Cloud-Based Load Balancers
Cloud-based load balancers are not just traffic controllers for spikes in traffic and for optimizing server use. Cloud-native load balancers can also provide predictive analytics to help you visualize traffic bottlenecks before they happen. That in turn delivers actionable insights to help any company optimize its IT solutions.
Application Load Balancing: As enterprises rely more and more on application performance and availability, application load balancing can help them scale, streamline operations, and save money.
Global Server Load Balancing: With users and customers around the world, companies can enhance their load availability with global server load balancing, which sends users to the nearest endpoint to them.
DNS Load Balancing: The practice of configuring a domain in the Domain Name System (DNS) so that user requests to the domain are distributed across a group of server machines is called DNS load balancing.
Network Load Balancing: Application delivery controllers (ADCs), physical or virtual appliances functioning as proxies for physical servers, manage application or network functions, and rely on a network load balancing solution to support them. ADCs also use other techniques, including caching, compression, and offloading of SSL processing, to improve the performance of web applications. In the usual configuration, the ADC sits in front of a group of web and application servers and mediates requests and responses between them and their clients, effectively making the group look like a single virtual server to the end user.
HTTP(S) Load Balancing: The technique for distributing traffic across multiple web or application server groups to optimize resource utilization is called HTTP(S) load balancing.
Internal Load Balancing: An internal load balancer is assigned to a private subnet and does not have a public IP. It typically works within a server farm.
Diameter: A diameter load balancer distributes signaling traffic across multiple servers in a network. One of the most cost-effective ways to do this is to scale the diameter control plane rather than the data transport layer. (Diameter load balancing can also be static or dynamic.)
