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Making Digital Transformation Work for You – Part 2

Bridging the Performance Gap
Joshua Dobies

Start with Making Digital Transformation Work for You – Part 1

Part 1 of this three-part series examined how the digital transformation wave that has swept through enterprise IT is finally reaching the network. Organizations leverage public and private clouds to enable users to connect 24/7 to applications and information stores via a wide array of devices. This places an ever-increasing strain on the networks, and the professionals who build and manage them.

As a result, application performance levels too often fail to meet the needs of the business. This creates what I call a "performance gap" – a widening gulf between the needs of business and what IT is able to provide (or not) to meet those needs. The business impacts include more unhappy customers, contract delays, missed deadlines and lost revenue. So in Part 2 of this series, let's examine the four key elements any organization can address today to bridge this gap.

First, it's important to understand the solution is not to try to limit the number of applications you provide to users. That's like trying to push back the incoming high tide. Consider these stats:

According to Gartner, worldwide spending on enterprise application software will grow from $149.9 billion in 2015 to more than $201 billion by 2019, driven primarily by modernization, functional expansion and digital transformation projects.1

■ IDC predicts that by 2018, businesses will more than double software development capabilities; two-thirds of their coders will focus on strategic digital transformation apps and services.

IDC predicts that by 2018, there will be 22 billion Internet of Things devices installed, driving the development of more than 200,000 new apps and services.2

You have our global economy based on services to thank. The world has been heading toward a services-based economy for some time, leaving behind an economy dominated by manufacturing. In the 1980s, services accounted for about half of world GDP; by the mid-1990s it was up to two-thirds. The trend is even stronger in post-industrial economies: Services now make up 80 percent of the British and 84 percent of the US economy. Even in countries that are transitioning from agriculture to industry, the services sector is growing faster than the rest of the economy.

Services themselves are evolving rapidly. The old services economy was based on the model of someone doing something for you in the physical world — someone cooks dinner for you in a restaurant, someone fixes your car, someone does your taxes.

The new services economy, in contrast, is dominated by made-to-order digital services. They're differentiated by the quality of the experience for which intuitive ease, convenience, and richness of choice are key criteria. Thus, we are moving from a world dominated by mass-manufactured, mass-marketed products to an immersive market of custom services and digital experiences.

Digital services may seem like magic to users, who now expect – even demand – anytime, anywhere access to them on their desktops and mobile devices. But underneath the magic of the simple UX lies the difficulty of moving apps over long-distance high-speed networks.

Digital services are enabled by a chain of IT interactions that link device, application, data, network, and infrastructure components. This complex chain of interactions is only as strong as its weakest link. All the parts of an application are links in the chain, and these links must mesh seamlessly across a complex, hybrid IT environment which is partly in the cloud, partly on-premises, with connectivity provided by a mix of private and public networks, in order to give users a good experience and drive maximum business productivity. Any grain of sand in the gears, any tiny flaw in the infrastructure—from server failure, to issues within the software code, to a problematic database, to network latency, to user device compatibility—can slow the application down or cause it to fail completely.

And yet, in our globally distributed, hybrid application environment, there is so much complexity, so many moving parts and operational dependencies, that the weak links in the chain are bound to get stressed to the breaking point. This creates the performance gap.

Bridging the Performance Gap

You must get a handle on four elements that comprise the fundamental links to make an app work: data, software, people, and networks. That requires knowing the answers to four key questions (hint – there's really just one answer):

Q: Where are your apps?
A: Everywhere.

Q: Where is your data?
A: Everywhere.

Q: Where are your users?
A: Everywhere.

Q: How is it all connected?
A: Everywhere.

Your apps are everywhere. Your data is everywhere. Your users are everywhere, and it's all connected via multiple types of networks that are … yes … everywhere.

In today's complex hybrid IT environments where data, applications, people, and networks are everywhere, point solutions cannot provide a total solution. The infrastructure challenges that impact application performance are ubiquitous, so only a holistic approach that brings visibility, performance, agility, and security to every aspect and stage of application delivery can provide an enterprise-grade solution for the age of hybrid IT. Just as digital transformation is an enterprise business strategy, enterprises need an architectural strategy to make the underpinning technology work the way it needs to.

The foundation of that architectural strategy is to stop using the traditional tools: routers and switches. In Part 3 of this series, I'll explain why those tools are quickly growing obsolete, and why SD-WAN is emerging as the technology that enables you to create a scalable network architecture that supports, enables and drives digital transformation with new levels of visibility, performance, security and agility.

Joshua Dobies is VP of Product Marketing, Riverbed Technology.

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 ...

