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Log Messages¶
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Overview¶
As part of normal operation, MongoDB maintains a running log of events, including entries such as incoming connections, commands run, and issues encountered. Generally, log messages are useful for diagnosing issues, monitoring your deployment, and tuning performance.
Structured Logging¶
Starting in MongoDB 4.4, mongod
/ mongos
instances output all log messages in structured JSON format. Log entries are written as a series
of key-value pairs, where each key indicates a log message field type,
such as “severity”, and each corresponding value records the associated
logging information for that field type, such as “informational”.
Previously, log entries were output as plaintext.
Example
The following is an example log message in JSON format as it would appear in the MongoDB log file:
JSON log entries can be pretty-printed for readability. Here is the same log entry pretty-printed:
In this log entry, for example, the key s
, representing
severity, has a corresponding value of
I
, representing “Informational”, and the key c
, representing
component, has a corresponding value
of NETWORK
, indicating that the “network” component was
responsible for this particular message. The various field types are
presented in detail in the Log Message Field Types section.
Structured logging with key-value pairs allows for efficient parsing by automated tools or log ingestion services, and makes programmatic search and analysis of log messages easier to perform. Examples of analyzing structured log messages can be found in the Parsing Structured Log Messages section.
JSON Log Output Format¶
With MongoDB 4.4, all log output is now in JSON format. This includes
log output sent to the file, syslog, and stdout (standard out)
log destinations, as well as the
output of the getLog
command.
Each log entry is output as a self-contained JSON object which follows the Relaxed Extended JSON v2.0 specification, and has the following layout and field order:
- Timestamp - Timestamp of the log message, in
ISO-8601
format. See Timestamp. - Severity - String representing the short severity code of the log message. See Severity.
- Component - String representing the full component string of the log message. See Components.
- Context - String representing the name of the thread issuing the log statement.
- id - String representing the unique identifier of the log statement. See Filtering by Known Log ID for an example.
- Message - String representing the raw log output message as passed from the server or driver. This message is escaped as needed according to the JSON specification.
- Attributes - (optional) Object containing one or more key-value pairs for any additional attributes provided. If a log message does not include any additional attributes, this object is omitted. Attribute values may be referenced by their key name in the message body, depending on the message. Like message, attributes are escaped as needed according to the JSON specification.
- Tags - (optional) Array of strings representing any tags
applicable to the log statement, for example:
["startupWarnings"]
. - Truncated - (if truncated) Object containing information regarding log message truncation, if applicable. This object will only be present if the log entry contains at least one attribute that was truncated.
- Size - (if truncated) Integer representing the original size of a log entry if it has been truncated. This field will only be present if the log entry contains at least one attribute that was truncated.
Escaping¶
The message and attributes fields will escape control characters as necessary according to the Relaxed Extended JSON v2.0 specification:
Character Represented | Escape Sequence |
---|---|
Quotation Mark (" ) |
\" |
Backslash (\ ) |
\\ |
Backspace (0x08 ) |
\b |
Formfeed (0x0C ) |
\f |
Newline (0x0A ) |
\n |
Carriage return (0x0D ) |
\r |
Horizontal tab (0x09 ) |
\t |
Control characters not listed above are escaped with \uXXXX
where
“XXXX” is the unicode codepoint in hexadecimal. Bytes with invalid
UTF-8 encoding are replaced with the unicode replacement character
represented by \ufffd
.
An example of message escaping is provided in the examples section.
Truncation¶
Any attributes that exceed the maximum size defined with
maxLogSizeKB
(default: 10 KB) are truncated. Truncated
attributes omit log data beyond the configured limit, but retain the
JSON formatting of the entry to ensure that the entry remains parsable.
Here is an example of a log entry with a truncated attribute:
In this case, the request
attribute has been truncated and the
specific instance of its subfield _id
that triggered truncation
(i.e. caused the attribute to overrun maxLogSizeKB
) is
printed without data as {"_id":{}}
. The remainder of the request
attribute is then omitted.
Log entires containing one or more truncated attributes include a
truncated
object which provides the following information for each
truncated attribute in the log entry:
- the attribute that was truncated
- the specific subobject of that attribute that triggered truncation, if applicable.
