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Ensuring Business Continuity within the Borderless Enterprise in 2015

Bruce Kosbab

The borderless enterprise will become a topic of increasing prevalence in 2015. This phenomenon is being driven by the adoption of cloud, mobile devices and wireless access. The underlying technologies have acted as a catalyst for the transformation currently taking place in what has traditionally been thought of as the enterprise network. As far as the enterprise itself is concerned, the perimeters are disappearing.

As borderless enterprises proliferate, IT teams are experiencing new difficulties in ensuring Quality of Experience while continuing to support the business objectives of their workforce.

Cloud technologies, particularly Software-as-a-Service (SaaS) applications, have enabled non-IT groups within the enterprise to treat the cloud like a veritable IT vending machine. In a borderless enterprise, business operations teams, sales, marketing, manufacturing, HR and the line of business groups, can procure and implement their own applications, often without IT involvement.

This dynamic is a blessing and a curse for network teams within enterprises. With this newfound flexibility comes often-overlooked challenges and hurdles for IT teams. Business users are accessing applications, hosted in the cloud and purchased by enterprise business executives (not IT), while using their own devices to access those applications, over third-party infrastructure, which IT neither owns nor manages. All of this is going on and IT is still responsible for ensuring the end-user experience of all of those users, regardless of how, when, where and what applications they are using.

The five greatest challenges for ensuring Quality of Experience in a borderless enterprise include:

1. IT is caught unaware

Once upon a time, new application deployments were well planned, with change management processes, user acceptance testing and organization-wide communications. Today, this is no longer the case. End users bypass the traditional IT process because they can, resulting in faster deployment and, arguably, increased business efficiency. Yet when problems occur, the network team is still required to solve them even though they may have never initiated the deployment..

2. The blame game intensifies

Organizations often look for a scapegoat when things go wrong. In a borderless enterprise, finding someone to blame becomes more complex because users are now involved in choosing and deploying applications and services without input from IT teams. This leads to longer problem resolution times due to less clarity of the root cause.

3. Heightened complexity for enterprise IT

Current technology trends, user mobility and behavior drive IT complexity. While the cloud can simplify the enterprise, the ease with which business users can deploy new technology introduces much more complexity in the delivery chain than ever before.

4. Reduced visibility

IT teams do not have the same level of visibility in managing the end-user experience of cloud applications compared with on-premise applications. Applications that once ran inside a controlled corporate network are now running in any number of locations in the cloud. Their performance relies on the best-effort nature of the Internet, making it difficult for network teams to gather the necessary data to address application and network problems. Contributing to the blindness is that mobile users use third-party networks, which IT departments have no visibility into.

5. Many problems can’t be solved with a product

Many problems can’t be solved with just the product. Instead of simply improving the speed at which problems are found and fixed, organizations need to reduce overall occurrences. The key is to strategically choose tool vendors and service providers, create processes for adopting cloud applications, instill proactive management procedures, change the design of the enterprise architecture and acquire new IT skillsets.

To evolve along with the borderless enterprise of 2015, organizations need to commit to measuring true Quality of Experience for end-users, evaluating service level agreements (SLAs) of SaaS providers, establishing standard operating procedures for the adoption of cloud technologies and applications, and choosing tools that work harmoniously within the existing ecosystem and support primary IT objectives.

Bruce Kosbab is CTO of Fluke Networks.

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Ensuring Business Continuity within the Borderless Enterprise in 2015

Bruce Kosbab

The borderless enterprise will become a topic of increasing prevalence in 2015. This phenomenon is being driven by the adoption of cloud, mobile devices and wireless access. The underlying technologies have acted as a catalyst for the transformation currently taking place in what has traditionally been thought of as the enterprise network. As far as the enterprise itself is concerned, the perimeters are disappearing.

As borderless enterprises proliferate, IT teams are experiencing new difficulties in ensuring Quality of Experience while continuing to support the business objectives of their workforce.

Cloud technologies, particularly Software-as-a-Service (SaaS) applications, have enabled non-IT groups within the enterprise to treat the cloud like a veritable IT vending machine. In a borderless enterprise, business operations teams, sales, marketing, manufacturing, HR and the line of business groups, can procure and implement their own applications, often without IT involvement.

This dynamic is a blessing and a curse for network teams within enterprises. With this newfound flexibility comes often-overlooked challenges and hurdles for IT teams. Business users are accessing applications, hosted in the cloud and purchased by enterprise business executives (not IT), while using their own devices to access those applications, over third-party infrastructure, which IT neither owns nor manages. All of this is going on and IT is still responsible for ensuring the end-user experience of all of those users, regardless of how, when, where and what applications they are using.

The five greatest challenges for ensuring Quality of Experience in a borderless enterprise include:

1. IT is caught unaware

Once upon a time, new application deployments were well planned, with change management processes, user acceptance testing and organization-wide communications. Today, this is no longer the case. End users bypass the traditional IT process because they can, resulting in faster deployment and, arguably, increased business efficiency. Yet when problems occur, the network team is still required to solve them even though they may have never initiated the deployment..

2. The blame game intensifies

Organizations often look for a scapegoat when things go wrong. In a borderless enterprise, finding someone to blame becomes more complex because users are now involved in choosing and deploying applications and services without input from IT teams. This leads to longer problem resolution times due to less clarity of the root cause.

3. Heightened complexity for enterprise IT

Current technology trends, user mobility and behavior drive IT complexity. While the cloud can simplify the enterprise, the ease with which business users can deploy new technology introduces much more complexity in the delivery chain than ever before.

4. Reduced visibility

IT teams do not have the same level of visibility in managing the end-user experience of cloud applications compared with on-premise applications. Applications that once ran inside a controlled corporate network are now running in any number of locations in the cloud. Their performance relies on the best-effort nature of the Internet, making it difficult for network teams to gather the necessary data to address application and network problems. Contributing to the blindness is that mobile users use third-party networks, which IT departments have no visibility into.

5. Many problems can’t be solved with a product

Many problems can’t be solved with just the product. Instead of simply improving the speed at which problems are found and fixed, organizations need to reduce overall occurrences. The key is to strategically choose tool vendors and service providers, create processes for adopting cloud applications, instill proactive management procedures, change the design of the enterprise architecture and acquire new IT skillsets.

To evolve along with the borderless enterprise of 2015, organizations need to commit to measuring true Quality of Experience for end-users, evaluating service level agreements (SLAs) of SaaS providers, establishing standard operating procedures for the adoption of cloud technologies and applications, and choosing tools that work harmoniously within the existing ecosystem and support primary IT objectives.

Bruce Kosbab is CTO of Fluke Networks.

Hot Topics

The Latest

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

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