Server load balancing is a standard solution in data centers as well as in Server load balancing is a standard solution in data centers as well as in the computing environments of network infrastructures. At its essence, server load balancing (SLB) is a technique by which application and web traffic (or load) is distributed across multiple servers to optimize application and server performance, ensure availability, scalability and resilience, offer first-level security and deliver a high-quality user experience. Server load balancing also allows easy scaling of applications and web services; as traffic loads increase, servers can be seamlessly added to the pool to provide additional resources.
Key Technologies and Techniques
The APV Series offers a number of other features that serve to further accelerate and secure web and business application servers. Among them are:
Large numbers of short connections can cause a server to run out of network resources. Connection multiplexing converts these short connections into a smaller number of high-throughput connections, effectively creating persistent fast lanes that can increase server efficiency by up to 70 percent.
Caching and compression:
The APV Series performs caching of frequently requested data in its memory to increase server efficiency and improve seek and response times by as much as 500%. In addition, hardware or software compression can reduce bandwidth utilization and client response times by more than half.
Layer-7 policy engine:
APV Series includes an immense library of policies, which eliminates to a large degree the need for complex, compute-intensive scripting. Policies can be combined and nested for advanced, granular application traffic management.
WebWall® web application security:
WebWall provides deep application data inspection (beyond just IP and TCP headers) to protect against attacks such as SQL injection and cross-site scripting.
DDoS protection with machine learning:
Array ADCs are security hardened to protect against DDoS attacks at the network, session and application layers, and content filtering protects against protocol and application DDoS attacks along with many common attack types. Machine learning provides anomaly detection and automatic configuration of thresholds.