Riverbed: Trends and Predictions for 2017

Sean Applegate
Learn more about Riverbed

Riverbed highlights the following trends and predictions for 2017:

Enterprises Move Toward a Strategic Architecture for Digital Transformation

IDC predicts that, by 2017, 60% of digital transformation initiatives will be unable to scale due to a lack of a strategic architecture. And by 2018, 70% of siloed digital transformation initiatives will ultimately fail due to insufficient collaboration, integration, sourcing, or project management. Research from MIT Sloan Management and Deloitte University Press concurs. They found that less-mature digital companies tend to take a tactical, piecemeal approach as they solve discrete business problems with individual digital technologies. As a result, they don’t fully integrate digital technologies with their business operations, don’t solve the underlying infrastructure problems that cause frequent application performance issues across the enterprise, and fail to deliver the required technical capabilities at scale.

Prediction: Enterprises will realize that, for application, compute, storage, and networking infrastructure to work optimally, it all must work together, seamlessly, as a system. Any point of weakness or failure anywhere in the infrastructure can make the whole system fail. Thus, a strategic architecture must extend across the enterprise and unite all the components into a seamless, software-defined system delivering high-performing applications, data, and services.

Everything Becomes Software-Defined

Whether it is compute, storage or networking, you can see increased impact and adoption of software-defined everything. In the software-defined world, management and control of computing environment, storage and networking is automated by intelligent software and not by the hardware components.

Prediction: Enterprise organizations will implement technologies that ensure agility, visibility and performance in order to transition more and more to a software-defined enterprise.

Digital Transformation Drives Next Wave of Cloud

Enterprise-level internal resources including business-critical applications are now being moved to the cloud. This is a new development as internal-facing applications are traditionally kept internal. The challenge with migrating old systems and applications to a newer encrypted approach is that the network capabilities can be stretched thin or become too fragile. This ultimately creates complexities tied to application planning, performance monitoring and final migration to the cloud.

Prediction: Digital transformation isn’t a fad and we expect to see the migration of critical applications to the cloud increase in 2017 across all markets. Large enterprise clouds are now being adopted beyond just customer-facing resources like eCommerce websites. Having visibility is important in order to understand how things are being influenced as organizations change the digital landscape. Cloud-only and internet-only transport are the future as they allow enterprise organizations to become more nimble and agile, while also providing cost savings.

New Breed of Engineers Turns Network Threats Into Opportunities

The rapid adoption rates of public cloud and SaaS-based applications and services are fueling an incredible transformation in how work gets done. This creates a challenge for IT to meet user expectations and needs, so much so that many users bypass IT entirely and start using new SaaS and cloud-based applications, increasing shadow IT and driving further complexity. This creates a performance gap between the needs of the business, and what IT can provide.

Prediction: We expect to see a new breed of network engineers to help departments evaluate and solve their business needs. The business will see them as strategic partners. Increasingly, this function will be critical to ensure that the business can respond to the changing expectations of its internal and external customers. For this, they have to embrace the tools that will bring enterprise networking to the cloud era.

Visibility Creates a Competitive Advantage for the Hybrid Enterprise

After deploying a hybrid environment, which can be complex and difficult to manage, the work is just beginning for the enterprise. The process continues as application requirements and business needs evolve. So, to increase agility, IT is always evaluating and adopting cloud services and related technologies like PaaS, containers and micro-services to deliver applications faster. IT organizations will keep an eye on the longer-term to ensure that they can scale as usage increases.

Prediction: We expect to see greater adoption of application and network management functionality to ensure visibility into the hybrid cloud creating more trust in IT and alignment to business objectives.

Cloud Visibility Becomes Critical to Success of DevOps Approach to Digital Services

DevOps teams are increasingly using the cloud’s PaaS capabilities together with third-party components to develop composite applications faster. According to Sonatype, the average enterprise downloads more than 229,000 components annually, of which one in 16 has security defects. Third-party components account for 80% - 90% of the code in a typical enterprise application today. Current monitoring for components traces app transactions through server interactions, which obscures dependencies within the app layer.

Prediction: Enterprises will seek new solutions that provide clear visibility into the behavior and interaction of third-party components and platforms in cloud-based environments in order to accelerate development of apps and digital services in the cloud, proactively prevent performance issues, and improve performance of cloud-based apps.