- the data
type
of the truncated field - the
size
of the truncated field
Log entries with truncated attributes may also include an additional
size
field at the end of the entry which indicates the original
size of the attribute before truncation, in this case 46328
or about
46KB. This final size
field is only shown if it is different from
the size
field in the truncated
object, i.e. if the total object
size of the attribute is different from the size of the truncated
subobject, as is the case in the example above.
Padding¶
When output to the file or the syslog log destinations, padding is added after the severity, context, and id fields to increase readability when viewed with a fixed-width font.
The following MongoDB log file excerpt demonstrates this padding:
Pretty Printing¶
When working with MongoDB structured logging, the jq command-line utility is a useful tool that allows for easy pretty-printing of log entries, and powerful key-based matching and filtering.
jq
is an open-source JSON parser, and is available for
Linux, Windows, and macOS.
You can use jq
to pretty-print log entires as follows:
Pretty-print the entire log file:
Pretty-print the most recent log entry:
More examples of working with MongoDB structured logs are available in the Parsing Structured Log Messages section.
Configuring Log Message Destinations¶
MongoDB log messages can be output to file, syslog, or stdout (standard output).
To configure the log output destination, use one of the following settings, either in the configuration file or on the command-line:
- Configuration file:
- The
systemLog.destination
option for file or syslog
- The
- Command-line:
Not specifying either file or syslog sends all logging output to stdout.
For the full list of logging settings and options see:
- Configuration file:
- Command-line:
- Log options list for
mongod
- Log options list for
mongos
- Log options list for
Note
Error messages sent to stderr
(standard error), such as fatal
errors during startup when not using the file or syslog log
destinations, or messages having to do with misconfigured logging
settings, are not affected by the log output destination setting, and
are printed to stderr
in plaintext format.
Log Message Field Types¶
Timestamp¶
The timestamp field type indicates the precise date and time at which the logged event occurred.
When logging to file or to syslog [1], the default
format for the timestamp is iso8601-local
. To modify the
timestamp format, use the --timeStampFormat
runtime option or the
systemLog.timeStampFormat
setting.
See Filtering by Date Range for log parsing examples that filter on the timestamp field.
Note
Starting in MongoDB 4.4, the ctime
timestamp format is no longer
supported.
[1] | If logging to syslog, the syslog daemon generates timestamps
when it logs a message, not when MongoDB issues the message. This
can lead to misleading timestamps for log entries, especially when
the system is under heavy load. |
Severity¶
The severity field type indicates the severity level associated with the logged event.
Severity levels range from “Fatal” (most severe) to “Debug” (least severe):
Level | Description |
---|---|
F |
Fatal |
E |
Error |
W |
Warning |
I |
Informational, for verbosity level 0 |
D1 - D5 |
Debug, for verbosity levels > Starting in version 4.2, MongoDB indicates the specific
debug verbosity level.
For example, if verbosity level is 2, MongoDB indicates In previous versions, MongoDB log messages specified |
You can specify the verbosity level of various components to determine the amount of Informational and Debug messages MongoDB outputs. Severity categories above these levels are always shown. [2] To set verbosity levels, see Configure Log Verbosity Levels.
Components¶
The component field type indicates the category a logged event is a member of, such as NETWORK or COMMAND.
Each component is individually configurable via its own verbosity filter. The available components are as follows:
-
ACCESS
¶ Messages related to access control, such as authentication. To specify the log level for
ACCESS
components, use thesystemLog.component.accessControl.verbosity
setting.
-
COMMAND
¶ Messages related to database commands, such as
count
. To specify the log level forCOMMAND
components, use thesystemLog.component.command.verbosity
setting.
-
CONTROL
¶ Messages related to control activities, such as initialization. To specify the log level for
CONTROL
components, use thesystemLog.component.control.verbosity
setting.
-
ELECTION
¶ Messages related specifically to replica set elections. To specify the log level for
ELECTION
components, set thesystemLog.component.replication.election.verbosity
parameter.REPL
is the parent component ofELECTION
. IfsystemLog.component.replication.election.verbosity
is unset, MongoDB uses theREPL
verbosity level forELECTION
components.
