This document discusses the concept of structured logging and the methods for
adding structure to log entry payload fields. When the log payload is formatted
as a JSON object and that object is stored in the jsonPayload
field, the log
entry is called a structured log. For these logs, you can construct queries
that search specific JSON paths and you can index specific fields in the
log payload. In contrast, when the log payload is formatted as a string and
stored in the textPayload
field, the log entry is unstructured.
You can search the text field, but you can't index its content.
To create structured log entries, do any of the following:
- Call the
entries.write
API method and supply a fully formattedLogEntry
. - Use the
gcloud logging write
command.
- Use a Cloud Logging client library which writes structured logs.
- Use the BindPlane service.
Use an agent to write logs:
Some Google Cloud services contain an integrated logging agent that sends the data written to
stdout
orstderr
as logs to Cloud Logging. You can use this approach for Google Cloud services such as Google Kubernetes Engine, App Engine flexible environment, and Cloud Run functions.For Compute Engine virtual machines (VMs), you can install and configure the Ops Agent or the legacy Logging agent, and then use the installed agent to send logs to Cloud Logging.
For more information about these approaches, see the following sections.
Write logs by using client libraries or the API
You can write log data by using the
Cloud Logging client libraries, which
call the Cloud Logging API, or by directly calling the Cloud Logging API.
Client libraries can simplify population of the special JSON fields by
automatically capturing some information and by providing interfaces to
appropriately populate the fields. However, for full control over the
structure of your payloads, directly call the Cloud Logging API and pass the
full LogEntry
structure to the Cloud Logging API.
For more information, see the entries.write
reference.
For code examples, see Writing structured logs.
Write logs by using the gcloud CLI
You can write log data by using the gcloud CLI. The interface supports unstructured logs and structured logs. When you want to write a structured log, provide the command a serialized JSON object.
For a quickstart, see Write and query log entries with the Google Cloud CLI.
For code examples, see the
gcloud logging write
reference.
Write logs by using BindPlane
You can use the BindPlane service to send logs to Logging. For these logs, the payloads are in JSON format and are structured according to the source system. For information on finding and viewing logs ingested by using BindPlane, see the BindPlane Quickstart Guide.
Write logs by using an agent
To get logs from your Compute Engine instances, you can use the Ops Agent or the legacy Cloud Logging agent. Both agents can collect metrics from third-party applications, and both provide support for structured logging:
The Ops Agent is the recommended agent for collecting telemetry from your Compute Engine instances. This agent combines logging and metrics into a single agent, provides a YAML-based configuration, and features high-throughput logging.
For information about how to configure the Ops Agent to support structured logging or to customize the form of a structured log, see Configure the Ops Agent.
The legacy Cloud Logging agent collects logs. This agent doesn't collect other forms of telemetry.
The remainder of this section is specific to the legacy Logging agent.
Logging agent: special JSON fields
Some fields in the JSON object are recognized as special by the
legacy Logging agent and extracted into the
LogEntry
structure. These special JSON fields can be used to set
the following fields in the LogEntry
:
severity
spanId
labels
defined by the userhttpRequest
Because JSON is more precise and versatile than text lines, you can use JSON objects to write multiline messages and add metadata.
To create structured log entries for your applications using the simplified format, see the following table, which lists the fields and their values in JSON:
JSON log field |
LogEntry
field
|
Cloud Logging agent function | Example value |
---|---|---|---|
severity
|
severity
|
The Logging agent attempts to match a variety of common severity strings, which includes the list of LogSeverity strings recognized by the Logging API. | "severity":"ERROR"
|
message
|
textPayload
(or part of
jsonPayload )
|
The message that appears on the log entry line in the Logs Explorer. | "message":"There was an error in the application." Note: message is saved as textPayload if it is the
only field remaining after the Logging
agent moves the other special-purpose fields and
detect_json wasn't enabled; otherwise message
remains in jsonPayload . detect_json is not applicable to managed
logging environments like Google Kubernetes Engine. If your log entry contains an
exception stack trace, the exception stack trace should
be set in this message JSON log field, so that the exception
stack trace can be parsed and saved to Error Reporting. |
log
(legacy
Google Kubernetes Engine
only) |
textPayload
|
Only applies to legacy Google Kubernetes Engine:
if, after moving special purpose
fields, only a log field remains, then
that field is saved as textPayload . |
|
httpRequest
|
httpRequest
|
A structured record in the format
of the LogEntry
HttpRequest field. |
"httpRequest":{"requestMethod":"GET"}
|
time-related fields | timestamp
|
For more information, see Time-related fields. | "time":"2020-10-12T07:20:50.52Z"
|
logging.googleapis.com/insertId
|
insertId
|
For more information,
see insertId
on the LogEntry page. |
"logging.googleapis.com/insertId":"42"
|
logging.googleapis.com/labels
|
labels
|
The value of this field
must be a structured record.
