SLF4J: Failed to load class org.slf4j.impl.StaticLoggerBinder

Quick fix

Read the commands before running them. Anything that restarts a service, deletes data or changes permissions should be tried on a non-production system first.

# Confirm the API version first: 1.7 uses bindings, 2.x uses providers
mvn dependency:tree -Dincludes=org.slf4j
./gradlew dependencies --configuration runtimeClasspath | grep slf4j

<!-- SLF4J 2.x with Logback -->
<dependency>
  <groupId>ch.qos.logback</groupId>
  <artifactId>logback-classic</artifactId>
  <version>1.5.18</version>
</dependency>

<!-- Or route SLF4J into Log4j 2 instead, never both -->
<!-- org.apache.logging.log4j:log4j-slf4j2-impl -->

# Two bindings is the other failure: SLF4J picks one at random and says so
# "Class path contains multiple SLF4J providers"
mvn dependency:tree | grep -E 'logback-classic|log4j-slf4j|slf4j-simple|slf4j-jdk14'

# A shaded or fat jar drops the service file that 2.x uses to find the provider,
# so keep META-INF/services intact in the shade plugin configuration

How to diagnose Logging errors

Logging failures are dangerous because they are silent: the application keeps running while its telemetry disappears. The recurring causes are buffer overflow under backpressure (the destination cannot keep up), permissions on log files or directories, and ingestion rate limits at the cloud provider. Monitoring the logging pipeline itself is the only reliable way to notice.

If the quick fix above does not resolve it, work through these steps. They apply to this whole class of error, not just to this one message, which is usually what saves the time.

1. Check the collector's own logs first: Fluentd, Logstash and the CloudWatch agent all log their own failures, usually to a separate destination.
2. Look for backpressure metrics: buffer queue length, retry counts, and dropped-record counters. A full buffer means the destination, not the collector, is the bottleneck.
3. Verify write permissions and disk space on the buffer path. A full disk silently stops most collectors.
4. For cloud ingestion, check the API rate limit for the log group or stream and batch more aggressively rather than retrying harder.
5. Add a heartbeat log line and alert on its absence. This is the only way to detect a pipeline that has stopped without erroring.

Tools worth reaching for

• collector self-logs
• buffer/queue metrics
• df -h
• aws logs describe-log-streams
• logger / fluent-cat for test events

Authoritative references

Primary documentation for this error, worth reading before applying any fix in production.

📖 slf4j.org 📖 slf4j.org

Related Logging errors

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• Fluentd: Buffer overflowFluentd's output buffer is full because the destination cannot accept data fast enough. Logs…
• journalctl: No journal files were foundjournald stores logs in memory when /var/log/journal does not exist, so everything is…
• Log4j: Appender not foundThe logging configuration references an appender that is not defined. The log4j2.xml or…
• log4j2: ERROR StatusLogger No Log4j 2 configuration file foundLog4j 2 could not find log4j2.xml on the classpath and fell back to logging errors only to…
• Logback: Failed to create log fileLogback cannot create or write to the log file due to filesystem permissions or the directory…
• logrotate: skipping because parent directory has insecure permissionslogrotate refuses to rotate a file in a directory that is group or world writable, because…
• Logstash: Pipeline errorA Logstash pipeline failed to start or process events, usually due to a bad grok pattern…

See all 12 Logging errors →

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Something missing or wrong?

This entry is maintained by hand. If the fix is out of date, incomplete, or you have a better one, email a correction and it will be reviewed.