Kibana Maximum Call Stack Size Exceeded Error - Common Causes & Fixes

Brief Explanation

The "Max Call Stack Size Exceeded" error in Kibana occurs when the JavaScript engine reaches its maximum call stack size. This typically happens due to excessive recursion or deeply nested function calls, causing the program to terminate unexpectedly.

Common Causes

1. Complex or poorly optimized Kibana queries
2. Large datasets causing excessive recursion in data processing
3. Plugins or custom scripts with inefficient code
4. Insufficient memory allocation for Kibana
5. Outdated or incompatible Kibana version

Troubleshooting and Resolution Steps

1. Optimize Queries:

   • Simplify complex queries
   • Use appropriate time ranges and filters
   • Avoid nested aggregations where possible

2. Increase Node.js Memory Limit:

   • Set the --max-old-space-size flag to a higher value
   • Example: node --max-old-space-size=4096 /path/to/kibana/src/cli/cli.js

3. Update Kibana:

   • Ensure you're using the latest compatible version of Kibana

4. Check and Optimize Custom Code:

   • Review any custom plugins or scripts for inefficiencies
   • Implement pagination or lazy loading for large datasets

5. Adjust Browser Settings:

   • Increase browser memory allocation (if applicable)
   • Clear browser cache and cookies

6. Monitor System Resources:

   • Ensure sufficient CPU and RAM are available for Kibana

7. Review Elasticsearch Settings:

   • Check if Elasticsearch is properly configured to handle the data volume

Best Practices

• Regularly monitor Kibana and Elasticsearch performance
• Implement data lifecycle management to prevent excessive data accumulation
• Use Kibana's built-in performance optimization tools
• Keep Kibana and Elasticsearch versions in sync and up-to-date

Frequently Asked Questions

Q: Can increasing Node.js memory always solve this error?
A: While increasing memory can help in many cases, it's not always the solution. The root cause might be inefficient queries or code that need optimization.

Q: How does this error affect Kibana's overall performance?
A: This error can significantly degrade Kibana's performance, causing slow load times, failed queries, and potential crashes of the Kibana service.

Q: Are there any Kibana settings to prevent this error?
A: While there's no specific setting to prevent this error, optimizing query timeout settings, adjusting index patterns, and using appropriate date ranges can help mitigate the risk.

Q: Can this error be caused by Elasticsearch issues?
A: Yes, Elasticsearch configuration or performance issues can indirectly lead to this error in Kibana, especially with large datasets or complex queries.

Q: How can I identify which query or visualization is causing this error?
A: Check Kibana and browser console logs for error details. You can also try loading visualizations and dashboards individually to isolate the problematic component.