Kibana Error: Request Timeout After 30000ms - Common Causes & Fixes

Brief Explanation

Kibana will show an error saying "Request Timeout After 30000ms" when a request to Elasticsearch takes longer than the default timeout of 30 seconds (30,000 milliseconds) to complete. This timeout is set to prevent long-running queries from consuming excessive resources.

Common Causes

1. Complex queries or aggregations that take too long to process
2. Large volumes of data being queried
3. Elasticsearch cluster performance issues
4. Network latency between Kibana and Elasticsearch
5. Insufficient resources (CPU, memory) on Elasticsearch nodes

Troubleshooting and Resolution Steps

1. Optimize your query:

   • Narrow down the time range of your search
   • Reduce the number of fields being queried
   • Simplify complex aggregations

2. Increase the request timeout:

   • In kibana.yml, add or modify: elasticsearch.requestTimeout: 60000
   • Restart Kibana after making changes

3. Check Elasticsearch performance:

   • Monitor CPU, memory, and disk usage on Elasticsearch nodes
   • Review Elasticsearch logs for any errors or warnings

4. Verify network connectivity:

   • Ensure there are no network issues between Kibana and Elasticsearch
   • Check for any firewall rules that might be causing delays

5. Scale your Elasticsearch cluster:

   • Add more nodes to distribute the load
   • Increase resources (CPU, RAM) on existing nodes

6. Review index patterns and mappings:

   • Ensure your index patterns are optimized
   • Check if field mappings are appropriate for your data types

7. Use the Query Profiler:

   • Analyze slow queries using Kibana's Query Profiler tool
   • Identify bottlenecks and optimize accordingly

Best Practices

• Regularly monitor and optimize your Elasticsearch cluster
• Implement index lifecycle management to handle large volumes of data
• Use appropriate shard sizes and replication factors
• Periodically review and optimize your Kibana dashboards and visualizations

Frequently Asked Questions

Q: Can increasing the request timeout solve all timeout issues?
A: While increasing the timeout can help with some queries, it's not a universal solution. It's important to address the root cause of slow queries through optimization and proper resource allocation.

Q: How can I identify which query is causing the timeout?
A: Use Kibana's Query Profiler or enable slow logs in Elasticsearch to identify problematic queries. You can also check Kibana and Elasticsearch logs for more details about the request that timed out.

Q: Will adding more Elasticsearch nodes always solve timeout issues?
A: Adding nodes can help distribute the load, but it's not always the solution. Sometimes, query optimization or data structure improvements are more effective in resolving timeout issues.

Q: Can index patterns affect query performance and lead to timeouts?
A: Yes, poorly designed index patterns can lead to inefficient queries. Ensure your index patterns match your data structure and query needs to optimize performance.

Q: How does the Elasticsearch cache impact query timeouts?
A: Elasticsearch uses various caches to improve performance. Properly warmed caches can significantly reduce query times. However, cache evictions due to memory pressure can lead to slower queries and potential timeouts.