-
FTDC
¶ New in version 3.2.
Messages related to the diagnostic data collection mechanism, such as server statistics and status messages. To specify the log level for
FTDC
components, use thesystemLog.component.ftdc.verbosity
setting.
-
GEO
¶ Messages related to the parsing of geospatial shapes, such as verifying the GeoJSON shapes. To specify the log level for
GEO
components, set thesystemLog.component.geo.verbosity
parameter.
-
INDEX
¶ Messages related to indexing operations, such as creating indexes. To specify the log level for
INDEX
components, set thesystemLog.component.index.verbosity
parameter.
-
INITSYNC
¶ Messages related to initial sync operation. To specify the log level for
INITSYNC
components, set thesystemLog.component.replication.initialSync.verbosity
parameter.REPL
is the parent component ofINITSYNC
. IfsystemLog.component.replication.initialSync.verbosity
is unset, MongoDB uses theREPL
verbosity level forINITSYNC
components.
-
JOURNAL
¶ Messages related specifically to storage journaling activities. To specify the log level for
JOURNAL
components, use thesystemLog.component.storage.journal.verbosity
setting.STORAGE
is the parent component ofJOURNAL
. IfsystemLog.component.storage.journal.verbosity
is unset, MongoDB uses theSTORAGE
verbosity level forJOURNAL
components.
-
NETWORK
¶ Messages related to network activities, such as accepting connections. To specify the log level for
NETWORK
components, set thesystemLog.component.network.verbosity
parameter.
-
QUERY
¶ Messages related to queries, including query planner activities. To specify the log level for
QUERY
components, set thesystemLog.component.query.verbosity
parameter.
-
RECOVERY
¶ Messages related to storage recovery activities. To specify the log level for
RECOVERY
components, use thesystemLog.component.storage.recovery.verbosity
setting.STORAGE
is the parent component ofRECOVERY
. IfsystemLog.component.storage.recovery.verbosity
is unset, MongoDB uses theSTORAGE
verbosity level forRECOVERY
components.
-
REPL
¶ Messages related to replica sets, such as initial sync, heartbeats, steady state replication, and rollback. [2] To specify the log level for
REPL
components, set thesystemLog.component.replication.verbosity
parameter.REPL
is the parent component of theELECTION
,INITSYNC
,REPL_HB
, andROLLBACK
components.
-
REPL_HB
¶ Messages related specifically to replica set heartbeats. To specify the log level for
REPL_HB
components, set thesystemLog.component.replication.heartbeats.verbosity
parameter.REPL
is the parent component ofREPL_HB
. IfsystemLog.component.replication.heartbeats.verbosity
is unset, MongoDB uses theREPL
verbosity level forREPL_HB
components.
-
ROLLBACK
¶ Messages related to rollback operations. To specify the log level for
ROLLBACK
components, set thesystemLog.component.replication.rollback.verbosity
parameter.REPL
is the parent component ofROLLBACK
. IfsystemLog.component.replication.rollback.verbosity
is unset, MongoDB uses theREPL
verbosity level forROLLBACK
components.
-
SHARDING
¶ Messages related to sharding activities, such as the startup of the
mongos
. To specify the log level forSHARDING
components, use thesystemLog.component.sharding.verbosity
setting.
-
STORAGE
¶ Messages related to storage activities, such as processes involved in the
fsync
command. To specify the log level forSTORAGE
components, use thesystemLog.component.storage.verbosity
setting.
-
TXN
¶ New in version 4.0.2.
Messages related to multi-document transactions. To specify the log level for
TXN
components, use thesystemLog.component.transaction.verbosity
setting.
-
WRITE
¶ Messages related to write operations, such as
update
commands. To specify the log level forWRITE
components, use thesystemLog.component.write.verbosity
setting.
-
-
¶ Messages not associated with a named component. Unnamed components have the default log level specified in the
systemLog.verbosity
setting. ThesystemLog.verbosity
setting is the default setting for both named and unnamed components.