Making Digital Transformation Work for You – Part 2

Bridging the Performance Gap
Joshua Dobies

Start with Making Digital Transformation Work for You – Part 1

Part 1 of this three-part series examined how the digital transformation wave that has swept through enterprise IT is finally reaching the network. Organizations leverage public and private clouds to enable users to connect 24/7 to applications and information stores via a wide array of devices. This places an ever-increasing strain on the networks, and the professionals who build and manage them.

As a result, application performance levels too often fail to meet the needs of the business. This creates what I call a "performance gap" – a widening gulf between the needs of business and what IT is able to provide (or not) to meet those needs. The business impacts include more unhappy customers, contract delays, missed deadlines and lost revenue. So in Part 2 of this series, let's examine the four key elements any organization can address today to bridge this gap.

First, it's important to understand the solution is not to try to limit the number of applications you provide to users. That's like trying to push back the incoming high tide. Consider these stats:

According to Gartner, worldwide spending on enterprise application software will grow from $149.9 billion in 2015 to more than $201 billion by 2019, driven primarily by modernization, functional expansion and digital transformation projects.1

■ IDC predicts that by 2018, businesses will more than double software development capabilities; two-thirds of their coders will focus on strategic digital transformation apps and services.

IDC predicts that by 2018, there will be 22 billion Internet of Things devices installed, driving the development of more than 200,000 new apps and services.2

You have our global economy based on services to thank. The world has been heading toward a services-based economy for some time, leaving behind an economy dominated by manufacturing. In the 1980s, services accounted for about half of world GDP; by the mid-1990s it was up to two-thirds. The trend is even stronger in post-industrial economies: Services now make up 80 percent of the British and 84 percent of the US economy. Even in countries that are transitioning from agriculture to industry, the services sector is growing faster than the rest of the economy.

Services themselves are evolving rapidly. The old services economy was based on the model of someone doing something for you in the physical world — someone cooks dinner for you in a restaurant, someone fixes your car, someone does your taxes.

The new services economy, in contrast, is dominated by made-to-order digital services. They're differentiated by the quality of the experience for which intuitive ease, convenience, and richness of choice are key criteria. Thus, we are moving from a world dominated by mass-manufactured, mass-marketed products to an immersive market of custom services and digital experiences.

Digital services may seem like magic to users, who now expect – even demand – anytime, anywhere access to them on their desktops and mobile devices. But underneath the magic of the simple UX lies the difficulty of moving apps over long-distance high-speed networks.

Digital services are enabled by a chain of IT interactions that link device, application, data, network, and infrastructure components. This complex chain of interactions is only as strong as its weakest link. All the parts of an application are links in the chain, and these links must mesh seamlessly across a complex, hybrid IT environment which is partly in the cloud, partly on-premises, with connectivity provided by a mix of private and public networks, in order to give users a good experience and drive maximum business productivity. Any grain of sand in the gears, any tiny flaw in the infrastructure—from server failure, to issues within the software code, to a problematic database, to network latency, to user device compatibility—can slow the application down or cause it to fail completely.

And yet, in our globally distributed, hybrid application environment, there is so much complexity, so many moving parts and operational dependencies, that the weak links in the chain are bound to get stressed to the breaking point. This creates the performance gap.

Bridging the Performance Gap

You must get a handle on four elements that comprise the fundamental links to make an app work: data, software, people, and networks. That requires knowing the answers to four key questions (hint – there's really just one answer):

Q: Where are your apps?
A: Everywhere.

Q: Where is your data?
A: Everywhere.

Q: Where are your users?
A: Everywhere.

Q: How is it all connected?
A: Everywhere.

Your apps are everywhere. Your data is everywhere. Your users are everywhere, and it's all connected via multiple types of networks that are … yes … everywhere.

In today's complex hybrid IT environments where data, applications, people, and networks are everywhere, point solutions cannot provide a total solution. The infrastructure challenges that impact application performance are ubiquitous, so only a holistic approach that brings visibility, performance, agility, and security to every aspect and stage of application delivery can provide an enterprise-grade solution for the age of hybrid IT. Just as digital transformation is an enterprise business strategy, enterprises need an architectural strategy to make the underpinning technology work the way it needs to.

The foundation of that architectural strategy is to stop using the traditional tools: routers and switches. In Part 3 of this series, I'll explain why those tools are quickly growing obsolete, and why SD-WAN is emerging as the technology that enables you to create a scalable network architecture that supports, enables and drives digital transformation with new levels of visibility, performance, security and agility.

Joshua Dobies is VP of Product Marketing, Riverbed Technology.

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 ...