For more information, see
labels on
the LogEntry page. |
"logging.googleapis.com/labels":
{"user_label_1":"value_1","user_label_2":"value_2"}
|
logging.googleapis.com/operation
|
operation
|
The value of this field
is also used by
the Logs Explorer to
group related log entries.
For more information,
see operation on
the LogEntry page. |
"logging.googleapis.com/operation":
{"id":"get_data","producer":"github.com/MyProject/MyApplication",
"first":"true"}
|
logging.googleapis.com/sourceLocation
|
sourceLocation
|
Source code location
information associated
with the log entry,
if any.
For more information,
see LogEntrySourceLocation
on the LogEntry page. |
"logging.googleapis.com/sourceLocation":
{"file":"get_data.py","line":"142","function":"getData"}
|
logging.googleapis.com/spanId
|
spanId
|
The span ID within the
trace associated with
the log entry.
For more information,
see spanId
on the LogEntry page. |
"logging.googleapis.com/spanId":"000000000000004a"
|
logging.googleapis.com/trace
|
trace
|
Resource name of the trace
associated with
the log entry
if any.
For more information,
see trace
on the LogEntry page.
|
"logging.googleapis.com/trace":"projects/my-projectid/traces/0679686673a" Note: If not writing to stdout or stderr ,
the value of this field should be formatted as
projects/[PROJECT-ID]/traces/[TRACE-ID] ,
so it can be used by the Logs Explorer and
the Trace Viewer to group log entries
and display them in line with traces.
If autoformat_stackdriver_trace is true and
[V] matches the format of ResourceTrace
traceId the LogEntry trace field has the value
projects/[PROJECT-ID]/traces/[V] . |
logging.googleapis.com/trace_sampled
|
traceSampled
|
The value of this field
must be either true or
false .
For more information,
see traceSampled
on the LogEntry page. |
"logging.googleapis.com/trace_sampled": false
|
To create log entries in the simplified format, create a JSON representation of the entry using the fields. All of the fields are optional.
The following is an example of a simplified JSON log entry:
{ "severity":"ERROR", "message":"There was an error in the application.", "httpRequest":{ "requestMethod":"GET" }, "times":"2020-10-12T07:20:50.52Z", "logging.googleapis.com/insertId":"42", "logging.googleapis.com/labels":{ "user_label_1":"value_1", "user_label_2":"value_2" }, "logging.googleapis.com/operation":{ "id":"get_data", "producer":"github.com/MyProject/MyApplication", "first":"true" }, "logging.googleapis.com/sourceLocation":{ "file":"get_data.py", "line":"142", "function":"getData" }, "logging.googleapis.com/spanId":"000000000000004a", "logging.googleapis.com/trace":"projects/my-projectid/traces/06796866738c859f2f19b7cfb3214824", "logging.googleapis.com/trace_sampled":false }
The following is an example of the resulting log entry:
{ "insertId": "42", "jsonPayload": { "message": "There was an error in the application", "times": "2020-10-12T07:20:50.52Z" }, "httpRequest": { "requestMethod": "GET" }, "resource": { "type": "k8s_container", "labels": { "container_name": "hello-app", "pod_name": "helloworld-gke-6cfd6f4599-9wff8", "project_id": "stackdriver-sandbox-92334288", "namespace_name": "default", "location": "us-west4", "cluster_name": "helloworld-gke" } }, "timestamp": "2020-11-07T15:57:35.945508391Z", "severity": "ERROR", "labels": { "user_label_2": "value_2", "user_label_1": "value_1" }, "logName": "projects/stackdriver-sandbox-92334288/logs/stdout", "operation": { "id": "get_data", "producer": "github.com/MyProject/MyApplication", "first": true }, "trace": "projects/my-projectid/traces/06796866738c859f2f19b7cfb3214824", "sourceLocation": { "file": "get_data.py", "line": "142", "function": "getData" }, "receiveTimestamp": "2020-11-07T15:57:42.411414059Z", "spanId": "000000000000004a" }
Logging agent: configuration
The legacy Logging agent, google-fluentd
, is a
Cloud Logging-specific packaging of the
Fluentd log data collector.
