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A Full Picture: Adding Business Context to IT's Puzzle Pieces

Matthew Carr

Think about the first puzzle you ever built. For me, it was a majestic picture of the Big Ben. There were hundreds of pieces scattered around, each with a place for me to find based on the picture on the box. Even with the picture as a guide, it was a daunting task that took hours. Now imagine building that puzzle without having the photo as a guide. It changes the game entirely. Today's IT teams are facing a similar challenge with managing hybrid-centric environments.

As the IT world has become more hybrid-centric, the big picture has gotten lost or is not known holistically by most trying to place their IT puzzle piece. Since hybrid is "the new normal," outdated operations will no longer suffice, and current IT management systems must be modernized to succeed in this new hybrid world where the big picture is always changing.

As machine and IT event data continue to become more complex – and massively abundant – IT departments are trying to manage a plethora of information. In many cases, IT departments – as well as business practice groups – manage IT data by silo, each concerned solely about their particular piece of the puzzle, and not focusing on the whole picture required to understand where their piece fits.

Placing IT Puzzle Pieces Without Context is Guesswork

Over the years, it has been common practice for large organizations to have IT teams working independently, where each individual team uses its own tools to monitor and manage specific data components. In other words, the networking team works independently from the help desk team, not sharing tools or information, for a very insular and antiquated approach.

Compounding the problem, organizations generally have an immense variety of data sources – sometimes as many as a dozen or more – including datacenter, application, end-user monitoring systems, and IT service management system. Each component (and team) – or puzzle piece – exists in its own silo, accessing only a limited-view of a small portion of the enterprise.

There were a variety of tools that worked reasonably well before companies evolved to a hybrid world. For instance, legacy monitoring tools were helpful in examining the components and applications within the datacenter, though were not designed to provide a more comprehensive view. Then came EUEM (End-User Experience Monitoring) tools, which were more proactive, but couldn't effectively provide critical information about the root-cause of issues. The benefit of domain monitoring tools was pinpointing root-cause, but offered limited functionality for other IT needs.

The combination of people working in silos, tools used with limited scope and ability, plus a hybrid environment all resulted in a very challenging equation. Now, companies are faced with increased data across multiple, unconnected platforms. Thus, teams working independently don't have any understanding of where their piece of the puzzle fits into the landscape, and are limited without any big-picture context. And tools that can only serve limited functions are inefficient, ineffective, and make it overly complicated to get results.

Picture an organization whose IT teams are trying to work in different departments, with information buried in different monitoring systems, who are monitoring different components and infrastructures. Using this disjointed approach, even if all monitoring systems report healthy, it is still no guarantee that they actually are. In this scenario, no one has a clear view of the entire enterprise, and no one is seeing significant problems – or potential problems – in any kind of structural context. IT teams are limited in what they can see or do, as they're operating with just pieces of information – a component in a silo – rather seeing the complete picture.

Reassembling an IT Puzzle That Changes Daily is Impossible

How can these IT professionals be expected to excel in this hybrid world when they're working in such compartmentalized and complicated conditions? It's a futile effort.

Instead, enterprises need to shift their approach from the inefficient, compartmentalized systems they're currently using, and become more holistic, comprehensive, and streamlined. Understanding how the IT landscape or picture changes on a daily basis is important to knowing how one's piece of the IT puzzle fits today. Providing real-time updates to the IT landscape so everyone is working to restore the same puzzle is important for achieving service levels required by any business.

Additionally, it is crucial that they adjust their mindset to be more proactive – anticipating and resolving potential issues before they're disruptive – rather than being reactive, and only acting after an end-user reports an issue.

It seems pretty straight-forward to say that proactive, comprehensive, swift, efficient and predictive processes are superior to outdated reactive, slow and compartmentalized systems. Yet, so many organizations are trapped in outdated models, unable to get a firm handle on their processes, let alone the IT puzzle pieces they're attempting to manage. It is all so complicated, making it difficult to navigate the variety of options for new monitoring tools that can handle an organization's IT management needs.

Self-Updating IT Landscape Pictures Keep Every Silo's Puzzle Piece in Place

Fortunately, more advanced IT environment discovery and monitoring solutions are becoming available. Savvy businesses are deploying systems that are change-aware and automatically discover and update the "big picture" of their inter-dependent IT environment, providing each team with a transparent view into how their piece contributes to the overall business. Moreover, they're implementing unified processes, investing in 360-degree views that unite their silos, and using the appropriate tools to analyze and manage their IT puzzle pieces. IT and business teams must work more holistically and collaboratively across departments so they're all building the same – ever changing – picture comprised of hundreds of puzzle pieces.

Now, thankfully, there are modern solutions that help organizations transition from the silo approach to a holistic environment no matter how complex or distributed one's hybrid environment becomes. Think about providing every person on your team with an always up-to-date picture for their IT landscape puzzle with a guide depicting each piece's exact place in that puzzle. This is available today. Using these solutions allows companies to elevate their systems, processes, and approaches to operate in a more productive, efficient, innovative, and successful manner.

Matthew Carr is Business Development Manager at Savision.

