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Riverbed Data Express Service Introduced

Riverbed introduced its new Riverbed Data Express Service enabling enterprises to radically accelerate the movement of massive datasets now required to prepare and deploy AI models at scale — reaching data transfer speeds up to 10 times faster than current industry solutions — improving a customer’s time to value and lowering costs. 

Enterprises are racing to build large language models with tens of petabytes of data scattered across data centers, edge environments, and multiple public clouds. Moving this data to AI-optimized GPU clusters often takes months, delaying time-to-value and increasing costs. With the new Riverbed Data Express Service, what once took months can now be completed in days—giving organizations the speed and security of data delivery now required to prosper in the AI era.

Built on Oracle Cloud Infrastructure (OCI), Riverbed’s Data Express Service utilizes post-quantum cryptography (PQC) to move petabyte-scale datasets through secure VPN tunnels to ensure that customer data remains protected during the transfer process. The service includes enterprise-grade controls for secure access to data as well as the option to deploy data mover agents in customer tenants to enable additional security controls.

“With today’s announcement of the Riverbed Data Express Service, we will be helping customers overcome one of the biggest barriers to AI adoption—getting the right data to the right location, with industry-leading speed and security,” said Dave Donatelli, CEO of Riverbed. “In the first half of this year, we experienced strong demand in our overall business, achieving 77% year-over-year bookings growth. With our new Data Express Service announced today, and with more services planned in the future, we will continue to build on our momentum, helping customers maximize the return on their AI investment.”

“Speed, security and simplicity are now key driving factors for successful AI outcomes,” said Chalan Aras, SVP and GM of Riverbed’s Acceleration Business. “We’re leveraging over two decades of large-scale data movement expertise to dramatically shrink data transfer timelines and accelerate our customer’s path to competitive advantage in the AI era.”

The Riverbed Data Express Service is planned for general availability in Q4 of 2025. 

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Riverbed Data Express Service Introduced

Riverbed introduced its new Riverbed Data Express Service enabling enterprises to radically accelerate the movement of massive datasets now required to prepare and deploy AI models at scale — reaching data transfer speeds up to 10 times faster than current industry solutions — improving a customer’s time to value and lowering costs. 

Enterprises are racing to build large language models with tens of petabytes of data scattered across data centers, edge environments, and multiple public clouds. Moving this data to AI-optimized GPU clusters often takes months, delaying time-to-value and increasing costs. With the new Riverbed Data Express Service, what once took months can now be completed in days—giving organizations the speed and security of data delivery now required to prosper in the AI era.

Built on Oracle Cloud Infrastructure (OCI), Riverbed’s Data Express Service utilizes post-quantum cryptography (PQC) to move petabyte-scale datasets through secure VPN tunnels to ensure that customer data remains protected during the transfer process. The service includes enterprise-grade controls for secure access to data as well as the option to deploy data mover agents in customer tenants to enable additional security controls.

“With today’s announcement of the Riverbed Data Express Service, we will be helping customers overcome one of the biggest barriers to AI adoption—getting the right data to the right location, with industry-leading speed and security,” said Dave Donatelli, CEO of Riverbed. “In the first half of this year, we experienced strong demand in our overall business, achieving 77% year-over-year bookings growth. With our new Data Express Service announced today, and with more services planned in the future, we will continue to build on our momentum, helping customers maximize the return on their AI investment.”

“Speed, security and simplicity are now key driving factors for successful AI outcomes,” said Chalan Aras, SVP and GM of Riverbed’s Acceleration Business. “We’re leveraging over two decades of large-scale data movement expertise to dramatically shrink data transfer timelines and accelerate our customer’s path to competitive advantage in the AI era.”

The Riverbed Data Express Service is planned for general availability in Q4 of 2025. 

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Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...