Managing CPU Load in Confluence Data Center

High CPU utilization across your Confluence Data Center nodes can significantly impact system responsiveness and user experience. This insight appears when processor utilization exceeds the recommended threshold of 70%.

How does high CPU load affect Confluence Data Center performance?

When CPU load remains consistently high, users experience several critical impacts:

• Extended response times affect daily operations, causing slower page loading and delayed space operations like imports and exports.

• Background tasks, including indexing and scheduled jobs, take longer to complete.

• Your cluster may also experience degraded synchronization and increased latency for API calls and integrations.

What's the recommendation?

Monitor and analyze CPU trends

Regular monitoring helps identify patterns and potential issues:

1. Review current status:

   • Go to Administration > System Information

   • Check CPU usage graphs for each node

   • Identify usage patterns and spikes

2. Set up monitoring:

   • Configure alerts for high utilization

   • Track historical trends

   • Monitor peak usage periods

   • Review node-specific metrics

More about best practices for performance

Optimize cluster configuration

Ensure efficient resource utilization across your cluster:

1. Load balancer settings:

   • Review traffic distribution

   • Verify session affinity

   • Configure health checks

   • Implement weighted balancing if needed

2. Resource allocation:

   • Maintain consistent node specifications

   • Consider dedicated nodes for specific tasks

   • Optimize thread pool settings

   • Review memory allocation

More about Data Center infrastructure recommendations

Investigate high-CPU processes

Generate diagnostic information to identify resource-intensive operations:

• Navigate to Administration > Troubleshooting and Support

• Create a Support Zip with thread dumps enabled

• Include runtime diagnostics for comprehensive analysis

Pay special attention to these common CPU-intensive operations:
• Space exports and imports
• PDF generation tasks
• Search indexing operations
• Backup processes
• Resource-heavy app activities

Implement preventive measures

Maintain optimal performance through regular maintenance:

• Schedule resource-intensive tasks during off-peak hours

• Monitor and optimize app performance regularly

• Review and adjust backup timing

• Maintain efficient search indexes

Plan for growth by:

• Tracking usage trends

• Planning infrastructure scaling

• Reviewing resource allocation quarterly

• Monitoring user pattern changes

Create support ticket

If issues persist after implementing these recommendations:

1. Collect the following information:

   • Support zip with thread dumps

   • CPU usage patterns

   • Recent configuration changes

   • Node-specific metrics

2. Create a support ticket with the collected information