Akamai, Riverbed collaborate to accelerate cloud-based applications


by CBR Staff Writer| 11 May 2011

To solve new app performance challenges introduced by hybrid cloud networks

Akamai Technologies, a provider of cloud optimisation services, and Riverbed Technology, an IT performance firm, have collaborated to work on a joint offering designed to overcome the application performance bottlenecks facing enterprises that leverage public cloud services.

The joint application acceleration offering for hybrid cloud networks leverages a combination of Internet optimisation and wide area network (WAN) optimisation; and the planned offering would be designed to accelerate cloud-based applications, said Akamai.

In addition, both the companies will focus on technology integration designed to solve the new application performance challenges introduced by hybrid cloud networks.

Akamai Internet optimisation software would be integrated within Riverbed Steelhead with the goal of extending Internet optimisations into enterprise networks, thereby extending Akamai's edge from close proximity of the data-centre to directly within the enterprise.

Further, Riverbed WAN optimisation software would be integrated within Akamai edge servers with the goal of extending WAN optimisation into the public cloud, thereby extending Riverbed's edge from the data centre to close proximity of cloud data centres.

Akamai marketing international vice-president Martin Haring said the company's highly-distributed architecture is close to any public cloud infrastructure and Riverbed's Steelhead appliances stretch across thousands of enterprise IT networks from the data centre to the branch office and mobile worker.

"This alliance is focused on marrying best-in-class protocol optimisations for maximum acceleration and infrastructure offload. Together, both companies expect to provide a seamless offering with quick time-to-value while leveraging each other's existing footprints," Haring said.

The joint offering is expected to be available early in 2012.

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