Client Data¶
MongoDB drivers and
client applications (including the mongo
shell) have the
ability to send identifying information at the time of connection to the
server. After the connection is established, the client does not send
the identifying information again unless the connection is dropped
and reestablished.
This identifying information is contained in the attributes field of the log entry. The exact information included varies by client.
Below is a sample log message containing the client data document as
transmitted from a mongo
shell connection. The client
data is contained in the doc
object in the attributes field:
When secondary members of a
replica set initiate
a connection to a primary, they send similar data. A sample log message
containing this initiation connection might appear as follows. The
client data is contained in the doc
object in the attributes
field:
See the examples section for a pretty-printed example showing client data.
For a complete description of client information and required fields, see the MongoDB Handshake specification.
Verbosity Levels¶
You can specify the logging verbosity level to increase or decrease the the amount of log messages MongoDB outputs. Verbosity levels can be adjusted for all components together, or for specific named components individually.
Verbosity affects log entires in the severity categories Informational and Debug only. Severity categories above these levels are always shown.
You might set verbosity levels to a high value to show detailed logging for debugging or development, or to a low value to minimize writes to the log on a vetted production deployment. [2]
View Current Log Verbosity Level¶
To view the current verbosity levels, use the
db.getLogComponents()
method:
Your output might resemble the following:
The initial verbosity
entry is the parent verbosity level for all
components, while the individual named components that follow, such as accessControl
,
indicate the specific verbosity level for that component, overriding the
global verbosity level for that particular component if set.
A value of -1
, indicates that the component inherits the verbosity
level of their parent, if they have one (as with recovery
above,
inheriting from storage
), or the global verbosity level if they do
not (as with command
). Inheritance relationships for verbosity
levels are indicated in the components section.
Configure Log Verbosity Levels¶
You can configure the verbosity level using: the
systemLog.verbosity
and
systemLog.component.<name>.verbosity
settings, the
logComponentVerbosity
parameter, or the
db.setLogLevel()
method. [2]
systemLog
Verbosity Settings¶
To configure the default log level for all components, use the systemLog.verbosity
setting. To configure the level of specific components, use the
systemLog.component.<name>.verbosity
settings.
For example, the following configuration sets the
systemLog.verbosity
to 1
, the
systemLog.component.query.verbosity
to 2
, the
systemLog.component.storage.verbosity
to 2
, and the
systemLog.component.storage.journal.verbosity
to 1
:
You would set these values in the configuration file or on the command line for your
mongod
or mongos
instance.
All components not specified explicitly in the configuration have a
verbosity level of -1
, indicating that they inherit the verbosity
level of their parent, if they have one, or the global verbosity level
(systemLog.verbosity
) if they do not.
logComponentVerbosity
Parameter¶
To set the logComponentVerbosity
parameter, pass a
document with the verbosity settings to change.
For example, the following sets the default verbosity level
to 1
, the query
to 2
, the storage
to 2
, and the
storage.journal
to 1
.
You would set these values from the mongo
shell.
db.setLogLevel()
¶
Use the db.setLogLevel()
method to update a single component
log level. For a component, you can specify verbosity level of 0
to
5
, or you can specify -1
to inherit the verbosity of the
parent. For example, the following sets the
systemLog.component.query.verbosity
to its parent verbosity
(i.e. default verbosity):
You would set this value from the mongo
shell.
[2] | (1, 2, 3, 4, 5) Starting in version 4.2 (also available starting in 4.0.6), secondary members of a replica set now
log oplog entries that take longer than the slow
operation threshold to apply. These slow oplog messages are logged
for the secondaries in the diagnostic log under the REPL component with the text applied
op: <oplog entry> took <num>ms . These slow oplog entries depend
only on the slow operation threshold. They do not depend on the log
levels (either at the system or component level), or the profiling
level, or the slow operation sample rate. The profiler does not
capture slow oplog entries. |
Logging Slow Operations¶
Client operations (such as queries) appear in the log if their duration exceeds the slow operation threshold or when the log verbosity level is 1 or higher. [2] These log entries include the full command object associated with the operation.
