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Riverbed SteelFusion Supports Microsoft Azure and AWS

Riverbed Technology announced that Riverbed SteelFusion is extending its reach to cloud environments with support for Azure through Microsoft StorSimple and Amazon Web Services through AWS Storage Gateway.

Customers now have more flexibility and choice for cloud-based data storage across remote locations and can leverage the cloud as a secondary storage tier for added capacity, backup, or for tiering in conjunction with private data center storage assets.

“We are excited to give our SteelFusion customers more options and flexibility with the ability to store their remote data in the cloud, whether it be with Microsoft Azure or Amazon Web Services,” said Paul O’Farrell, SVP and GM of SteelHead, SteelFusion and SD-WAN solutions at Riverbed. “Many of today’s enterprises are already using a hybrid IT model, with data both in the cloud and data center. Now with access to cloud-based storage and backup capabilities with SteelFusion, our customers can easily leverage the cloud as a secondary storage tier without any impact to users at the edge.”

This announcement builds on the SteelFusion 4.0 release in April 2015 that delivered updated and redesigned hardware platforms to provide increased performance and scalability for remote sites and regional hubs of all sizes. In November, Riverbed announced SteelFusion support for customers using VMware vSphere 6. Now, Riverbed is continuing to expand its SteelFusion ecosystem with leading cloud providers AWS and Microsoft, giving enterprises the additional flexibility to access cloud-based storage, backup, and tiering capabilities from one centralized location – eliminating the need to invest in costly physical servers at remote locations.

Combining virtualization, intelligent storage delivery, and WAN optimization, SteelFusion is designed with the unique challenges of remote and branch office (ROBO) IT in mind.

SteelFusion:

- Removes all physical servers, storage, and valuable data from ROBO locations

- Consolidates and accelerates time-consuming ROBO IT operations, such as backup processes and data protection, provisioning of new services and sites, and fast recovery to central data centers in a single solution

- Extends enterprise-class security, services and resiliency of the central data center, and now the cloud, out to all ROBO locations, regardless of distance, and without compromising performance

Unlike hyper-converged solutions purpose-built to simplify data center infrastructures, SteelFusion is built to enable the “hyper-converged edge.” SteelFusion simultaneously meets the top requirements of businesses, IT organizations and employees by reducing the operational cost of managing remote locations, increasing data security, improving business continuity and IT agility with 100x faster recovery times and 30x faster deployment of branch services and sites, and providing up to a 100x increase in application performance at the branch for greater productivity.

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Riverbed SteelFusion Supports Microsoft Azure and AWS

Riverbed Technology announced that Riverbed SteelFusion is extending its reach to cloud environments with support for Azure through Microsoft StorSimple and Amazon Web Services through AWS Storage Gateway.

Customers now have more flexibility and choice for cloud-based data storage across remote locations and can leverage the cloud as a secondary storage tier for added capacity, backup, or for tiering in conjunction with private data center storage assets.

“We are excited to give our SteelFusion customers more options and flexibility with the ability to store their remote data in the cloud, whether it be with Microsoft Azure or Amazon Web Services,” said Paul O’Farrell, SVP and GM of SteelHead, SteelFusion and SD-WAN solutions at Riverbed. “Many of today’s enterprises are already using a hybrid IT model, with data both in the cloud and data center. Now with access to cloud-based storage and backup capabilities with SteelFusion, our customers can easily leverage the cloud as a secondary storage tier without any impact to users at the edge.”

This announcement builds on the SteelFusion 4.0 release in April 2015 that delivered updated and redesigned hardware platforms to provide increased performance and scalability for remote sites and regional hubs of all sizes. In November, Riverbed announced SteelFusion support for customers using VMware vSphere 6. Now, Riverbed is continuing to expand its SteelFusion ecosystem with leading cloud providers AWS and Microsoft, giving enterprises the additional flexibility to access cloud-based storage, backup, and tiering capabilities from one centralized location – eliminating the need to invest in costly physical servers at remote locations.

Combining virtualization, intelligent storage delivery, and WAN optimization, SteelFusion is designed with the unique challenges of remote and branch office (ROBO) IT in mind.

SteelFusion:

- Removes all physical servers, storage, and valuable data from ROBO locations

- Consolidates and accelerates time-consuming ROBO IT operations, such as backup processes and data protection, provisioning of new services and sites, and fast recovery to central data centers in a single solution

- Extends enterprise-class security, services and resiliency of the central data center, and now the cloud, out to all ROBO locations, regardless of distance, and without compromising performance

Unlike hyper-converged solutions purpose-built to simplify data center infrastructures, SteelFusion is built to enable the “hyper-converged edge.” SteelFusion simultaneously meets the top requirements of businesses, IT organizations and employees by reducing the operational cost of managing remote locations, increasing data security, improving business continuity and IT agility with 100x faster recovery times and 30x faster deployment of branch services and sites, and providing up to a 100x increase in application performance at the branch for greater productivity.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

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.