⚡ Load Balancers in Argentina
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.
Argentina is a South American country with a population of over 46 million people.
According to our statistics, load balancers are detected on 4% of websites from Argentina.
⭐ Most Popular in 2026
The following chart shows the top load balancers in Argentina in 2026, based on market share.
The most popular is Google Cloud Load Balancer with a share of 27.1%, followed by
AWS Elastic Load Balancer with 24.5% and Varnish with 13.6%.
Google Cloud Load Balancer 27.1%
AWS Elastic Load Balancer 24.5%
- Varnish 13.6%
F5 BIG-IP 13.3%Envoy 13%
- Application Request Routing 6.1%
Azure Front Door 3.4%
Azure Application Gateway 3.4%
- Sucuri CloudProxy 2.4%
Heroku Vegur 1%Kong Gateway 0.6%
NetScaler 0.4%
Squid 0.3%
Ivanti vADC 0.3%
Apache Traffic Server 0.1%
🚀 Highlights
Here is a list of the top load balancers that are more popular in Argentina than worldwide.
Differences between global and country rankings are shown in parentheses.
- 1.
Google Cloud Load Balancer (-1)
- 2.
AWS Elastic Load Balancer (-1)
- 5.
Envoy (-1)
- 7.
Azure Front Door (-1)
- 8.
Azure Application Gateway (-1)
- 11.
Kong Gateway (-5)
- 12.
NetScaler (-3)
- 13.
Squid (-4)
✨ Best Load Balancers
Below is a more detailed list of 16 load balancers used on sites from Argentina, 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 17,785 websites from Argentina.
- We currently track the presence of 18 load balancers across the web.
- Of these, 16 were detected on websites from Argentina.
- Statistics were last calculated on .
- For more details, see our methodology and disclaimer.