this article outlines how to achieve site acceleration by deploying cdn and load balancing on vps in hong kong and singapore, key nodes in the asia-pacific. the article covers selection, deployment points, caching and ssl optimization, capacity estimation and monitoring methods, focusing on practical and executable steps to help engineers quickly implement and verify the effect.
the main reason for choosing to deploy in hong kong or singapore is that the two places are close to the traffic centers of southern china and southeast asia, which can significantly reduce the network latency on the client side. cooperate with < b> cdn to sink static resources to edge nodes, and distribute them to multiple < b > hong kong vps or < b > singapore vps back-end servers through < b > load balancing, which can improve concurrent processing capabilities, disaster recovery capabilities and cache hit rates, thereby reducing origin site bandwidth pressure and jitter.
when choosing, give priority to pops coverage (whether there are hong kong/singapore nodes), price, protocol support (http/2, http/3), cache control and log visibility. both public cloud cdns (such as cloudfront, gcp, alibaba cloud, tencent cloud) and commercial cdns (cloudflare, fastly) can be considered. in terms of load balancing, software layer solutions (nginx, haproxy) or cloud-hosted lb are optional. if you want to hide the origin ip and quickly enable global acceleration, it is recommended to prioritize the hybrid solution of cdn combined with cloud lb; if cost is sensitive, nginx+keepalived can be used to achieve basic high availability.
use smart resolution (geodns or cdn cname) at the dns layer to direct user traffic to the nearest edge node. cname the domain name to the domain name provided by the cdn. the cdn pulls the origin content (pull) from your hong kong vps or singapore vps or pushes it. pay attention to setting the origin site ip as whitelist access, or hiding the real ip through waf+acl to prevent bypassing edge nodes and directly attacking the origin site.
software solutions commonly use nginx or haproxy for reverse proxy and load balancing, and use keepalived to implement virtual ip drift (vrrp) to ensure active and standby switching. configuration points include: reasonable upstream weight, request timeout and retry strategy, session stickiness based on uri or cookie (if necessary), and active/passive health checks on the backend (http 200 check, slow query threshold). combined with system monitoring alarms, it can automatically go offline and trigger failover when a node is abnormal.
the caching strategy prioritizes static resources (images, js, css) and lowers the ttl (reasonably extend the ttl of static resources, use short ttl or no-cache for dynamic pages and cooperate with edge cache keys). use cache-control, etag and surrogate-key to facilitate granular cleanup. for ssl, it is recommended to terminate tls at the edge of the cdn to reduce the backend load, and at the same time enable two-way tls or origin verification between the edge and the origin site to ensure transmission security. enabling http/2 or http/3 with brotli compression can further reduce transmission latency.

the estimate is based on the peak number of concurrent connections and the average traffic per request: bandwidth (mbps) ≈ number of concurrencies × average bandwidth of a single connection (kb) × 8/1024. calculate the origin site bandwidth requirements based on the cache hit rate (for example, 70%-95%): origin site bandwidth = total traffic × (1-hit rate). the number of nodes is determined by disaster recovery requirements and geographical coverage. it is recommended to deploy at least two nodes across availability zones or across vps computer rooms, and reserve 30%-50% redundant capacity to cope with sudden traffic.
use the dashboard provided by cdn and lb to view traffic, cache hit rate, error rate, and latency. combined with independent tools (ping, traceroute, curl -i, webpagetest, gtmetrix) to compare ttl, ttfb, first packet delay, etc. before and after activation. compare real user monitoring (rum) data and compliance logs in different regions, and continue to optimize caching strategies and return-to-origin strategies until the desired latency and hit rate goals are achieved.
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