- Log rotation
- Reopening log files
- Saving to multiple files
- Log filtering
- Transports and systemd
- Log to different streams
- Duplicate keys
- Log levels as labels instead of numbers
- Pino with
debug
- Unicode and Windows terminal
- Mapping Pino Log Levels to Google Cloud Logging (Stackdriver) Severity Levels
- Using Grafana Loki to evaluate pino logs in a kubernetes cluster
- Avoid Message Conflict
- Best performance for logging to
stdout
- Testing
Use a separate tool for log rotation:
We recommend logrotate.
Consider we output our logs to /var/log/myapp.log
like so:
$ node server.js > /var/log/myapp.log
We would rotate our log files with logrotate, by adding the following to /etc/logrotate.d/myapp
:
/var/log/myapp.log {
su root
daily
rotate 7
delaycompress
compress
notifempty
missingok
copytruncate
}
The copytruncate
configuration has a very slight possibility of lost log lines due
to a gap between copying and truncating - the truncate may occur after additional lines
have been written. To perform log rotation without copytruncate
, see the Reopening log files
help.
In cases where a log rotation tool doesn't offer copy-truncate capabilities,
or where using them is deemed inappropriate, pino.destination
can reopen file paths after a file has been moved away.
One way to use this is to set up a SIGUSR2
or SIGHUP
signal handler that
reopens the log file destination, making sure to write the process PID out
somewhere so the log rotation tool knows where to send the signal.
// write the process pid to a well known location for later
const fs = require('node:fs')
fs.writeFileSync('/var/run/myapp.pid', process.pid)
const dest = pino.destination('/log/file')
const logger = require('pino')(dest)
process.on('SIGHUP', () => dest.reopen())
The log rotation tool can then be configured to send this signal to the process after a log rotation event has occurred.
Given a similar scenario as in the Log rotation section a basic
logrotate
config that aligns with this strategy would look similar to the following:
/var/log/myapp.log {
su root
daily
rotate 7
delaycompress
compress
notifempty
missingok
postrotate
kill -HUP `cat /var/run/myapp.pid`
endscript
}
See pino.multistream
.
The Pino philosophy advocates common, preexisting, system utilities.
Some recommendations in line with this philosophy are:
- Use
grep
:$ # View all "INFO" level logs $ node app.js | grep '"level":30'
- Use
jq
:$ # View all "ERROR" level logs $ node app.js | jq 'select(.level == 50)'
systemd
makes it complicated to use pipes in services. One method for overcoming
this challenge is to use a subshell:
ExecStart=/bin/sh -c '/path/to/node app.js | pino-transport'
Pino's default log destination is the singular destination of stdout
. While
not recommended for performance reasons, multiple destinations can be targeted
by using pino.multistream
.
In this example, we use stderr
for error
level logs and stdout
as default
for all other levels (e.g. debug
, info
, and warn
).
const pino = require('pino')
var streams = [
{level: 'debug', stream: process.stdout},
{level: 'error', stream: process.stderr},
{level: 'fatal', stream: process.stderr}
]
const logger = pino({
name: 'my-app',
level: 'debug', // must be the lowest level of all streams
}, pino.multistream(streams))
Duplicate keys are possibly when a child logger logs an object with a key that collides with a key in the child loggers bindings.
See the child logger duplicate keys caveat for information on this is handled.
Pino log lines are meant to be parsable. Thus, Pino's default mode of operation
is to print the level value instead of the string name.
However, you can use the formatters
option
with a level
function to print the string name instead of the level value :
const pino = require('pino')
const log = pino({
formatters: {
level: (label) => {
return {
level: label
}
}
}
})
log.info('message')
// {"level":"info","time":1661632832200,"pid":18188,"hostname":"foo","msg":"message"}
Although it works, we recommend using one of these options instead if you are able:
- If the only change desired is the name then a transport can be used. One such
transport is
pino-text-level-transport
. - Use a prettifier like
pino-pretty
to make the logs human friendly.
The popular debug
is used in many modules across the ecosystem.
The pino-debug
module
can capture calls to debug
loggers and run them
through pino
instead. This results in a 10x (20x in asynchronous mode)
performance improvement - even though pino-debug
is logging additional
data and wrapping it in JSON.
To quickly enable this install pino-debug
and preload it with the -r
flag, enabling any debug
logs with the
DEBUG
environment variable:
$ npm i pino-debug
$ DEBUG=* node -r pino-debug app.js
pino-debug
also offers fine-grain control to map specific debug
namespaces to pino
log levels. See pino-debug
for more.
Pino uses sonic-boom to speed
up logging. Internally, it uses fs.write
to write log lines directly to a file
descriptor. On Windows, Unicode output is not handled properly in the
terminal (both cmd.exe
and PowerShell), and as such the output could
be visualized incorrectly if the log lines include utf8 characters. It
is possible to configure the terminal to visualize those characters
correctly with the use of chcp
by
executing in the terminal chcp 65001
. This is a known limitation of
Node.js.
Google Cloud Logging uses severity
levels instead of log levels. As a result, all logs may show as INFO
level logs while completely ignoring the level set in the pino log. Google Cloud Logging also prefers that
log data is present inside a message
key instead of the default msg
key that Pino uses. Use a technique
similar to the one below to retain log levels in Google Cloud Logging
const pino = require('pino')
// https://cloud.google.com/logging/docs/reference/v2/rest/v2/LogEntry#logseverity
const PinoLevelToSeverityLookup = {
trace: 'DEBUG',
debug: 'DEBUG',
info: 'INFO',
warn: 'WARNING',
error: 'ERROR',
fatal: 'CRITICAL',
};
const defaultPinoConf = {
messageKey: 'message',
formatters: {
level(label, number) {
return {
severity: PinoLevelToSeverityLookup[label] || PinoLevelToSeverityLookup['info'],
level: number,
}
}
},
}
module.exports = function createLogger(options) {
return pino(Object.assign({}, options, defaultPinoConf))
}
To get pino logs into Grafana Loki there are two options:
- Push: Use pino-loki to send logs directly to Loki.
- Pull: Configure Grafana Promtail to read and properly parse the logs before sending them to Loki.
Similar to Google Cloud logging, this involves remapping the log levels. See this article for details.
As described in the message
documentation, when a log
is written like log.info({ msg: 'a message' }, 'another message')
then the
final output JSON will have "msg":"another message"
and the 'a message'
string will be lost. To overcome this, the logMethod
hook
can be used:
'use strict'
const log = require('pino')({
level: 'debug',
hooks: {
logMethod (inputArgs, method) {
if (inputArgs.length === 2 && inputArgs[0].msg) {
inputArgs[0].originalMsg = inputArgs[0].msg
}
return method.apply(this, inputArgs)
}
}
})
log.info('no original message')
log.info({ msg: 'mapped to originalMsg' }, 'a message')
// {"level":30,"time":1596313323106,"pid":63739,"hostname":"foo","msg":"no original message"}
// {"level":30,"time":1596313323107,"pid":63739,"hostname":"foo","msg":"a message","originalMsg":"mapped to originalMsg"}
The best performance for logging directly to stdout is usually achieved by using the default configuration:
const log = require('pino')();
You should only have to configure custom transports or other settings if you have broader logging requirements.
See pino-test
.