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Why Government Agencies Aren't Ready to Return to the Office

Mike Marks
Riverbed

US government agencies are bringing more of their employees back into the office and implementing hybrid work schedules, but federal workers are worried that their agencies' IT architectures aren't built to handle the "new normal." They fear that the reactive, manual methods used by the current systems in dealing with user, IT architecture and application problems will degrade the user experience and negatively affect productivity.

In fact, according to a recent survey, many federal employees are concerned that they won't work as effectively back in the office as they did at home.

Employees Worry the User Experience Will Suffer

A Swish Data/Riverbed survey of federal IT workers, conducted in April and May by Market Connections, found that about half (47%) expect hybrid schedules that include teleworking two to four days a week to continue long-term, but that 52% think that the legacy IT and on-premises network architectures will struggle with the increased use of on-site collaboration tools such as Microsoft Teams and Zoom.

Those shortcomings manifest themselves in the user experience, the survey found. Forty-four percent of respondents are concerned that their user experience working in the office would fall short of their experience working from home. And a significant reason for the disconnect is the outdated methods agencies use to identify and quantify problems that arise with IT operations, and how those problems affect users.

A full 100% of survey respondents said it is at least somewhat important to measure the employees' user experience of productivity capabilities. But 87% said their agencies still rely — reactively — on waiting for help desk tickets to be generated before addressing problems. In fact, 51% rely on user phone calls as the primary means of quantifying problems.

The result, according to 59% of the feds surveyed, is that agencies aren't aware of the impact that changes in their IT environments are having. They're not measuring business-function productivity in terms of labor costs, latency or rates of success, all of which are tied to user experience. A majority of respondents said that although their organizations compare the business transaction productivity of teleworkers to that of in-office workers, they do so only partially. And measuring and comparing employee productivity is less likely to happen at civilian agencies than within the Department of Defense.

Unified Observability Takes a Proactive Approach

In light of the realities of hybrid work—with flexible home/office schedules, a greater reliance on collaboration tools and the shift toward greater use of digital workflows — federal employees are looking for a balance between collaborative tools and in-person needs.

A proactive approach that combines comprehensive network visibility and effective monitoring tools can provide a clear view of the user experience, which can enable both increased productivity and enhanced user satisfaction.

A Unified Observability platform can provide full-fidelity data from across the enterprise, capturing all transactions, packets and workflows. Using automated artificial intelligence and machine learning tools, it can prioritize actions to help enable cross-domain collaboration and coordination. While greatly improving the ability of IT teams to identify and remediate any problems (ranging from cyberattacks to workflow bottlenecks), Unified Observability enables IT teams to improve service delivery.

The higher quality of IT service will improve employee performance and the delivery of services to constituents and other stakeholders by allowing employees to more seamlessly perform their jobs, whether working from home or in the office. The visibility provided by a Unified Observability platform allows multiple teams across the enterprise to identify and analyze user issues while making use of automation to quickly resolve any problems.

"Government from Anywhere" as a Reality

The impact of the COVID-19 pandemic on top of digital transformations that were already underway has forever changed how agencies operate. The concept of "government from anywhere" is a widespread goal, but it requires a cultural change at most agencies. The survey recipients agreed, with 87% saying that their agency culture played a growing or significant role in driving change.

Abandoning inefficient, reactive methods of measuring the user experience in favor of enterprise-wide visibility with proactive monitoring and analysis will improve user experiences regardless of their location, while also boosting agency performance overall.

Mike Marks is VP of Product Marketing at Riverbed

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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 ...

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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 ...

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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 ...

Why Government Agencies Aren't Ready to Return to the Office

Mike Marks
Riverbed

US government agencies are bringing more of their employees back into the office and implementing hybrid work schedules, but federal workers are worried that their agencies' IT architectures aren't built to handle the "new normal." They fear that the reactive, manual methods used by the current systems in dealing with user, IT architecture and application problems will degrade the user experience and negatively affect productivity.

In fact, according to a recent survey, many federal employees are concerned that they won't work as effectively back in the office as they did at home.

Employees Worry the User Experience Will Suffer

A Swish Data/Riverbed survey of federal IT workers, conducted in April and May by Market Connections, found that about half (47%) expect hybrid schedules that include teleworking two to four days a week to continue long-term, but that 52% think that the legacy IT and on-premises network architectures will struggle with the increased use of on-site collaboration tools such as Microsoft Teams and Zoom.

Those shortcomings manifest themselves in the user experience, the survey found. Forty-four percent of respondents are concerned that their user experience working in the office would fall short of their experience working from home. And a significant reason for the disconnect is the outdated methods agencies use to identify and quantify problems that arise with IT operations, and how those problems affect users.

A full 100% of survey respondents said it is at least somewhat important to measure the employees' user experience of productivity capabilities. But 87% said their agencies still rely — reactively — on waiting for help desk tickets to be generated before addressing problems. In fact, 51% rely on user phone calls as the primary means of quantifying problems.

The result, according to 59% of the feds surveyed, is that agencies aren't aware of the impact that changes in their IT environments are having. They're not measuring business-function productivity in terms of labor costs, latency or rates of success, all of which are tied to user experience. A majority of respondents said that although their organizations compare the business transaction productivity of teleworkers to that of in-office workers, they do so only partially. And measuring and comparing employee productivity is less likely to happen at civilian agencies than within the Department of Defense.

Unified Observability Takes a Proactive Approach

In light of the realities of hybrid work—with flexible home/office schedules, a greater reliance on collaboration tools and the shift toward greater use of digital workflows — federal employees are looking for a balance between collaborative tools and in-person needs.

A proactive approach that combines comprehensive network visibility and effective monitoring tools can provide a clear view of the user experience, which can enable both increased productivity and enhanced user satisfaction.

A Unified Observability platform can provide full-fidelity data from across the enterprise, capturing all transactions, packets and workflows. Using automated artificial intelligence and machine learning tools, it can prioritize actions to help enable cross-domain collaboration and coordination. While greatly improving the ability of IT teams to identify and remediate any problems (ranging from cyberattacks to workflow bottlenecks), Unified Observability enables IT teams to improve service delivery.

The higher quality of IT service will improve employee performance and the delivery of services to constituents and other stakeholders by allowing employees to more seamlessly perform their jobs, whether working from home or in the office. The visibility provided by a Unified Observability platform allows multiple teams across the enterprise to identify and analyze user issues while making use of automation to quickly resolve any problems.

"Government from Anywhere" as a Reality

The impact of the COVID-19 pandemic on top of digital transformations that were already underway has forever changed how agencies operate. The concept of "government from anywhere" is a widespread goal, but it requires a cultural change at most agencies. The survey recipients agreed, with 87% saying that their agency culture played a growing or significant role in driving change.

Abandoning inefficient, reactive methods of measuring the user experience in favor of enterprise-wide visibility with proactive monitoring and analysis will improve user experiences regardless of their location, while also boosting agency performance overall.

Mike Marks is VP of Product Marketing at Riverbed

The Latest

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.

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 ...