AWS Elastic Load Balancer vs Google Cloud Load Balancer - Which Service is Better?
Both AWS Elastic Load Balancer (ELB) and Google Cloud Load Balancer (GCLB) are widely used load balancing services that help distribute traffic between servers to ensure efficient usage and reduce server downtime. While they might share some similarities, they do have their difference. In this post, we will be analyzing both services and provide an unbiased comparison of AWS Elastic Load Balancer vs Google Cloud Load Balancer.
AWS Elastic Load Balancer
Amazon Web Service’s (AWS) Elastic Load Balancer (ELB) is a fully-managed service provided by AWS that is designed to distribute traffic to multiple EC2 instances to improve application performance and reduce downtime. The load balancer is managed by AWS, which means you don't have to worry about setting it up and configuring it manually.
Features
AWS Elastic Load Balancer has three different types of load balancers that offer different features:
- Application Load Balancer: Offers layer 7 routing and supports path-based routing, host-based routing, and URL-based routing. It also supports HTTP/2 and WebSockets protocols.
- Network Load Balancer: Offers layer 4 routing and provides ultra-high throughput, making it suitable for high-performance, TCP/UDP based applications such as streaming.
- Classic Load Balancer: Provides basic load balancing across multiple Amazon EC2 instances and is suited for applications that were built within the EC2-Classic network.
Pricing
AWS offers a pay-as-you-go pricing model which charges based on the data processed by the load balancer, known as the Load Balancer Capacity Unit (LCU). The price per LCU differs depending on the region you use.
For example, In the US East (N. Virginia) region, the price per LCU is $0.025/hour. An Application Load Balancer consumes a minimum of 10 LCUs per hour and a Network Load Balancer consumes 1 LCU per hour.
Google Cloud Load Balancer
Google Cloud Load Balancer (GCLB) is another popular load balancing service provided by Google. It helps distribute traffic to multiple instances to ensure efficient usage and reduce server downtime.
Features
Google Cloud Load Balancing has the following features:
- HTTP(S) Load Balancing: Offers global load balancing using Google’s network and supports path-based routing, host-based routing, and URL-based routing. It also supports HTTP/2 and WebSockets protocols.
- SSL Proxy Load Balancing: Provides SSL/TLS termination for non-HTTP(S) traffic including SSL/TLS encrypted MySQL and RDP.
- TCP/UDP Load Balancing: Supports the load balancing of non-HTTP(S) traffic over TCP or UDP.
Pricing
Google Cloud Load Balancer operates on a pay-per-use model. It charges users based on the amount of traffic that passes through the load balancer. Load balancing in Google Compute Engine starts at $0.025 per hour ($0.000025 per second) for each forwarding rule (regional IP address) used in a load balancer.
For example, if you have one forwarding rule with one IP address for one load balancer, the cost of this load balancer is $18.25 per month. If you increase the number of forwarding rules, the cost will increase.
Which Load Balancer Service is Better?
Both AWS Elastic Load Balancer and Google Cloud Load Balancer have their pros and cons, and which one is better depends on your specific use cases.
If you are an existing AWS customer, then using AWS Elastic Load Balancer might make more sense as it can be easily integrated into your infrastructure. However, if you are starting fresh and want to incorporate more advanced features such as global load balancing, then Google Cloud Load Balancer may be a better choice.
In terms of pricing, both services have their unique billing models that make them highly competitive. AWS Elastic Load Balancer offers a pay-as-you-go model, while Google Cloud Load Balancer offers a pay-per-use model.
Overall, both AWS Elastic Load Balancer and Google Cloud Load Balancer are highly reliable and efficient load balancing services that help distribute traffic effectively, depending on your specific use case.