IT Continues to Solidify Its Place As a Value Center, Not a Cost Center

CIOs are continuing to re-examine how they generate and articulate value to their business peers, and they’re starting to make real progress in shifting the perceptions within organizations about IT and how it can help the business. The trends outlined above, like DevOps, will give IT leaders greater flexibility and agility when meeting dynamic business requirements, positioning them at the center of the corporate decision-making nexus.

Prediction: We expect to see more and more IT teams act more like a product team that helps develop the new tools stakeholders need. Watch for the further evolution of this trend in the coming year.

The Cloud-Ready Branch Ends Data Storage at Remote Locations

Organizations that lose data, lose business. Regardless of the mix of cloud services being used, backing up data is still a necessity, especially at branch or remote sites. Branch IT is poised for transformation with the rising adoption of cloud-first strategies, and as CIOs look for ways to reduce the risk of data loss at the branch.

Prediction: We expect to see more enterprise organizations transform distributed IT with a software-defined approach by deploying a centralized infrastructure model. This will allow organizations to build a safer, easier, and more effective way to back up data at the branch and store data in the datacenter, cloud or via a hybrid combination. By levering this approach, IT can instantly provision and deploy new services at these sites to keep pace with the demand and growth of the business.

Sean Applegate is Sr. Director, Technology Strategist at Riverbed.

Hot Topics

Related Vendors

The Latest

Manufacturing Organizations Doubled AI Investment Yet Only 37% Fully Prepared to Operationalize AI

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Optimizing Decisions with Edge-First Cognitive Intelligence

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

The New Perimeter Is the User: Why Identity Is the Real Network Edge

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

When AI Infrastructure Stops Behaving Like Infrastructure

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Enterprise Resilience: Understanding the Shift from Static to Dynamic

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile Users Expect Perfection in 2026

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

AI Confidence Is High. Readiness Is Not. What the Data Tells Us - and Why It Matters

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI, Realistic Expectations and the Future of IT Operations in 2026

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

Trust, But Verify: Building Confidence in AI Through Human Oversight

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

Data Centers Plan to Reduce Reliance on Grid

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...

Riverbed: Trends and Predictions for 2017

Sean Applegate
Learn more about Riverbed

Riverbed highlights the following trends and predictions for 2017:

Enterprises Move Toward a Strategic Architecture for Digital Transformation

IDC predicts that, by 2017, 60% of digital transformation initiatives will be unable to scale due to a lack of a strategic architecture. And by 2018, 70% of siloed digital transformation initiatives will ultimately fail due to insufficient collaboration, integration, sourcing, or project management. Research from MIT Sloan Management and Deloitte University Press concurs. They found that less-mature digital companies tend to take a tactical, piecemeal approach as they solve discrete business problems with individual digital technologies. As a result, they don’t fully integrate digital technologies with their business operations, don’t solve the underlying infrastructure problems that cause frequent application performance issues across the enterprise, and fail to deliver the required technical capabilities at scale.

Prediction: Enterprises will realize that, for application, compute, storage, and networking infrastructure to work optimally, it all must work together, seamlessly, as a system. Any point of weakness or failure anywhere in the infrastructure can make the whole system fail. Thus, a strategic architecture must extend across the enterprise and unite all the components into a seamless, software-defined system delivering high-performing applications, data, and services.

Everything Becomes Software-Defined

Whether it is compute, storage or networking, you can see increased impact and adoption of software-defined everything. In the software-defined world, management and control of computing environment, storage and networking is automated by intelligent software and not by the hardware components.

Prediction: Enterprise organizations will implement technologies that ensure agility, visibility and performance in order to transition more and more to a software-defined enterprise.

Digital Transformation Drives Next Wave of Cloud

Enterprise-level internal resources including business-critical applications are now being moved to the cloud. This is a new development as internal-facing applications are traditionally kept internal. The challenge with migrating old systems and applications to a newer encrypted approach is that the network capabilities can be stretched thin or become too fragile. This ultimately creates complexities tied to application planning, performance monitoring and final migration to the cloud.

