration), and
${sys:es.logs.node_name}
will resolve to the node name (if the node name is
explicitly set).
For example, if your log directory (path.logs
) is /var/log/elasticsearch
and
your cluster is named production
then ${sys:es.logs.base_path}
will resolve
to /var/log/elasticsearch
and
${sys:es.logs.base_path}${sys:file.separator}${sys:es.logs.cluster_name}.log
will resolve to /var/log/elasticsearch/production.log
.
######## Server JSON ############################ appender.rolling.type = RollingFile appender.rolling.name = rolling appender.rolling.fileName = ${sys:es.logs.base_path}${sys:file.separator}${sys:es.logs.cluster_name}_server.json appender.rolling.layout.type = ECSJsonLayout appender.rolling.layout.dataset = elasticsearch.server appender.rolling.filePattern = ${sys:es.logs.base_path}${sys:file.separator}${sys:es.logs.cluster_name}-%d{yyyy-MM-dd}-%i.json.gz appender.rolling.policies.type = Policies appender.rolling.policies.time.type = TimeBasedTriggeringPolicy appender.rolling.policies.time.interval = 1 appender.rolling.policies.time.modulate = true appender.rolling.policies.size.type = SizeBasedTriggeringPolicy appender.rolling.policies.size.size = 256MB appender.rolling.strategy.type = DefaultRolloverStrategy appender.rolling.strategy.fileIndex = nomax appender.rolling.strategy.action.type = Delete appender.rolling.strategy.action.basepath = ${sys:es.logs.base_path} appender.rolling.strategy.action.condition.type = IfFileName appender.rolling.strategy.action.condition.glob = ${sys:es.logs.cluster_name}-* appender.rolling.strategy.action.condition.nested_condition.type = IfAccumulatedFileSize appender.rolling.strategy.action.condition.nested_condition.exceeds = 2GB ################################################
Configure the |
|
Log to |
|
Use JSON layout. |
|
|
|
Roll logs to |
|
Use a time-based roll policy |
|
Roll logs on a daily basis |
|
Align rolls on the day boundary (as opposed to rolling every twenty-four hours) |
|
Using a size-based roll policy |
|
Roll logs after 256 MB |
|
Use a delete action when rolling logs |
|
Only delete logs matching a file pattern |
|
The pattern is to only delete the main logs |
|
Only delete if we have accumulated too many compressed logs |
|
The size condition on the compressed logs is 2 GB |
######## Server - old style pattern ########### appender.rolling_old.type = RollingFile appender.rolling_old.name = rolling_old appender.rolling_old.fileName = ${sys:es.logs.base_path}${sys:file.separator}${sys:es.logs.cluster_name}_server.log appender.rolling_old.layout.type = PatternLayout appender.rolling_old.layout.pattern = [%d{ISO8601}][%-5p][%-25c{1.}] [%node_name]%marker %m%n appender.rolling_old.filePattern = ${sys:es.logs.base_path}${sys:file.separator}${sys:es.logs.cluster_name}-%d{yyyy-MM-dd}-%i.old_log.gz
The configuration for |
Log4j’s configuration parsing gets confused by any extraneous whitespace; if you copy and paste any Log4j settings on this page, or enter any Log4j configuration in general, be sure to trim any leading and trailing whitespace.
Note than you can replace .gz
by .zip
in appender.rolling.filePattern
to
compress the rolled logs using the zip format. If you remove the .gz
extension then logs will not be compressed as they are rolled.
If you want to retain log files for a specified period of time, you can use a rollover strategy with a delete action.
appender.rolling.strategy.type = DefaultRolloverStrategy appender.rolling.strategy.action.type = Delete appender.rolling.strategy.action.basepath = ${sys:es.logs.base_path} appender.rolling.strategy.action.condition.type = IfFileName appender.rolling.strategy.action.condition.glob = ${sys:es.logs.cluster_name}-* appender.rolling.strategy.action.condition.nested_condition.type = IfLastModified appender.rolling.strategy.action.condition.nested_condition.age = 7D
Configure the |
|
Configure the |
|
The base path to the Elasticsearch logs |
|
The condition to apply when handling rollovers |
|
Delete files from the base path matching the glob
|
|
A nested condition to apply to files matching the glob |
|
Retain logs for seven days |
Multiple configuration files can be loaded (in which case they will get merged)
as long as they are named log4j2.properties
and have the Elasticsearch config
directory as an ancestor; this is useful for plugins that expose additional
loggers. The logger section contains the java packages and their corresponding
log level. The appender section contains the destinations for the logs.
Extensive information on how to customize logging and all the supported
appenders can be found on the
Log4j
documentation.