Starting in MongoDB 4.2, the profiler entries and the diagnostic log messages (i.e. mongod/mongos log messages) for read/write operations include:
queryHash
to help identify slow queries with the same query shape.planCacheKey
to provide more insight into the query plan cache for slow queries.
The following example output includes information about a slow aggregation operation:
See the examples section for a pretty-printed version of this log entry.
Parsing Structured Log Messages¶
Log parsing is the act of programmatically searching through and analyzing log files, often in an automated manner. With the introduction of structured logging in MongoDB 4.4, log parsing is made simpler and more powerful. For example:
- Log message fields are presented as key-value pairs. Log parsers can query by specific keys of interest to efficiently filter results.
- Log messages always contain the same message structure. Log parsers can reliably extract information from any log message, without needing to code for cases where information is missing or formatted differently.
The following examples demonstrate common log parsing workflows when working with MongoDB JSON log output.
Log Parsing Examples¶
When working with MongoDB structured logging, the jq command-line utility is a useful tool that allows for easy pretty-printing of log entries, and powerful key-based matching and filtering.
jq
is an open-source JSON parser, and is available for
Linux, Windows, and macOS.
These examples use jq
to simplify log parsing.
Counting Unique Messages¶
The following example shows the top 10 unique message values in a given log file, sorted by frequency:
Monitoring Connections¶
Remote client connections are shown in the log under the “remote” key in the attribute object. The following counts all unique connections over the course of the log file and presents them in descending order by number of occurrences:
Note that connections from the same IP address, but connecting over different ports, are treated as different connections by this command. You could limit output to consider IP addresses only, with the following change:
Analyzing Driver Connections¶
The following example counts all remote MongoDB driver connections, and presents each driver type and version in descending order by number of occurrences:
Analyzing Client Types¶
The following example analyzes the reported client data of remote MongoDB driver
connections and client applications, including the mongo
shell, and prints a total for each unique operating system type that
connected, sorted by frequency:
The string “Darwin”, as reported in this log field, represents a macOS client.
Analyzing Slow Queries¶
With slow operation logging enabled, the following returns only the slow operations that took above 2000 milliseconds:, for further analysis:
Consult the jq documentation
for more information on the jq
filters shown in this example.
Filtering by Known Log ID¶
Log IDs (the fifth field in the JSON log output format) map to specific log events, and can be relied upon to remain stable over successive MongoDB releases.
As an example, you might be interested in the following two log events, showing a client connection followed by a disconnection:
The log IDs for these two entires are 22943
and 22944
respectively. You could then filter your log output to show only these
log IDs, effectively showing only client connection activity, using the
following jq
syntax:
Consult the jq documentation
for more information on the jq
filters shown in this example.
Filtering by Date Range¶
Log output can be further refined by filtering on the timestamp field, limiting log entires returned to a specific date range. For example, the following returns all log entries that occurred on April 15th, 2020:
Note that this syntax includes the full timestamp, including milliseconds but excluding the timezone offset.
Filtering by date range can be combined with any of the examples above, creating weekly reports or yearly summaries for example. The following syntax expands the “Monitoring Connections” example from earlier to limit results to the month of May, 2020:
Consult the jq documentation
for more information on the jq
filters shown in this example.
Log Ingestion Services¶
Log ingestion services are third-party products that intake and aggregate log files, usually from a distributed cluster of systems, and provide ongoing analysis of that data in a central location.
The JSON log format, introduced with MongoDB 4.4, allows for more flexibility when working with log ingestion and analysis services. Whereas plaintext logs generally require some manner of transformation before being eligible for use with these products, JSON files can often be consumed out of the box, depending on the service. Further, JSON-formatted logs offer more control when performing filtering for these services, as the key-value structure offers the ability to specifically import only the fields of interest, while omitting the rest.
Consult the documentation for your chosen third-party log ingestion service for more information.
Log Message Examples¶
The following examples show log messages in JSON output format.
These log messages are presented in pretty-printed format for convenience.
Startup Warning¶
This example shows a startup warning:
Client Connection¶
This example shows a client connection that includes client data:
Slow Operation¶
This example shows a slow operation message:
Escaping¶
This example demonstrates character escaping, as shown in the setName
field of the
attribute object: