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Gigabit Internet is Coming - How Will You Make the Most of IT?

Steve Brown

As recently discussed in a blog on APMdigest, gigabit internet deployments are picking up speed (no pun intended) as they make their way to businesses and consumers around the globe. In the past year alone, deployments have risen at a rate of 72 percent as tracked by the Gigabit Monitor, bringing access to gigabit internet to more than 219 million people worldwide. This is good news for enterprises of all kinds.

Gigabit speeds and new technologies are driving new capabilities and even more opportunities to innovate and differentiate. Faster compute, new applications and more storage are all working together to enable greater efficiency and greater power. Yet with opportunity comes complexity.

Network traffic growth continues to defy expectations, and enterprise IT departments are faced with the task of meeting the demand for bandwidth. More than just the volume of traffic, however, there is an evolving mix of data traffic — including encrypted video which is expected to account for more than 65 percent of all business network traffic by 2020, according to Cisco's Visual Networking Index. And when you factor in hybrid cloud environments and the rapidly growing Internet of Things (IoT), it's no wonder that managing networks and applications is more complex than ever.

So how should businesses prepare for gigabit internet to make sure they are realizing its full potential? And what can IT teams do to meet end-user expectations when migrating to higher speed networks?

Full Speed Ahead

The key to successful migration to gigabit is preparation. Higher speeds mean more data throughput, which puts more strain on your network. Opening the internet floodgates without a strategic plan could compromise the health and performance of your workloads, not to mention the security of your entire network.

First, be sure to evaluate the condition of your network infrastructure to determine if it's robust enough to handle increased workloads. Here are four critical questions to assess your network preparedness:

1. Have you benchmarked normal bandwidth demand and application response times for the organization?

2. Are you monitoring bandwidth demand changes over time from users and applications?

3. Do you have sufficient excess capacity to support the demands of virtual and underlying physical environments?

4. Is the operating software up-to-date with the latest revisions?

Based upon answers to the above questions, you may need to adjust conditions that you're tracking or make upgrades in your IT infrastructure to ensure it is up to the task.

Second, take a close look at the state of your security defenses. As network users consume more data, your exposure to viruses, ransomware and DDoS attacks will increase proportionately. How well does your intrusion-detection system (IDS) handle encrypted data traffic? Do you have sufficient protection in place against cyberattacks, including all the latest patches and updates? It may seem obvious, but often it's the little things that are overlooked.

Third, keep a watchful eye on your network with the latest monitoring tools. Most legacy monitoring and management systems measure latency from an end user's perspective to the applicable web service, but not all issues will be immediately apparent to users. Others simply report uptime and availability of a physical piece of infrastructure.

Yet, in order to see how applications and related services are really performing, it's important to maintain comprehensive visibility and control of network infrastructure. This real-time visibility allows IT teams to recognize unusual traffic behavior or anomalies much more quickly to head off serious performance issues or security threats. Moreover, the ability to correlate data metrics in intelligent ways can even foreshadow risks that a critical service will begin to face in the coming hours, days or weeks.

And finally, just because your enterprise network migrates to higher speeds, you can't throw service level agreements (SLAs) out the window. Access to gigabit internet speeds, coupled with the proliferation of business applications based on the storage and compute power of the cloud, such as Amazon Web Services and Microsoft Azure, is driving even greater demand. Your IT team still needs to troubleshoot performance and manage quality of experience for these burgeoning workloads, so be sure to factor this growth into the SLA.

Moving forward, the transformative power of high-speed internet is powering an explosion in disruptive innovation and business applications. With the right strategy and preparation, you can take full advantage of the potential that gigabit access has to offer, while preventing harmful impact on the day-to-day running of your business network.

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.

Gigabit Internet is Coming - How Will You Make the Most of IT?

Steve Brown

As recently discussed in a blog on APMdigest, gigabit internet deployments are picking up speed (no pun intended) as they make their way to businesses and consumers around the globe. In the past year alone, deployments have risen at a rate of 72 percent as tracked by the Gigabit Monitor, bringing access to gigabit internet to more than 219 million people worldwide. This is good news for enterprises of all kinds.

Gigabit speeds and new technologies are driving new capabilities and even more opportunities to innovate and differentiate. Faster compute, new applications and more storage are all working together to enable greater efficiency and greater power. Yet with opportunity comes complexity.

Network traffic growth continues to defy expectations, and enterprise IT departments are faced with the task of meeting the demand for bandwidth. More than just the volume of traffic, however, there is an evolving mix of data traffic — including encrypted video which is expected to account for more than 65 percent of all business network traffic by 2020, according to Cisco's Visual Networking Index. And when you factor in hybrid cloud environments and the rapidly growing Internet of Things (IoT), it's no wonder that managing networks and applications is more complex than ever.

So how should businesses prepare for gigabit internet to make sure they are realizing its full potential? And what can IT teams do to meet end-user expectations when migrating to higher speed networks?

Full Speed Ahead

The key to successful migration to gigabit is preparation. Higher speeds mean more data throughput, which puts more strain on your network. Opening the internet floodgates without a strategic plan could compromise the health and performance of your workloads, not to mention the security of your entire network.

First, be sure to evaluate the condition of your network infrastructure to determine if it's robust enough to handle increased workloads. Here are four critical questions to assess your network preparedness:

1. Have you benchmarked normal bandwidth demand and application response times for the organization?

2. Are you monitoring bandwidth demand changes over time from users and applications?

3. Do you have sufficient excess capacity to support the demands of virtual and underlying physical environments?

4. Is the operating software up-to-date with the latest revisions?

Based upon answers to the above questions, you may need to adjust conditions that you're tracking or make upgrades in your IT infrastructure to ensure it is up to the task.

Second, take a close look at the state of your security defenses. As network users consume more data, your exposure to viruses, ransomware and DDoS attacks will increase proportionately. How well does your intrusion-detection system (IDS) handle encrypted data traffic? Do you have sufficient protection in place against cyberattacks, including all the latest patches and updates? It may seem obvious, but often it's the little things that are overlooked.

Third, keep a watchful eye on your network with the latest monitoring tools. Most legacy monitoring and management systems measure latency from an end user's perspective to the applicable web service, but not all issues will be immediately apparent to users. Others simply report uptime and availability of a physical piece of infrastructure.

Yet, in order to see how applications and related services are really performing, it's important to maintain comprehensive visibility and control of network infrastructure. This real-time visibility allows IT teams to recognize unusual traffic behavior or anomalies much more quickly to head off serious performance issues or security threats. Moreover, the ability to correlate data metrics in intelligent ways can even foreshadow risks that a critical service will begin to face in the coming hours, days or weeks.

And finally, just because your enterprise network migrates to higher speeds, you can't throw service level agreements (SLAs) out the window. Access to gigabit internet speeds, coupled with the proliferation of business applications based on the storage and compute power of the cloud, such as Amazon Web Services and Microsoft Azure, is driving even greater demand. Your IT team still needs to troubleshoot performance and manage quality of experience for these burgeoning workloads, so be sure to factor this growth into the SLA.

Moving forward, the transformative power of high-speed internet is powering an explosion in disruptive innovation and business applications. With the right strategy and preparation, you can take full advantage of the potential that gigabit access has to offer, while preventing harmful impact on the day-to-day running of your business network.

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.