Skip to main content

Riverbed Expands Embedded Solutions and Partner-Delivered Managed Services for Location-Independent Computing

Riverbed Technology announced a strategic initiative to expand the range of service delivery options with its service provider partners to enable location-independent computing.

The goal is to make it easier and faster for customers to enjoy the benefits of location-independent computing and to make it easier for partners to embed the Riverbed Application Performance Platform as a standard component into services offerings for application and data delivery.

In a world where application performance equals business performance, Riverbed is committed to offering – together with its partners – the most complete platform to enable organizations to embrace location-independent computing and achieve higher people productivity, better leverage of global skills/resources and radically reduced total cost of ownership (TCO).

The Riverbed Application Performance Platform (APP) is a set of integrated solutions that gives companies the flexibility to host applications and data in the locations that best serve the business while ensuring the flawless delivery of those apps. Riverbed works with a broad and diverse ecosystem of partners to extend the value of the platform with a range of implementation, integration and value-added services.

“With organizations shifting to buying managed services from both traditional service providers and cloud service providers, Riverbed is expanding its go-to-market capability in this area as a key initiative in 2014,” said Dave Peranich, president of global field operations at Riverbed. “The ultimate goal is to make it easy for every organization to turn distance and location into a competitive advantage by working with our partners to offer all the necessary capabilities as easy, fast, managed turnkey services.”

The program enables partners to offer customers fully managed Riverbed solutions that combine application and network performance software and appliances with monitoring and management services. Partners can also use Riverbed’s open APIs to interoperate with partner offerings or to create specialized applications for vertical industries.

According to Gartner, “The key to advancing during this unprecedented time in technology markets is to take a customer centered sales approach (beyond product and market) — to adapt sales models that support customers' new buying processes.”

Riverbed has appointed long-time channel leader and service provider veteran Randy Schirman to the role of senior vice president, service delivery. Schirman was recognized as a 2012 and 2013 Computer Reseller News (CRN) Channel Chief for his contribution and leadership of the Riverbed global channel sales strategy. In addition to spearheading growth and channel development with leading service providers and systems integrators as early as 2008, he was also instrumental in expanding the Riverbed channel with cloud service providers, solutions partners and OEMs.

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

Riverbed Expands Embedded Solutions and Partner-Delivered Managed Services for Location-Independent Computing

Riverbed Technology announced a strategic initiative to expand the range of service delivery options with its service provider partners to enable location-independent computing.

The goal is to make it easier and faster for customers to enjoy the benefits of location-independent computing and to make it easier for partners to embed the Riverbed Application Performance Platform as a standard component into services offerings for application and data delivery.

In a world where application performance equals business performance, Riverbed is committed to offering – together with its partners – the most complete platform to enable organizations to embrace location-independent computing and achieve higher people productivity, better leverage of global skills/resources and radically reduced total cost of ownership (TCO).

The Riverbed Application Performance Platform (APP) is a set of integrated solutions that gives companies the flexibility to host applications and data in the locations that best serve the business while ensuring the flawless delivery of those apps. Riverbed works with a broad and diverse ecosystem of partners to extend the value of the platform with a range of implementation, integration and value-added services.

“With organizations shifting to buying managed services from both traditional service providers and cloud service providers, Riverbed is expanding its go-to-market capability in this area as a key initiative in 2014,” said Dave Peranich, president of global field operations at Riverbed. “The ultimate goal is to make it easy for every organization to turn distance and location into a competitive advantage by working with our partners to offer all the necessary capabilities as easy, fast, managed turnkey services.”

The program enables partners to offer customers fully managed Riverbed solutions that combine application and network performance software and appliances with monitoring and management services. Partners can also use Riverbed’s open APIs to interoperate with partner offerings or to create specialized applications for vertical industries.

According to Gartner, “The key to advancing during this unprecedented time in technology markets is to take a customer centered sales approach (beyond product and market) — to adapt sales models that support customers' new buying processes.”

Riverbed has appointed long-time channel leader and service provider veteran Randy Schirman to the role of senior vice president, service delivery. Schirman was recognized as a 2012 and 2013 Computer Reseller News (CRN) Channel Chief for his contribution and leadership of the Riverbed global channel sales strategy. In addition to spearheading growth and channel development with leading service providers and systems integrators as early as 2008, he was also instrumental in expanding the Riverbed channel with cloud service providers, solutions partners and OEMs.

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...