Array Networks Unveils New Version of its OS for AppVelocity

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New AppVelocity software version leverages SpeedCore’s multi-core technology to further enhance performance by up to 10 times

Array Networks announced a new version of its operating system for its AppVelocity (APV) portfolio of application delivery controllers (ADC). Leveraging the SpeedCore architecture, the new ArrayOS 8.1 fully leverages 64-bit processing and multi-core technology to deliver dramatic improvements in performance, packet handling and memory capacity. The new version also delivers multi-fold improvements in server offload and acceleration capabilities using new and improved functionality related to server load balancing, caching, compression, system level monitoring, process/module level resilience, application flow monitoring and field troubleshooting. Together, these enhance overall performance and scalability under a high traffic load.

At the center of the ArrayOS is SpeedCore, which uses a lock-free multi-core technology to enhance performance by up to 10 times and deliver significant capacity gains for HTTP, TCP and SSL offloading by supporting multiple 10Gbps network inte

rface cards for application processing. The rise of Web 2.0 traffic, multi-media services, data center virtualization and hosted cloud-centric applications has made it increasingly important that ADC solutions be capable of handling complex application delivery efficiently. With the SpeedCore architecture, the ArrayOS 8.1 APV products have the ability to support diverse network and application-level routing using software-based intelligence to deliver high performance for processor-intensive applications.

The combination of high-performance and high-intelligence takes the efficiency of the Array APV products to the next level, said Michael Zhao, President & CEO of Array Networks. For more than a decade Array has been working with Global 500 customers in understanding the fundamental cause-and-effect relationships within complex application delivery architectures. We have identified datacenter bottlenecks, and redesigned key components to make them more efficient and