Cloud Computing 12 min read

How CDN and Global Load Balancing Accelerate Web Performance

This article explains the fundamentals of Content Delivery Networks (CDN), their caching and load‑balancing mechanisms, the value they bring to network traffic, and how Global Server Load Balancing (GSLB) techniques—based on DNS, HTTP redirects, and IP spoofing—select optimal server groups using geographic, load, and RTT strategies.

MaGe Linux Operations
MaGe Linux Operations
MaGe Linux Operations
How CDN and Global Load Balancing Accelerate Web Performance

CDN Overview

CDN (Content Delivery Network) is an intelligent virtual network built on existing Internet infrastructure. By deploying edge servers worldwide and using centralized load balancing, content distribution, and scheduling modules, users can retrieve data from nearby servers, reducing congestion, latency, and improving hit rates.

CDN Principle

The core principle relies on widespread cache servers placed in regions where users concentrate. Global load balancing directs user requests to the nearest healthy cache server, which serves the content directly, avoiding bottlenecks and ensuring faster, more stable delivery.

Global load balancing enables sites with servers in multiple regions to be accessed via a single IP or domain, routing users to the nearest server for optimal speed.

CDN Value

Reduces backbone bandwidth demand.

Provides server‑side acceleration, preventing overload from high traffic.

Uses web cache to serve repeated objects locally, saving upstream bandwidth and improving response time.

Mitigates uneven site distribution and lowers construction and maintenance costs.

Lessens the impact of traffic storms, enhancing network stability.

CDN Service Model

A CDN consists of distributed storage, load balancing, request redirection, and content management, with content management and traffic management being core components. By evaluating user proximity and server load, the CDN routes requests to the most efficient edge node.

Global Server Load Balancing (GSLB)

GSLB balances traffic across server groups located in different geographic areas, ensuring users reach the nearest server via a single IP or domain.

GSLB Based on DNS

DNS resolution may involve multiple queries. A GSLB device can replace the DNS server, returning the IP of the optimal server group. Advantages: simple implementation and low cost. Disadvantages: inaccurate proximity decisions when the user’s DNS resolver does not reflect the actual user location.

GSLB Based on HTTP Redirect

After DNS resolves the GSLB device’s IP, the device receives the HTTP request, selects the best server, and issues an HTTP 302 redirect with the chosen server’s IP. This captures the user’s real IP, solving DNS‑based inaccuracy, but works only for HTTP traffic.

GSLB Based on IP Spoofing (Triangular Routing)

For non‑HTTP protocols, the GSLB device forwards the request to the selected server, which replies with its source IP rewritten to the GSLB device’s IP. Users see only the GSLB device, unaware of the intermediate routing. This method supports all protocols but adds extra hops, reducing efficiency.

Server Group Selection Strategies

Common strategies include:

Geographic or custom user regions: map IP prefixes to regions and assign users to healthy sites based on their DNS resolver IP.

IP address weighting: assign traffic weights to each server IP.

Round‑Trip Time (RTT): choose the server with the lowest RTT, measured actively (via DNS/ICMP) or passively (observing TCP SYN‑ACK timing). Passive RTT reflects actual user experience without extra traffic.

These strategies guide GSLB in directing users to the most suitable server group, optimizing performance and reliability.

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CDNnetwork optimizationContent Delivery NetworkGSLBGlobal Load Balancing
MaGe Linux Operations
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MaGe Linux Operations

Founded in 2009, MaGe Education is a top Chinese high‑end IT training brand. Its graduates earn 12K+ RMB salaries, and the school has trained tens of thousands of students. It offers high‑pay courses in Linux cloud operations, Python full‑stack, automation, data analysis, AI, and Go high‑concurrency architecture. Thanks to quality courses and a solid reputation, it has talent partnerships with numerous internet firms.

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