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Understanding "Last Mile" WFH Connectivity

Paul Davenport
AppNeta

The mass rush to work-from-home (WFH) that took place back in the spring was a shock to the system for many enterprise networks. But with summer closing out and the prospects of a near-term return to office-centric workflows looking increasingly slim, enterprise IT teams that haven't gotten comfortable with their "new normal" need to start making changes fast.

But getting familiar with network connections your team doesn't own or control can be tricky for enterprise IT who are accustomed to managing a primarily branch-office footprint. These teams are relying on connectivity beyond the traditional network edge to give their users access to network resources and the apps they need to stay productive.

Unlike commercial connectivity, these residential connections — aka the "last mile" links between residential workstations and the network edge — aren't backed by ISP SLAs that guarantee upload and download speeds. Instead, this access is delivered "best effort," meaning any number of factors could impact how much network capacity is actually delivered out to a residential work station.

To begin with, residential connections don't enjoy nearly the network speeds of the office, putting workers at a disadvantage where performance is involved before random variances in last-mile delivery come into play.

But what may be surprising is just how this variance plays out over a widely-distributed enterprise footprint.

To help get ahead of issues impacting WFH users, teams need to first understand what they're working with when it comes to the new stakeholders involved in connecting end users with corporate network resources. This includes gaining a true understanding of the performance of ISPs, for instance, responsible for that last mile connectivity at each home location, as well as ensuring that the amount of capacity delivered to an individual user's home is adequate for the job.

When we at AppNeta closed our Boston and Vancouver offices back in March, we conducted an initial survey of our own WFH network connections — a practice we recommend every systems team does to help gain a baseline of expectations for network performance out to critical team members. We found that not only are most users' residential ISP offerings far off the capacity levels they're used to experiencing in-office, they're not even getting the full download and upload speeds that they've contracted for.



Compounded with the stress on the user's home network from non-business apps used by others throughout the household, this misalignment between expected and delivered capacity can sink worker productivity across teams.

This last mile, potentially between the enterprise network edge and a user's residential workstation, but more likely with the residential ISP, is where the bulk of performance issues arise in the WFH era, as reported by our own network management team and our enterprise customers. And while IT teams may not own, manage, or really control those residential last miles, they can still gain visibility into how that connection is performing to help resolve issues before they ripple across departments.

Teams need to understand what these variances are going to be so that even if they can't regain those lost seconds of dwell time because of the limitations on that last-mile connectivity, they at least have the data to baseline end-user expectations and inform improvements (and expected results) going forward. That means not only getting to the root of the problem (and proving innocence) fast, but also having the data handy to seek out resolution with the appropriate stakeholders.

Paul Davenport is Marketing Communications Manager at AppNeta

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Understanding "Last Mile" WFH Connectivity

Paul Davenport
AppNeta

The mass rush to work-from-home (WFH) that took place back in the spring was a shock to the system for many enterprise networks. But with summer closing out and the prospects of a near-term return to office-centric workflows looking increasingly slim, enterprise IT teams that haven't gotten comfortable with their "new normal" need to start making changes fast.

But getting familiar with network connections your team doesn't own or control can be tricky for enterprise IT who are accustomed to managing a primarily branch-office footprint. These teams are relying on connectivity beyond the traditional network edge to give their users access to network resources and the apps they need to stay productive.

Unlike commercial connectivity, these residential connections — aka the "last mile" links between residential workstations and the network edge — aren't backed by ISP SLAs that guarantee upload and download speeds. Instead, this access is delivered "best effort," meaning any number of factors could impact how much network capacity is actually delivered out to a residential work station.

To begin with, residential connections don't enjoy nearly the network speeds of the office, putting workers at a disadvantage where performance is involved before random variances in last-mile delivery come into play.

But what may be surprising is just how this variance plays out over a widely-distributed enterprise footprint.

To help get ahead of issues impacting WFH users, teams need to first understand what they're working with when it comes to the new stakeholders involved in connecting end users with corporate network resources. This includes gaining a true understanding of the performance of ISPs, for instance, responsible for that last mile connectivity at each home location, as well as ensuring that the amount of capacity delivered to an individual user's home is adequate for the job.

When we at AppNeta closed our Boston and Vancouver offices back in March, we conducted an initial survey of our own WFH network connections — a practice we recommend every systems team does to help gain a baseline of expectations for network performance out to critical team members. We found that not only are most users' residential ISP offerings far off the capacity levels they're used to experiencing in-office, they're not even getting the full download and upload speeds that they've contracted for.



Compounded with the stress on the user's home network from non-business apps used by others throughout the household, this misalignment between expected and delivered capacity can sink worker productivity across teams.

This last mile, potentially between the enterprise network edge and a user's residential workstation, but more likely with the residential ISP, is where the bulk of performance issues arise in the WFH era, as reported by our own network management team and our enterprise customers. And while IT teams may not own, manage, or really control those residential last miles, they can still gain visibility into how that connection is performing to help resolve issues before they ripple across departments.

Teams need to understand what these variances are going to be so that even if they can't regain those lost seconds of dwell time because of the limitations on that last-mile connectivity, they at least have the data to baseline end-user expectations and inform improvements (and expected results) going forward. That means not only getting to the root of the problem (and proving innocence) fast, but also having the data handy to seek out resolution with the appropriate stakeholders.

Paul Davenport is Marketing Communications Manager at AppNeta

Hot Topics

The Latest

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...