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Lightning Fast Internet Is Coming - Are You Ready?

Steve Brown

Network capacity is the lifeblood of an enterprise — bandwidth enables business.

If you're ever in doubt, just recall what it's like when there is an outage or a major slow-down. Disgruntled employees, frustrated network pros ... it's no wonder that around half of IT staff from network or system admins to VP level and higher all cite network slow-downs as one of their biggest challenges.

Getting the most out of the network is a fine balancing act, so it's understandable that enterprises are always hungry for more bandwidth. Two out of three IT and network professionals expect bandwidth usage to increase by up to 50% by the end of 2017.

Thankfully there are great leaps of progress afoot when it comes to broadband connectivity. Bandwidth availability issues that enterprises routinely face could become a thing of the past. We are on the cusp of a great surge of capacity as gigabit speed internet becomes a reality. In fact, there are already more than 600 deployments of gigabit internet globally.

The mind-boggling speed of gigabit internet is often explained in the number of seconds it would take to, say, download an HD movie (less than 5). But while we can all appreciate the entertainment possibilities, let's not forget its importance from an enterprise perspective. Speeds and capacity on this scale have the power to transform businesses and disrupt business models, as we are already seeing with the advent of virtual reality, augmented reality and the IoT.

Wouldn't it be great to track the development of super-fast broadband deployments as they happen? Viavi thought so. Using publicly available data, we built a visual, living database of gigabit deployments around the world: the Gigabit Monitor. Here's what we found.

The Need for Speed

While fiber makes up the lion's share of deployments (no surprise), there is strong evidence pointing to the scale of cellular gigabit connectivity changing significantly. Currently, we know that 25 mobile operators are lab-testing 5G, and 12 of those have progressed to field trials.

It's fascinating to speculate how such a shift will change public services, manufacturing and retail to name but a few industries. 5G is coming and businesses need to be ready for it.

Digital Transformation

Gigabit deployments have risen at a rate of 72 percent in the past year. This is higher than even we expected. Businesses who are interested in checking the progress of gigabit connectivity by region, provider or technology type can now easily do so. As businesses increasingly adopt agile methods and implement digital transformation, gigabit speeds will be a key enabler.

A Mixed Bag for US Business

Globally, over 219 million people have gigabit speeds available to them. The US leads the way with around 57 percent of deployments. This translates to over 56 million people in the US having gigabit broadband available to them, but that accounts for only 17 percent of the overall US population. Contrast this with the next highest ranking country for deployments, South Korea, whose installations cover slightly less than 10 million people, fewer than the US, but have achieved 93 percent population coverage.

We are still at the very start of the gigabit revolution. Just 3.1 percent of the world's population are able to access gigabit internet currently, but those penetration levels are changing rapidly. New deployments are being reported all the time, and LTE and 5G installations are expected in the very near future. The impact on the day-to-day running of business networks will be transformative, powering an explosion in application innovation and disrupting business models.

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.

Lightning Fast Internet Is Coming - Are You Ready?

Steve Brown

Network capacity is the lifeblood of an enterprise — bandwidth enables business.

If you're ever in doubt, just recall what it's like when there is an outage or a major slow-down. Disgruntled employees, frustrated network pros ... it's no wonder that around half of IT staff from network or system admins to VP level and higher all cite network slow-downs as one of their biggest challenges.

Getting the most out of the network is a fine balancing act, so it's understandable that enterprises are always hungry for more bandwidth. Two out of three IT and network professionals expect bandwidth usage to increase by up to 50% by the end of 2017.

Thankfully there are great leaps of progress afoot when it comes to broadband connectivity. Bandwidth availability issues that enterprises routinely face could become a thing of the past. We are on the cusp of a great surge of capacity as gigabit speed internet becomes a reality. In fact, there are already more than 600 deployments of gigabit internet globally.

The mind-boggling speed of gigabit internet is often explained in the number of seconds it would take to, say, download an HD movie (less than 5). But while we can all appreciate the entertainment possibilities, let's not forget its importance from an enterprise perspective. Speeds and capacity on this scale have the power to transform businesses and disrupt business models, as we are already seeing with the advent of virtual reality, augmented reality and the IoT.

Wouldn't it be great to track the development of super-fast broadband deployments as they happen? Viavi thought so. Using publicly available data, we built a visual, living database of gigabit deployments around the world: the Gigabit Monitor. Here's what we found.

The Need for Speed

While fiber makes up the lion's share of deployments (no surprise), there is strong evidence pointing to the scale of cellular gigabit connectivity changing significantly. Currently, we know that 25 mobile operators are lab-testing 5G, and 12 of those have progressed to field trials.

It's fascinating to speculate how such a shift will change public services, manufacturing and retail to name but a few industries. 5G is coming and businesses need to be ready for it.

Digital Transformation

Gigabit deployments have risen at a rate of 72 percent in the past year. This is higher than even we expected. Businesses who are interested in checking the progress of gigabit connectivity by region, provider or technology type can now easily do so. As businesses increasingly adopt agile methods and implement digital transformation, gigabit speeds will be a key enabler.

A Mixed Bag for US Business

Globally, over 219 million people have gigabit speeds available to them. The US leads the way with around 57 percent of deployments. This translates to over 56 million people in the US having gigabit broadband available to them, but that accounts for only 17 percent of the overall US population. Contrast this with the next highest ranking country for deployments, South Korea, whose installations cover slightly less than 10 million people, fewer than the US, but have achieved 93 percent population coverage.

We are still at the very start of the gigabit revolution. Just 3.1 percent of the world's population are able to access gigabit internet currently, but those penetration levels are changing rapidly. New deployments are being reported all the time, and LTE and 5G installations are expected in the very near future. The impact on the day-to-day running of business networks will be transformative, powering an explosion in application innovation and disrupting business models.

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.