Logstash Error: Max inflight events reached - Common Causes & Fixes

Brief Explanation

The "Max inflight events reached" error in Logstash occurs when the number of events being processed simultaneously in a pipeline exceeds the configured maximum limit. This error is typically a sign of backpressure in the Logstash pipeline.

Impact

This error can significantly impact the performance and stability of your Logstash pipeline:

• Event processing may slow down or stall
• Increased memory usage and potential out-of-memory errors
• Potential data loss if input buffers overflow

Common Causes

1. Insufficient resources (CPU, memory) for the current workload
2. Slow or unresponsive output destinations
3. Complex or inefficient filter configurations
4. Mismatched input and output throughput capacities
5. Inadequate pipeline worker settings

Troubleshooting and Resolution Steps

1. Check system resources: Monitor CPU and memory usage to ensure Logstash has sufficient resources.

2. Review pipeline configuration:

   • Optimize filter plugins for efficiency
   • Ensure output destinations can handle the incoming event rate

3. Adjust pipeline settings:

   • Increase pipeline.workers if resources allow
   • Tune pipeline.batch.size and pipeline.batch.delay

4. Enable persistent queues:

   • Configure persistent queues to handle backpressure
   • Adjust queue settings like queue.type: persisted and queue.max_bytes

5. Scale horizontally:

   • Consider distributing the workload across multiple Logstash instances

6. Monitor and tune outputs:

   • Ensure output plugins are configured optimally
   • Check if output destinations are responsive and can handle the load

7. Use the Logstash monitoring API:

   • Monitor pipeline metrics to identify bottlenecks

Best Practices

• Regularly monitor Logstash performance and adjust configurations as needed
• Implement a robust monitoring solution for your Logstash deployment
• Use Logstash's persistent queue feature for better resilience against backpressure
• Consider implementing a buffer (like Redis or Kafka) between your data source and Logstash for high-volume scenarios

Frequently Asked Questions

Q: How can I determine the current number of inflight events?
A: You can use the Logstash monitoring API to check the pipeline.events.in_flight metric, which shows the current number of events being processed in the pipeline.

Q: What's the default max inflight events limit in Logstash?
A: The default limit is typically calculated based on the pipeline.workers and pipeline.batch.size settings. It's usually pipeline.workers * pipeline.batch.size * 1.5.

Q: Can increasing pipeline.workers always solve this error?
A: Not always. While increasing workers can help, it also increases resource usage. It's important to balance this with available system resources and identify the actual bottleneck in your pipeline.

Q: How do persistent queues help with this error?
A: Persistent queues act as a buffer, allowing Logstash to handle temporary spikes in event flow and backpressure from outputs, reducing the likelihood of reaching the max inflight events limit.

Q: Is it possible to dynamically adjust the max inflight events limit?
A: The limit is not directly configurable, but you can influence it by adjusting pipeline.workers and pipeline.batch.size. These changes typically require a Logstash restart to take effect.