Overview
Get WuKongIM system runtime variables and performance metrics for system monitoring and performance analysis.Query Parameters
Sort field
in_msgs- Sort by received message countout_msgs- Sort by sent message countin_bytes- Sort by received bytesout_bytes- Sort by sent bytes
Connection information limit count
Specify node ID (cluster environment)
Response Fields
Server Information
Server identifier
WuKongIM version number
Git commit hash
Go language version
Runtime Information
Server start time (ISO 8601 format)
Current time (ISO 8601 format)
Runtime duration
Connection Statistics
Current connection count
Total connections (historical cumulative)
Number of slow consumers
Total subscriptions
Message Statistics
Total received messages
Total sent messages
Total received bytes
Total sent bytes
HTTP Request Statistics
HTTP request statistics
System Resources
CPU usage (percentage)
Memory usage (bytes)
Configuration Information
System configuration information
Status Codes
| Status Code | Description |
|---|---|
| 200 | Successfully retrieved system variables |
| 500 | Internal server error |
Monitoring Metrics Description
Performance Metrics
| Metric | Description | Normal Range | Alert Threshold |
|---|---|---|---|
| CPU Usage | Server CPU utilization percentage | < 70% | > 80% |
| Memory Usage | Server memory consumption | < 80% | > 90% |
| Connections | Current active connections | Based on config | Near maximum |
| Slow Consumers | Number of slow processing connections | < 5% | > 10% |
Throughput Metrics
| Metric | Description | Monitoring Focus |
|---|---|---|
| Message Receive Rate | Messages received per second | Sudden increases or decreases |
| Message Send Rate | Messages sent per second | Ratio to receive rate |
| Byte Transfer Rate | Network transfer speed | Bandwidth usage |
| HTTP Request Stats | API call frequency and response time | Hot APIs and performance bottlenecks |
Best Practices
- Regular Monitoring: Recommended to get system variables every 30-60 seconds
- Alert Setup: Set reasonable alert thresholds for key metrics
- Trend Analysis: Record historical data to analyze system performance trends
- Capacity Planning: Perform capacity planning based on monitoring data
- Performance Optimization: Identify performance bottlenecks and optimize
- Cluster Monitoring: Monitor all node status in cluster environments