Configuring logging levels
editEach Java package in the Elasticsearch source code has a related logger. For
example, the org.elasticsearch.discovery
package has
logger.org.elasticsearch.discovery
for logs related to the
discovery process.
To get more or less verbose logs, use the cluster
update settings API to change the related logger’s log level. Each logger
accepts Log4j 2’s built-in log levels, from least to most verbose: OFF
,
FATAL
, ERROR
, WARN
, INFO
, DEBUG
, and TRACE
. The default log level is
INFO
. Messages logged at higher verbosity levels (DEBUG
and TRACE
) are
only intended for expert use.
PUT /_cluster/settings { "persistent": { "logger.org.elasticsearch.discovery": "DEBUG" } }
Other ways to change log levels include:
-
elasticsearch.yml
:logger.org.elasticsearch.discovery: DEBUG
This is most appropriate when debugging a problem on a single node.
-
log4j2.properties
:logger.discovery.name = org.elasticsearch.discovery logger.discovery.level = debug
This is most appropriate when you already need to change your Log4j 2 configuration for other reasons. For example, you may want to send logs for a particular logger to another file. However, these use cases are rare.
Deprecation logging
editElasticsearch also writes deprecation logs to the log directory. These logs record a message when you use deprecated Elasticsearch functionality. You can use the deprecation logs to update your application before upgrading Elasticsearch to a new major version.
By default, Elasticsearch rolls and compresses deprecation logs at 1GB. The default configuration preserves a maximum of five log files: four rolled logs and an active log.
Elasticsearch emits deprecation log messages at the CRITICAL
level. Those messages
are indicating that a used deprecation feature will be removed in a next major
version. Deprecation log messages at the WARN
level indicates that a less
critical feature was used, it won’t be removed in next major version, but might
be removed in the future.
To stop writing deprecation log messages, set logger.deprecation.level
to OFF
in log4j2.properties
:
logger.deprecation.level = OFF
Alternatively, you can change the logging level dynamically:
PUT /_cluster/settings { "persistent": { "logger.org.elasticsearch.deprecation": "OFF" } }
Refer to Configuring logging levels.
You can identify what is triggering deprecated functionality if X-Opaque-Id
was used as an HTTP header.
The user ID is included in the X-Opaque-ID
field in deprecation JSON logs.
{ "type": "deprecation", "timestamp": "2019-08-30T12:07:07,126+02:00", "level": "WARN", "component": "o.e.d.r.a.a.i.RestCreateIndexAction", "cluster.name": "distribution_run", "node.name": "node-0", "message": "[types removal] Using include_type_name in create index requests is deprecated. The parameter will be removed in the next major version.", "x-opaque-id": "MY_USER_ID", "cluster.uuid": "Aq-c-PAeQiK3tfBYtig9Bw", "node.id": "D7fUYfnfTLa2D7y-xw6tZg" }
Deprecation logs can be indexed into .logs-deprecation.elasticsearch-default
data stream
cluster.deprecation_indexing.enabled
setting is set to true.
Deprecation logs throttling
editDeprecation logs are deduplicated based on a deprecated feature key
and x-opaque-id so that if a feature is repeatedly used, it will not overload the deprecation logs.
This applies to both indexed deprecation logs and logs emitted to log files.
You can disable the use of x-opaque-id
in throttling by changing
cluster.deprecation_indexing.x_opaque_id_used.enabled
to false
See RateLimitingFilter
JSON log format
editTo make parsing Elasticsearch logs easier, logs are now printed in a JSON format.
This is configured by a Log4J layout property appender.rolling.layout.type = ECSJsonLayout
.
This layout requires a dataset
attribute to be set which is used to distinguish
logs streams when parsing.
appender.rolling.layout.type = ECSJsonLayout appender.rolling.layout.dataset = elasticsearch.server
Each line contains a single JSON document with the properties configured in ECSJsonLayout
.
See this class javadoc for more details.
However if a JSON document contains an exception, it will be printed over multiple lines.
The first line will contain regular properties and subsequent lines will contain the
stacktrace formatted as a JSON array.
You can still use your own custom layout. To do that replace the line
appender.rolling.layout.type
with a different layout. See sample below:
appender.rolling.type = RollingFile appender.rolling.name = rolling appender.rolling.fileName = ${sys:es.logs.base_path}${sys:file.separator}${sys:es.logs.cluster_name}_server.log appender.rolling.layout.type = PatternLayout appender.rolling.layout.pattern = [%d{ISO8601}][%-5p][%-25c{1.}] [%node_name]%marker %.-10000m%n appender.rolling.filePattern = ${sys:es.logs.base_path}${sys:file.separator}${sys:es.logs.cluster_name}-%d{yyyy-MM-dd}-%i.log.gz
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