Under the digital wave, CDN is the core technology to ensure the user access speed and experience, but many enterprises will still have the transmission speed is not up to expectations after deploying CDN. The following is to share how to use scientific means to maximize CDN transmission efficiency from technical principles, strategy optimization and practical skills.

1. the underlying logic and bottleneck analysis of CDN acceleration

The essence of CDN is to cache content through distributed nodes to enable users to obtain data nearby. Its core performance indicators include cache hit ratio, delay time, and bandwidth utilization. The bottleneck of transmission speed is often caused by the following scenarios: Node coverage is insufficient. If the CDN node does not cover the user dense area, the request still needs to be sent back across the region, resulting in high latency; When the cache policy fails, static resources are not fully cached or dynamic content is not processed properly. As a result, data is frequently pulled back to the source and bandwidth pressure is increased. Protocol and compression defects: Efficient protocols such as HTTP/2 and QUIC are not enabled, or transmitted content is not compressed, resulting in resource waste; Network path redundancy In the absence of intelligent routing scheduling, packets pass through multiple inefficient transit nodes, extending the transmission path.

2. Key optimization strategy and implementation path

Refined cache management. Caching is the cornerstone of CDN performance. Optimization needs to start from two aspects:

Static resource caching. Set a long cache time (such as 30 days) for images, CSS, JS and other files, and configure a mandatory cache policy using Nginx:

nginx  
location ~ \.(jpg|css|js)$ {  
expires 30d;  
add_header CacheControl "public";  
}

This configuration reduces repeated requests by more than 80%.

Dynamic content processing. For dynamic requests such as apis, edge computing technology (such as Cloudflare Workers) is used to process part of the logic near the node, reducing the number of back to the source.

Path optimization uses BGP Anycast technology to dynamically select the optimal node. For example, when a user visits from Hong Kong and is automatically assigned to the Shenzhen node instead of the US source station, the latency can be reduced from 200ms to 30ms. The load balancing algorithm adjusts weight allocation based on real-time traffic. The following Python example implements dynamic traffic scheduling:

python  
def select_node(nodes):  

Select the optimal node based on node load, latency, and bandwidth

return min(nodes, key=lambda x: x.locad 0.6 + x.locency 0.4)

This algorithm can improve the request response speed by 15%.

Enable HTTP/3 (QUIC) : Compared to TCP, QUIC reduces handshake latency and supports multiplexing, especially for networks with high packet loss rates. Tests have shown that video streaming with QUIC enabled reduces buffering time by 50%. Gzip/Brotli compression: Enable Brotli compression for text resources (20% more efficient than Gzip) with the following Nginx configuration:

nginx  
gzip on;  
gzip_types text/plain application/json;  
brotli on;  
brotli_types text/html application/javascript;  

The solution can reduce the amount of data transfer by 70%.

CDN performance is strongly related to the source station. The optimization measures include database query optimization, which reduces the query time from 500ms to 50ms through index optimization and sub-database and sub-table; The CDN mirroring function is used to asynchronously synchronize data from the source station to the edge node, avoiding direct return to the source.

Multi-cdn strategy and fault disaster recovery are selected to complement the coverage of CDN service providers in the supplier portfolio, and improve the quality of global coverage through DNS subregional resolution. Automatic switchover When the active CDN fails, the Anycast DNS or a third-party service (such as Cedexis) is used to automatically switch to the standby link, ensuring an SLA of 99.99%.

The optimization of CDN transmission speed is long-term and requires full-link coordination from protocol, cache, routing to the source station. With scientific strategy design and real-time monitoring, enterprises can improve user experience and obtain more opportunities in digital competition.