The Logging agent comes with the default Fluentd configuration
and uses Fluentd input plugins to pull event logs from external sources
such as files on disk, or to parse incoming log records.
Fluentd has a list of supported parsers that extract logs and convert them into structured (JSON) payloads.
By configuring a log source with format [PARSER_NAME]
, you can build on the
built-in parsers provided by Fluentd. For information about configuring the
legacy Logging agent, see
Configure the Logging agent.
The following code samples show the Fluentd configuration, the input log record, and the output structured payload, which is part of a Cloud Logging log entry:
Fluentd configuration:
<source> @type tail format syslog # This uses a predefined log format regex named # `syslog`. See details at https://docs.fluentd.org/parser/syslog. path /var/log/syslog pos_file /var/lib/google-fluentd/pos/syslog.pos read_from_head true tag syslog </source>
Log record (input):
<6>Feb 28 12:00:00 192.168.0.1 fluentd[11111]: [error] Syslog test
Structured payload (output):
jsonPayload: { "pri": "6", "host": "192.168.0.1", "ident": "fluentd", "pid": "11111", "message": "[error] Syslog test" }
For more information about how the syslog
parser works, see the detailed
Fluentd documentation.
Logging agent: standard parsers enabled by default
The following table includes the standard parsers that are included in the agent if you enable structured logging:
Parser Name | Configuration file |
---|---|
syslog |
/etc/google-fluentd/config.d/syslog.conf |
nginx |
/etc/google-fluentd/config.d/nginx.conf |
apache2 |
/etc/google-fluentd/config.d/apache.conf |
apache_error |
/etc/google-fluentd/config.d/apache.conf |
For instructions on enabling structured logging when installing the legacy Logging agent, see the Installation section.
Logging agent: installation
To enable structured logging, you must change the default configuration of the legacy Logging agent when installing or reinstalling it. Enabling structured logging replaces the previously listed configuration files but doesn't change the operation of the agent itself.
When you enable structured logging, the listed logs are converted to log entries with different formats than they had before you enabled structured logs. If the logs are being routed to destinations outside of Logging, the change could affect any post-processing applications. For example, if routing logs to BigQuery, BigQuery rejects the new log entries for the remainder of the day as having an incorrect schema.
For instructions on installing the legacy Logging agent and enabling structured logging, refer to Installing the Logging agent.
You can find the legacy Logging agent configuration files at
/etc/google-fluentd/config.d/
, which should now include the
Standard parsers enabled by default.
Logging agent: configure Apache access log format
By default, the legacy Logging agent stores Apache access
log data in the jsonPayload
field. For example:
{
"logName": ...,
"resource": ...,
"httpRequest": ...,
"jsonPayload": {
"user" : "some-user",
"method" : "GET",
"code" : 200,
"size" : 777,
"host" : "192.168.0.1",
"path" : "/some-path",
"referer": "some-referer",
"agent" : "Opera/12.0"
},
...
}
Alternatively, you can configure the legacy Logging agent to
extract certain fields to the httpRequest
field. For example:
{
"logName": ...,
"resource": ...,
"httpRequest": {
"requestMethod": "GET",
"requestUrl": "/some-path",
"requestSize": "777",
"status": "200",
"userAgent": "Opera/12.0",
"serverIp": "192.168.0.1",
"referrer":"some-referrer",
},
"jsonPayload": {
"user":"some-user"
},
...
}
Configuring the httpRequest
field, as shown in the prior sample, assists
tracing: the Google Cloud console presents all logs for a given HTTP request
in a parent-child hierarchy.
