In this post, you’ll learn how load balancing works in the cloud, specifically on Google Cloud Platform, and which load balancers are available for your use. You have two options: scale up or scale out
By IOD Expert Samuel James
If you’re a person working in DevOps or on a software development team, you’ve probably heard the expression “You build it, you run it,” coined by Werner Vogels, the CTO of Amazon, in 2016. This attitude dominates the DevOps approach.
Modern applications serve millions of requests from users across different geographical regions around the world. It’s a must that teams find an efficient way of distributing workloads across servers to maximize speed and capacity utilization.
In this post, you’ll learn how load balancing works in the cloud, specifically on Google Cloud Platform, and which load balancers are available for your use.
Figure 1: Simple example of load balancing
One of the main goals of load balancing in the cloud is to prevent servers from breaking down or getting overloaded.
Load balancers can either be hardware-based or software-based. Hardware-based load balancers are physical hardware and are essentially dedicated systems (boxes) whose main purpose is to balance the flow of information between servers. Conversely, software-based load balancers run on standard operating systems and hardware (PCs, desktops).
While hardware-based load balancers require rack-and-sack, proprietary appliances, the software-based balancers are installed on virtual machines and standard x86 servers.
Hardware-based load balancers typically require you to provide enough load balancers to meet increasing network traffic demands. By implication, several load balancers will have to remain idle until there’s an increase in network traffic, for example, on Black Friday.
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