APISIX Performance Tuning Guide

Introduction

Optimizing APISIX performance is crucial for handling high-traffic APIs efficiently. This guide covers essential tuning parameters, caching strategies, and monitoring techniques.

Prerequisites:

APISIX version 2.0 or higher
Basic understanding of NGINX configuration
Access to system resources monitoring

System-Level Optimization

Operating System Tuning

Optimize your system settings for better performance:

# /etc/sysctl.conf
net.core.somaxconn = 32768
net.ipv4.tcp_max_syn_backlog = 16384
net.core.netdev_max_backlog = 16384
net.ipv4.tcp_fastopen = 3
fs.file-max = 1000000

Worker Process Configuration

NGINX Worker Settings

# config.yaml
nginx_config:
  worker_processes: auto
  worker_connections: 10240
  worker_rlimit_nofile: 20480

2x-3x

Potential performance improvement with optimized worker settings

Caching Strategies

Response Caching

{
    "plugins": {
        "proxy-cache": {
            "cache_zone": "disk_cache_one",
            "cache_key": ["$host", "$request_uri"],
            "cache_bypass": ["$arg_bypass"],
            "cache_method": ["GET", "HEAD"],
            "cache_http_status": [200],
            "hide_cache_headers": true,
            "no_cache": ["$arg_no_cache"]
        }
    }
}

Connection Pooling

Upstream Connection Pool

{
    "upstream": {
        "nodes": {
            "127.0.0.1:80": 1
        },
        "type": "roundrobin",
        "keepalive_pool": {
            "size": 320,
            "idle_timeout": 60,
            "requests": 1000
        }
    }
}

Plugin Optimization

Plugin Configuration

Enable only necessary plugins
Optimize plugin execution order
Use lightweight authentication methods
Implement efficient rate limiting

{
    "plugins": {
        "limit-count": {
            "count": 2000,
            "time_window": 60,
            "rejected_code": 503,
            "key": "remote_addr"
        }
    }
}

Performance Monitoring

Metrics Collection

{
    "plugins": {
        "prometheus": {
            "prefer_name": true
        }
    }
}

Key metrics to monitor:

Request latency
Error rates
CPU and memory usage
Network I/O
Cache hit rates

Performance Troubleshooting

Common Issues and Solutions

Issue	Possible Cause	Solution
High Latency	Insufficient worker processes	Adjust worker_processes setting
Memory Leaks	Plugin memory management	Update plugins, adjust cache settings
CPU Spikes	Inefficient route matching	Optimize route configurations