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

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For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

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New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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A Full Picture: Adding Business Context to IT's Puzzle Pieces

Matthew Carr

Think about the first puzzle you ever built. For me, it was a majestic picture of the Big Ben. There were hundreds of pieces scattered around, each with a place for me to find based on the picture on the box. Even with the picture as a guide, it was a daunting task that took hours. Now imagine building that puzzle without having the photo as a guide. It changes the game entirely. Today's IT teams are facing a similar challenge with managing hybrid-centric environments.

As the IT world has become more hybrid-centric, the big picture has gotten lost or is not known holistically by most trying to place their IT puzzle piece. Since hybrid is "the new normal," outdated operations will no longer suffice, and current IT management systems must be modernized to succeed in this new hybrid world where the big picture is always changing.

As machine and IT event data continue to become more complex – and massively abundant – IT departments are trying to manage a plethora of information. In many cases, IT departments – as well as business practice groups – manage IT data by silo, each concerned solely about their particular piece of the puzzle, and not focusing on the whole picture required to understand where their piece fits.

Placing IT Puzzle Pieces Without Context is Guesswork

Over the years, it has been common practice for large organizations to have IT teams working independently, where each individual team uses its own tools to monitor and manage specific data components. In other words, the networking team works independently from the help desk team, not sharing tools or information, for a very insular and antiquated approach.

Compounding the problem, organizations generally have an immense variety of data sources – sometimes as many as a dozen or more – including datacenter, application, end-user monitoring systems, and IT service management system. Each component (and team) – or puzzle piece – exists in its own silo, accessing only a limited-view of a small portion of the enterprise.

There were a variety of tools that worked reasonably well before companies evolved to a hybrid world. For instance, legacy monitoring tools were helpful in examining the components and applications within the datacenter, though were not designed to provide a more comprehensive view. Then came EUEM (End-User Experience Monitoring) tools, which were more proactive, but couldn't effectively provide critical information about the root-cause of issues. The benefit of domain monitoring tools was pinpointing root-cause, but offered limited functionality for other IT needs.

The combination of people working in silos, tools used with limited scope and ability, plus a hybrid environment all resulted in a very challenging equation. Now, companies are faced with increased data across multiple, unconnected platforms. Thus, teams working independently don't have any understanding of where their piece of the puzzle fits into the landscape, and are limited without any big-picture context. And tools that can only serve limited functions are inefficient, ineffective, and make it overly complicated to get results.

Picture an organization whose IT teams are trying to work in different departments, with information buried in different monitoring systems, who are monitoring different components and infrastructures. Using this disjointed approach, even if all monitoring systems report healthy, it is still no guarantee that they actually are. In this scenario, no one has a clear view of the entire enterprise, and no one is seeing significant problems – or potential problems – in any kind of structural context. IT teams are limited in what they can see or do, as they're operating with just pieces of information – a component in a silo – rather seeing the complete picture.

Reassembling an IT Puzzle That Changes Daily is Impossible

How can these IT professionals be expected to excel in this hybrid world when they're working in such compartmentalized and complicated conditions? It's a futile effort.

Instead, enterprises need to shift their approach from the inefficient, compartmentalized systems they're currently using, and become more holistic, comprehensive, and streamlined. Understanding how the IT landscape or picture changes on a daily basis is important to knowing how one's piece of the IT puzzle fits today. Providing real-time updates to the IT landscape so everyone is working to restore the same puzzle is important for achieving service levels required by any business.

Additionally, it is crucial that they adjust their mindset to be more proactive – anticipating and resolving potential issues before they're disruptive – rather than being reactive, and only acting after an end-user reports an issue.

It seems pretty straight-forward to say that proactive, comprehensive, swift, efficient and predictive processes are superior to outdated reactive, slow and compartmentalized systems. Yet, so many organizations are trapped in outdated models, unable to get a firm handle on their processes, let alone the IT puzzle pieces they're attempting to manage. It is all so complicated, making it difficult to navigate the variety of options for new monitoring tools that can handle an organization's IT management needs.

Self-Updating IT Landscape Pictures Keep Every Silo's Puzzle Piece in Place

Fortunately, more advanced IT environment discovery and monitoring solutions are becoming available. Savvy businesses are deploying systems that are change-aware and automatically discover and update the "big picture" of their inter-dependent IT environment, providing each team with a transparent view into how their piece contributes to the overall business. Moreover, they're implementing unified processes, investing in 360-degree views that unite their silos, and using the appropriate tools to analyze and manage their IT puzzle pieces. IT and business teams must work more holistically and collaboratively across departments so they're all building the same – ever changing – picture comprised of hundreds of puzzle pieces.

Now, thankfully, there are modern solutions that help organizations transition from the silo approach to a holistic environment no matter how complex or distributed one's hybrid environment becomes. Think about providing every person on your team with an always up-to-date picture for their IT landscape puzzle with a guide depicting each piece's exact place in that puzzle. This is available today. Using these solutions allows companies to elevate their systems, processes, and approaches to operate in a more productive, efficient, innovative, and successful manner.

Matthew Carr is Business Development Manager at Savision.

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...