⚡ Load Balancers in Hong Kong
Load balancers are software components or network devices that distribute incoming traffic across multiple backend servers, improving application availability, scalability, and fault tolerance by preventing any single server from becoming a bottleneck.
Hong Kong is an East Asian special administrative region of China with a population of around 7.5 million people.
According to our statistics, load balancers are detected on 3.7% of websites from Hong Kong.
⭐ Most Popular in 2026
The following chart shows the top load balancers in Hong Kong in 2026, based on market share.
The most popular is Google Cloud Load Balancer with an impressive share of 30.3%, followed by
F5 BIG-IP with 18.5% and AWS Elastic Load Balancer with 16.7%.
Google Cloud Load Balancer 30.3%
F5 BIG-IP 18.5%AWS Elastic Load Balancer 16.7%
- Varnish 10.6%
Envoy 10.4%
- Application Request Routing 8.6%
Azure Front Door 5.1%
Azure Application Gateway 4.6%
- Sucuri CloudProxy 1.8%
- HAProxy 1.5%
Squid 0.6%
Heroku Vegur 0.3%Ivanti vADC 0.3%
Kong Gateway 0.1%
🚀 Highlights
Here is a list of the top load balancers that are more popular in Hong Kong than worldwide.
Differences between global and country rankings are shown in parentheses.
- 1.
Google Cloud Load Balancer (-1)
- 2.
F5 BIG-IP (-2) - 5.
Envoy (-1)
- 7.
Azure Front Door (-1)
- 8.
Azure Application Gateway (-1)
- 10. HAProxy (-3)
- 11.
Squid (-6)
- 14.
Kong Gateway (-2)
✨ Best Load Balancers
Below is a more detailed list of 14 load balancers used on sites from Hong Kong, ranked by their market share.
🗃️ About This Data
- We evaluate the popularity of technologies based on the number of websites where we detect their usage.
- Technologies without a detectable web footprint, and those we do not track, are not reflected in the calculated market share.
- This report is based on the analysis of 18,179 websites from Hong Kong.
- We currently track the presence of 18 load balancers across the web.
- Of these, 14 were detected on websites from Hong Kong.
- Statistics were last calculated on .
- For more details, see our methodology and disclaimer.