Riverbed has launched its most comprehensive acceleration update in seven years, significantly enhancing its SteelHead hardware and software portfolio. The company just rolled out significant updates to its SteelHead products, which tackle the complex data handling challenges AI brings to the table.
Riverbed’s timing couldn’t be better—networks are increasingly being completely reconfigured for AI workloads. These enhancements allow IT teams to handle the now-massive data flows that AI tools require.
Speed meets security across environments
Riverbed is rolling out its SteelHead lineup with the new RiOS 10 acceleration software, promising to help companies move data faster between clouds, data centers, and edge locations without sacrificing security or flexibility. Alongside these hardware and software updates, Riverbed is also introducing a more adaptable licensing approach.
The networking landscape is changing with AI at breakneck speed. According to David Donatelli, CEO of Riverbed, this pushed Riverbed to reimagine how data moves through data centers, clouds, and edge environments.
“This is our largest launch in seven years, principally driven by the new ways people need to configure their networks in this new world of AI, with a combination of new software, faster hardware appliances, and flexible business practices that allow our customers to consume our solutions in the ways they want,” said Donatelli.
The bottom line is this: as AI transforms networking, businesses need fresh and ferocious approaches to handle their changing data patterns and infrastructure needs.
Double the performance at half the cost
“AI has made networking much more critical again, across all different parts of the network,” says Jim Frey, principal analyst, networks, at Enterprise Strategy Group. “The research we did has pretty clear findings. AI drives the need to add bandwidth capacity, and enterprises need better, lower latencies because of a variety of ways that AI gets used.”
As Frey explains, AI—especially the generative kind—constantly collects massive amounts of data to train language models, both large and small. Companies now find themselves gathering way more data than before and shipping it back to their training systems.
With generative AI, there’s another challenge as well. When these systems make predictions, they often pull information from a central location to wherever the AI works. This creates a double whammy – not only do you need more bandwidth, but any delays in this process can really hurt performance.
Riverbed’s latest upgrades represent a major performance leap for existing customers, doubling the throughput capacity from 30 Gbps to 60 Gbps per appliance.
The cost benefits are substantial, too—Chalan Aras, who heads up the Acceleration division at Riverbed as senior vice president and general manager, points out that their solutions now move data at around half the cost of traditional methods. This price advantage makes Riverbed’s technology an increasingly attractive option for companies dealing with expanding data requirements.
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