To configure this extraction, add the following to the end of your
/etc/google-fluentd/config.d/apache.conf
:
<filter apache-access>
@type record_transformer
enable_ruby true
<record>
httpRequest ${ {"requestMethod" => record['method'], "requestUrl" => record['path'], "requestSize" => record['size'], "status" => record['code'], "userAgent" => record['agent'], "serverIp" => record['host'],
"referer" => record['referer']} }
</record>
remove_keys method, path, size, code, agent, host, referer
</filter>
For more details on how to configure your log entries, see Modifying log records.
Logging agent: configure nginx access log format
By default, the legacy Logging agent stores nginx access
log data in the jsonPayload
field. For example:
{
"logName": ...,
"resource": ...,
"httpRequest": ...,
"jsonPayload": {
"remote":"127.0.0.1",
"host":"192.168.0.1",
"user":"some-user",
"method":"GET",
"path":"/some-path",
"code":"200",
"size":"777",
"referrer":"some-referrer",
"agent":"Opera/12.0",
"http_x_forwarded_for":"192.168.3.3"
},
...
}
Alternatively, you can configure the legacy Logging agent to
extract certain fields to the httpRequest
field. For example:
{
"logName": ...,
"resource": ...,
"httpRequest": {
"requestMethod": "GET",
"requestUrl": "/some-path",
"requestSize": "777",
"status": "200",
"userAgent": "Opera/12.0",
"remoteIp": "127.0.0.1",
"serverIp": "192.168.0.1",
"referrer":"some-referrer",
},
"jsonPayload": {
"user":"some-user",
"http_x_forwarded_for":"192.168.3.3"
},
...
}
Configuring the httpRequest
field, as shown in the prior sample, assists
tracing: the Google Cloud console presents all logs for a given HTTP request
in a parent-child hierarchy.
To configure this extraction, add the following to the end of your
/etc/google-fluentd/config.d/nginx.conf
:
<filter nginx-access>
@type record_transformer
enable_ruby true
<record>
httpRequest ${ {"requestMethod" => record['method'], "requestUrl" => record['path'], "requestSize" => record['size'], "status" => record['code'], "userAgent" => record['agent'], "remoteIp" => record['remote'], "serverIp" => record['host'], "referer" => record['referer']} }
</record>
remove_keys method, path, size, code, agent, remote, host, referer
</filter>
For more details on how to configure your log entries, see Modifying log records.
Write your own parser
If your logs aren't supported by the standard parsers, you can write your own parser. Parsers consist of a regular expression that is used to match log records and apply labels to the pieces.
The following code examples show a log line in the log record, a configuration with a regular expression that indicates the format of the log line, and the stored log entry:
A log line in the log record:
REPAIR CAR $500
A configuration with a regular expression that indicates the format of the log line:
$ sudo vim /etc/google-fluentd/config.d/test-structured-log.conf $ cat /etc/google-fluentd/config.d/test-structured-log.conf <source> @type tail # Format indicates the log should be translated from text to # structured (JSON) with three fields, "action", "thing" and "cost", # using the following regex: format /(?<action>\w+) (?<thing>\w+) \$(?<cost>\d+)/ # The path of the log file. path /tmp/test-structured-log.log # The path of the position file that records where in the log file # we have processed already. This is useful when the agent # restarts. pos_file /var/lib/google-fluentd/pos/test-structured-log.pos read_from_head true # The log tag for this log input. tag structured-log </source>
The resulting log entry:
{ insertId: "eps2n7g1hq99qp" jsonPayload: { "action": "REPAIR" "thing": "CAR" "cost": "500" } labels: { compute.googleapis.com/resource_name: "add-structured-log-resource" } logName: "projects/my-sample-project-12345/logs/structured-log" receiveTimestamp: "2023-03-21T01:47:11.475065313Z" resource: { labels: { instance_id: "3914079432219560274" project_id: "my-sample-project-12345" zone: "us-central1-c" } type: "gce_instance" } timestamp: "2023-03-21T01:47:05.051902169Z" }
Troubleshoot issues
To troubleshoot common issues found with installing or interacting with the legacy Logging agent, see Troubleshooting the agent.
What's next
To query and view log entries, see View logs by using the Logs Explorer.
To read log entries using the Google Cloud CLI, see Reading log entries.
To read log entries using the Logging API, see the
entries.list
method.