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Using Monitoring to Bridge the Gap Between Process and Technology

Ivar Sagemo

For several decades now, IT infrastructure has been the fundamental engine of business processes. Going from the abstract idea of a business process to a smoothly running technical implementation of that process ought to be straightforward, right? But as we know, such is not the case. Technology has improved by leaps and bounds, but our ability to leverage it to our best business effect isn't nearly as well optimized. Too often, IT has become its own little world, all but divorced from the business side and unable to take into account business goals and strategies in the way services are managed.

Consider, for instance, solutions such as Microsoft BizTalk and the way BizTalk-driven processes are typically implemented:

• Company requirements translate into logistic rules and requests. For retail stores for example, packages need to be shipped on time or warehouse stores supplemented adequately. Ideally at the lowest cost and the highest reliability.

• The flow of information is then determined and logical rights are assigned to make that happen. When a company specifies where shipments should go and which are rush orders, as the shipments move towards a destination, updates must be provided to a website. Business logistics such as these take on a technical slant when processes are implemented.

Instead of focusing on whether information is actually getting from one location to another in a timely and accurate manner, monitoring services generally miss the mark and revolve around issues such as the CPU utilization of underlying systems, available storage of associated databases, etc.

Also problematic is that thresholds are typically determined arbitrarily and don't always correlate to actual success or failure of the business process it was derived from. This has the effect of making it harder and slower to solve problems when they occur.

It's also an essentially reactive approach: "Wait until something goes wrong and then fix it." Much better would be: "Anticipate what is likely to go wrong, and ensure that it doesn't."

And what happens when the process changes?

Imagine, for instance, that a new business system is brought in-house such as a new sales tool, involving a whole new data source. How easy or difficult is it for a BizTalk monitoring system to adapt in parallel? Usually, a series of manual modifications are needed — possibly by outside consultants specializing in BizTalk. This is slow, cumbersome, and operationally costly. It also introduces the possibility of inadvertent mistakes that could easily compromise monitoring when the whole point was to improve it.

Building a Better Mousetrap

Instead of that all-too-familiar paradigm, let's imagine something quite different.

• Smart discovery. What if BizTalk monitoring systems, once deployed, could automatically discover the business processes that led to the IT decision such as how information flows, critical dependencies, normal performance at different times and under different conditions — and thus establish accurate thresholds needed to ensure effective performance?

• Intuitive design. What if, instead of having to call in a consultant when things go belly-up, IT people could look at a topological map and understand the issue themselves? What if they could drill down into that map, getting specific technical insight needed to fix the problem quickly?

• Out-of-box best practices. What if your BizTalk monitoring system already knew the kinds of monitoring problems other companies have faced, and the best ways to avoid those problems? What if your organization could benefit from that kind of insight without having to call in a consultant?

While, the goal of every organization is to take those great ideas developed at the process stage and carry them through to the final IT implementation, we know that solutions change after initial deployment: new processes, new partners and changing business demands mean processes shift as the journey toward final implementation moves along. We'd like to think that monitoring could help in that journey.

Ivar Sagemo is CEO of AIMS Innovation.

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Using Monitoring to Bridge the Gap Between Process and Technology

Ivar Sagemo

For several decades now, IT infrastructure has been the fundamental engine of business processes. Going from the abstract idea of a business process to a smoothly running technical implementation of that process ought to be straightforward, right? But as we know, such is not the case. Technology has improved by leaps and bounds, but our ability to leverage it to our best business effect isn't nearly as well optimized. Too often, IT has become its own little world, all but divorced from the business side and unable to take into account business goals and strategies in the way services are managed.

Consider, for instance, solutions such as Microsoft BizTalk and the way BizTalk-driven processes are typically implemented:

• Company requirements translate into logistic rules and requests. For retail stores for example, packages need to be shipped on time or warehouse stores supplemented adequately. Ideally at the lowest cost and the highest reliability.

• The flow of information is then determined and logical rights are assigned to make that happen. When a company specifies where shipments should go and which are rush orders, as the shipments move towards a destination, updates must be provided to a website. Business logistics such as these take on a technical slant when processes are implemented.

Instead of focusing on whether information is actually getting from one location to another in a timely and accurate manner, monitoring services generally miss the mark and revolve around issues such as the CPU utilization of underlying systems, available storage of associated databases, etc.

Also problematic is that thresholds are typically determined arbitrarily and don't always correlate to actual success or failure of the business process it was derived from. This has the effect of making it harder and slower to solve problems when they occur.

It's also an essentially reactive approach: "Wait until something goes wrong and then fix it." Much better would be: "Anticipate what is likely to go wrong, and ensure that it doesn't."

And what happens when the process changes?

Imagine, for instance, that a new business system is brought in-house such as a new sales tool, involving a whole new data source. How easy or difficult is it for a BizTalk monitoring system to adapt in parallel? Usually, a series of manual modifications are needed — possibly by outside consultants specializing in BizTalk. This is slow, cumbersome, and operationally costly. It also introduces the possibility of inadvertent mistakes that could easily compromise monitoring when the whole point was to improve it.

Building a Better Mousetrap

Instead of that all-too-familiar paradigm, let's imagine something quite different.

• Smart discovery. What if BizTalk monitoring systems, once deployed, could automatically discover the business processes that led to the IT decision such as how information flows, critical dependencies, normal performance at different times and under different conditions — and thus establish accurate thresholds needed to ensure effective performance?

• Intuitive design. What if, instead of having to call in a consultant when things go belly-up, IT people could look at a topological map and understand the issue themselves? What if they could drill down into that map, getting specific technical insight needed to fix the problem quickly?

• Out-of-box best practices. What if your BizTalk monitoring system already knew the kinds of monitoring problems other companies have faced, and the best ways to avoid those problems? What if your organization could benefit from that kind of insight without having to call in a consultant?

While, the goal of every organization is to take those great ideas developed at the process stage and carry them through to the final IT implementation, we know that solutions change after initial deployment: new processes, new partners and changing business demands mean processes shift as the journey toward final implementation moves along. We'd like to think that monitoring could help in that journey.

Ivar Sagemo is CEO of AIMS Innovation.

Hot Topics

The Latest

From smart factories and autonomous vehicles to real-time analytics and intelligent building systems, the demand for instant, local data processing is exploding. To meet these needs, organizations are leaning into edge computing. The promise? Faster performance, reduced latency and less strain on centralized infrastructure. But there's a catch: Not every network is ready to support edge deployments ...

Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

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