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As Remote Work Takes Off, Network Visibility Helps IT Keep Pace

Paul Davenport
AppNeta

While remote work policies have been gaining steam for the better part of the past decade across the enterprise space — driven in large part by more agile and scalable, cloud-delivered business solutions — recent events have pushed adoption into overdrive.

For starters, anxieties surrounding the global spread of the COVID-19 virus have encouraged business leaders to let employees collaborate via UCaaS and collaboration tools from remote locations rather than convene in group settings that could make workers vulnerable to exposure. But the remote work movement was gaining steam well before that, as factors like commuting and the environment have simply made allowing flexibility for how and where employees get the job done a more logical and cost-effective policy.

As a result, managing user experience at remote offices has become an integral part of the job for modern enterprise IT. But in most cases, when the number of remote locations the network supports increases, IT operations remain centrally located, as staffing a physical presence at each new office would eat into the cost savings and efficiency that cloud and SaaS tools are meant to enable. While these efficiencies are hugely beneficial to the business, they do fundamentally change the level of visibility IT used to have when teams were centralized and issues could be quickly addressed on-premises.

Without solutions that deliver visibility into remote locations or provide insight into traffic from those locations, IT can become overly dependent on end users to report app performance issues — and usually only after these problems have impacted performance. The trouble with this is that end users may be quick to blame the network for performance issues when the real culprit may be the app itself, not the underlying infrastructure.

When visibility into remote office performance is lacking, IT teams frequently end up wasting time and budget getting to the bottom of issues that are impacting users across the business. When dealing with poorly performing apps, not only do end users become unproductive and start missing deadlines, but IT often gets sidelined because they’re constantly putting out fires rather than getting strategic initiatives off the ground. This will Inevitably start to impact the reputation of the IT team, as performance issues become chronic and remote users are constantly frustrated.

Embracing Automation to Gain Visibility

With an automated monitoring strategy that can deliver a local perspective into issues hindering remote locations, IT can be proactively alerted to network and application performance problems before users are even impacted. This arms IT with the ability to quickly know if performance-impacting issues are caused by flaws with the enterprise infrastructure, service providers, connecting networks or the apps themselves.

Comprehensive visibility into the performance of every app, user, and location is also critical in helping IT ensure their network is equipped with the requirements necessary to support the new breed of cloud and SaaS tools users rely on most. This can help illuminate areas of the network where IT could leverage more cost-effective connectivity options like local Internet breakouts or SD-WAN connectivity instead of MPLS or other private circuits.

When IT can ensure they have complete visibility into their remote locations, they can more predictably ensure end users aren’t meaningfully impacted by performance issues, while also starting to think strategically about how to plan for the future. Visibility empowers teams to more predictably budget for projects and ensure they meet their goals on schedule, even allowing them to investigate and deliver more cost-effective connectivity at remote locations.

Paul Davenport is Marketing Communications Manager at AppNeta

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As Remote Work Takes Off, Network Visibility Helps IT Keep Pace

Paul Davenport
AppNeta

While remote work policies have been gaining steam for the better part of the past decade across the enterprise space — driven in large part by more agile and scalable, cloud-delivered business solutions — recent events have pushed adoption into overdrive.

For starters, anxieties surrounding the global spread of the COVID-19 virus have encouraged business leaders to let employees collaborate via UCaaS and collaboration tools from remote locations rather than convene in group settings that could make workers vulnerable to exposure. But the remote work movement was gaining steam well before that, as factors like commuting and the environment have simply made allowing flexibility for how and where employees get the job done a more logical and cost-effective policy.

As a result, managing user experience at remote offices has become an integral part of the job for modern enterprise IT. But in most cases, when the number of remote locations the network supports increases, IT operations remain centrally located, as staffing a physical presence at each new office would eat into the cost savings and efficiency that cloud and SaaS tools are meant to enable. While these efficiencies are hugely beneficial to the business, they do fundamentally change the level of visibility IT used to have when teams were centralized and issues could be quickly addressed on-premises.

Without solutions that deliver visibility into remote locations or provide insight into traffic from those locations, IT can become overly dependent on end users to report app performance issues — and usually only after these problems have impacted performance. The trouble with this is that end users may be quick to blame the network for performance issues when the real culprit may be the app itself, not the underlying infrastructure.

When visibility into remote office performance is lacking, IT teams frequently end up wasting time and budget getting to the bottom of issues that are impacting users across the business. When dealing with poorly performing apps, not only do end users become unproductive and start missing deadlines, but IT often gets sidelined because they’re constantly putting out fires rather than getting strategic initiatives off the ground. This will Inevitably start to impact the reputation of the IT team, as performance issues become chronic and remote users are constantly frustrated.

Embracing Automation to Gain Visibility

With an automated monitoring strategy that can deliver a local perspective into issues hindering remote locations, IT can be proactively alerted to network and application performance problems before users are even impacted. This arms IT with the ability to quickly know if performance-impacting issues are caused by flaws with the enterprise infrastructure, service providers, connecting networks or the apps themselves.

Comprehensive visibility into the performance of every app, user, and location is also critical in helping IT ensure their network is equipped with the requirements necessary to support the new breed of cloud and SaaS tools users rely on most. This can help illuminate areas of the network where IT could leverage more cost-effective connectivity options like local Internet breakouts or SD-WAN connectivity instead of MPLS or other private circuits.

When IT can ensure they have complete visibility into their remote locations, they can more predictably ensure end users aren’t meaningfully impacted by performance issues, while also starting to think strategically about how to plan for the future. Visibility empowers teams to more predictably budget for projects and ensure they meet their goals on schedule, even allowing them to investigate and deliver more cost-effective connectivity at remote locations.

Paul Davenport is Marketing Communications Manager at AppNeta

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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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...