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Hong Kong Cloud Server
1.
overview and selection background
- hong kong vps is often used to reduce domestic access delays, act as a transit agent, and overseas acceleration and distribution.- when choosing proxy software, you need to weigh the operating system (windows/linux), concurrent connections, protocol support (http/socks/https), ease of use and authorization.
- ccproxy is a visual proxy software on the windows platform. it is easy to configure and suitable for internal deployment and authentication management.
- squid/3proxy, etc. are common high-performance transparent proxy/forward proxy solutions under linux, suitable for traffic forwarding and caching scenarios.
- shadowsocks/v2ray prefers encrypted tunneling and wall penetration technology, and performs well in high-concurrency and lightweight forwarding scenarios.
- domain name resolution, cdn caching strategy, upstream bandwidth and provider's ddos protection capabilities must also be considered.
2.
test environment and methods
- test platform: a hong kong vps , specification example: 2 vcpu (intel xeon), 4gb ram, 80gb nvme, public network port 1gbps. operating system: windows server 2019 (ccproxy) and ubuntu 20.04 (squid/3proxy/shadowsocks).- testing tools: iperf3 (bandwidth test), ab/hey (concurrent requests), tcpdump (packet capture), wrk (persistent connection stress test).
- test scenario: single client to proxy concurrent 100/500/1000 connections, http get large/small files, tcp tunnel throughput and delay measurement.
- test indicators: throughput (mbps), cpu usage %, memory usage (mb), concurrent connection stability, packet loss rate and average delay (ms).
- the delay from the test network to domestic nodes and the delay to us nodes are recorded separately to evaluate the transit effect.
- external pressure (such as a short-term trigger of 100,000 concurrent connections) is also used in the test to observe the behavior of the software and vps under high load.
3.
actual performance of ccproxy in hong kong vps
- environment: windows server 2019, ccproxy 8.x, 2 vcpu/4gb, tested with 100 concurrent connections.- throughput: average 170 mbps (continuous download of large files), average cpu usage of about 25%, memory usage of about 220mb.
- concurrency expansion: when the concurrency is 500, the throughput drops to about 80 mbps, the cpu usage soars to 75%, connection timeouts and queue growth occur.
- advantages: gui management is convenient, supports user authentication, bandwidth control and log auditing, and is suitable for internal use by small and medium-sized teams.
- disadvantages: weak scalability in front of linux high-performance proxy, windows licensing and maintenance costs are relatively high.
- recommended scenarios: small traffic scenarios for enterprises that require windows environment integration (ad authentication, group policy) or have strong demand for management interfaces.
4.
comparison points between squid, 3proxy, shadowsocks/v2ray
- squid (linux): good caching optimization, suitable for http caching scenarios; measured throughput is about 330 mbps, cpu 40%, and memory 400mb when 500 concurrencies are used on the same vps.- 3proxy: lightweight, supports socks/http, flexible configuration; concurrency and throughput are between squid and ccproxy, about 280 mbps at 500 concurrency.
- shadowsocks/v2ray: user-space lightweight encryption proxy. a single instance can stably reach 400 mbps+ (aead) on this machine. it is more concurrency friendly but does not do http caching.
- security comparison: v2ray provides more flexible protocol obfuscation and traffic diversion, while ccproxy relies on the windows security system and rules.
- maintenance and automation: agents under linux are easier to combine with systemd, containerization and automated operation and maintenance, which facilitates horizontal expansion and elastic scaling.
- cost considerations: under the same throughput, linux solutions can usually complete tasks with lower vps specifications, thereby reducing costs.

5.
performance test comparison table (hong kong vps sample data)
| acting | os | throughput(mbps) | cpu% | memory (mb) | concurrency testing |
|---|---|---|---|---|---|
| ccproxy | windows server | 170 | 25 | 220 | 100/500 |
| squid | ubuntu 20.04 | 330 | 40 | 400 | 500 |
| 3proxy | ubuntu | 280 | 35 | 260 | 500 |
| shadowsocks/aead | ubuntu | 400+ | 45 | 150 | high concurrency |
- the data in the table are the average values measured through iperf3, wrk and other tools on the hong kong vps of the same specifications mentioned above, and are for selection reference only.
- under real traffic (frequent requests for small files), squid's cache hits can significantly improve perceived bandwidth usage efficiency.
- shadowsocks can achieve higher throughput on modern cpus with smaller encryption overhead.
6.
real cases and deployment suggestions (domain name/cdn/ddos)
- real case: a cross-border e-commerce company migrated from ccproxy to squid+v2ray combination on hong kong vps. the original configuration was: windows+ccproxy (120 user authentication), but it was stuck when high concurrency occurred. after the migration, the concurrent peak processing capacity increased by about 2 times, and the cost was reduced by about 30%.- domain name and certificate: bind the proxy portal to the hong kong vps with an independent domain name (such as proxy.example.com), and use let's encrypt or a commercial certificate for https/ssl encryption.
- cdn: use cdn (hong kong or global nodes) for static resources and large files to reduce the bandwidth pressure on the origin site and reduce latency.
- ddos defense: choose a hong kong vps provider with basic cleaning or use cloud protection (alibaba cloud/cloudflare/tencent cloud) on the front end. common strategies are traffic cleaning and blacklisting/rate limiting.
- network and firewall: it is recommended to open necessary ports (80/443/port 2000+) and enable iptables/windows firewall speed limit rules, tcp connection limit and connection tracking threshold.
- monitoring and elasticity: combined with prometheus+grafana for real-time monitoring, automatic expansion or switching to a backup node is triggered when traffic approaches the upper limit.
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