Prediction: Digital transformation isn’t a fad and we expect to see the migration of critical applications to the cloud increase in 2017 across all markets. Large enterprise clouds are now being adopted beyond just customer-facing resources like eCommerce websites. Having visibility is important in order to understand how things are being influenced as organizations change the digital landscape. Cloud-only and internet-only transport are the future as they allow enterprise organizations to become more nimble and agile, while also providing cost savings.

New Breed of Engineers Turns Network Threats Into Opportunities

The rapid adoption rates of public cloud and SaaS-based applications and services are fueling an incredible transformation in how work gets done. This creates a challenge for IT to meet user expectations and needs, so much so that many users bypass IT entirely and start using new SaaS and cloud-based applications, increasing shadow IT and driving further complexity. This creates a performance gap between the needs of the business, and what IT can provide.

Prediction: We expect to see a new breed of network engineers to help departments evaluate and solve their business needs. The business will see them as strategic partners. Increasingly, this function will be critical to ensure that the business can respond to the changing expectations of its internal and external customers. For this, they have to embrace the tools that will bring enterprise networking to the cloud era.

Visibility Creates a Competitive Advantage for the Hybrid Enterprise

After deploying a hybrid environment, which can be complex and difficult to manage, the work is just beginning for the enterprise. The process continues as application requirements and business needs evolve. So, to increase agility, IT is always evaluating and adopting cloud services and related technologies like PaaS, containers and micro-services to deliver applications faster. IT organizations will keep an eye on the longer-term to ensure that they can scale as usage increases.

Prediction: We expect to see greater adoption of application and network management functionality to ensure visibility into the hybrid cloud creating more trust in IT and alignment to business objectives.

Cloud Visibility Becomes Critical to Success of DevOps Approach to Digital Services

DevOps teams are increasingly using the cloud’s PaaS capabilities together with third-party components to develop composite applications faster. According to Sonatype, the average enterprise downloads more than 229,000 components annually, of which one in 16 has security defects. Third-party components account for 80% - 90% of the code in a typical enterprise application today. Current monitoring for components traces app transactions through server interactions, which obscures dependencies within the app layer.

Prediction: Enterprises will seek new solutions that provide clear visibility into the behavior and interaction of third-party components and platforms in cloud-based environments in order to accelerate development of apps and digital services in the cloud, proactively prevent performance issues, and improve performance of cloud-based apps.

IT Continues to Solidify Its Place As a Value Center, Not a Cost Center

CIOs are continuing to re-examine how they generate and articulate value to their business peers, and they’re starting to make real progress in shifting the perceptions within organizations about IT and how it can help the business. The trends outlined above, like DevOps, will give IT leaders greater flexibility and agility when meeting dynamic business requirements, positioning them at the center of the corporate decision-making nexus.

Prediction: We expect to see more and more IT teams act more like a product team that helps develop the new tools stakeholders need. Watch for the further evolution of this trend in the coming year.

The Cloud-Ready Branch Ends Data Storage at Remote Locations

Organizations that lose data, lose business. Regardless of the mix of cloud services being used, backing up data is still a necessity, especially at branch or remote sites. Branch IT is poised for transformation with the rising adoption of cloud-first strategies, and as CIOs look for ways to reduce the risk of data loss at the branch.

Prediction: We expect to see more enterprise organizations transform distributed IT with a software-defined approach by deploying a centralized infrastructure model. This will allow organizations to build a safer, easier, and more effective way to back up data at the branch and store data in the datacenter, cloud or via a hybrid combination. By levering this approach, IT can instantly provision and deploy new services at these sites to keep pace with the demand and growth of the business.

Sean Applegate is Sr. Director, Technology Strategist at Riverbed.

Hot Topics

Related Vendors

The Latest

Manufacturing Organizations Doubled AI Investment Yet Only 37% Fully Prepared to Operationalize AI

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Optimizing Decisions with Edge-First Cognitive Intelligence

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

The New Perimeter Is the User: Why Identity Is the Real Network Edge

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

When AI Infrastructure Stops Behaving Like Infrastructure

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Enterprise Resilience: Understanding the Shift from Static to Dynamic

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile Users Expect Perfection in 2026

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

AI Confidence Is High. Readiness Is Not. What the Data Tells Us - and Why It Matters

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI, Realistic Expectations and the Future of IT Operations in 2026

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

Trust, But Verify: Building Confidence in AI Through Human Oversight

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

Data Centers Plan to Reduce Reliance on Grid

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...