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The State of Application Modernization

Alisha Marfatia
EvolveWare

As businesses continue to rely heavily on technology to drive growth and innovation, the importance of modernizing outdated applications has become a top priority for CIOs and IT teams. With this in mind, EvolveWare commissioned an independent survey to gain current insights into IT teams' strategies and preparedness for modernization initiatives, revealing some surprising contradictions to common assumptions around modernization priorities and goals. It has also highlighted a curious disconnect between IT leaders' perception and the reality of their overall readiness, their ability to secure legacy talent, and the availability of the much-sought-after technology capabilities.

Jump to infographic below

Key findings include:

Confidence in understanding of applications wanes as projects progress

A comparison of the confidence in knowledge of applications being modernized between those who have not yet begun their modernization projects (41% very confident) to those who have already begun projects (28% very confident) reveals a notable drop. This is likely an indication that organizations only start to realize the level of knowledge needed for these efforts after they execute on the project plans.

Many respondents also base their confidence on having personnel with knowledge of these legacy systems. This is a clear blindspot for IT leaders, as a full 81% of respondents say they currently have — or anticipate — challenges hiring and/or retaining legacy programming talent. This shortage of specialized IT talent will only continue to grow as employees retire and expertise in legacy systems continues to decline.

IT Teams and the rest of the C-Suite may not be aligned on modernization goals

The number one modernization motivation for IT team respondents is boosting employee productivity (40%). This is opposed to commonly cited rationales such as improving customer experience (29%) and migrating to the cloud (22%). However when looking at success measures, increasing business efficiency is in the bottom two chosen, which boosting employee productivity would typically be related to. This discrepancy seems to imply that while IT teams are looking to address challenges they face with maintaining legacy applications, possibly due to lack of documentation and/or lack of qualified personnel, they must also justify these projects in terms that are important to business leadership.

Reasons most often cited by the C-Suite for modernization are directly related to increasing revenue and profits, such as moving to the cloud to improve customer experience and reduce costs. The disconnect indicates that IT teams, who have their own modernization motivations, must find ways to align with the C-Suite who are defining tangible measures of success, prior to executing on these projects.

IT teams lack of awareness and access to modern tools

Most respondents don't believe they have access to the capabilities they want. For example, more than half would like to automate code transformation and business rules extraction (BRE) to a large degree, and 40% want to automate application documentation creation. Similarly, 64% believe freezing code during the modernization process will have significant business and financial consequences, and a full 59% say the ability to modernize without freezing code is on their technology wish list, making it the top most requested modernization capability. Yet while these, and other technologies on their wish lists, are available in the current modernization market, no more than 31% of IT leaders say they have access to them.

The ability to successfully modernize will be a key differentiator for businesses as they navigate the ever-evolving digital landscape. While the process can be complex and challenging, insights into potential blind spots and disconnects can help IT leaders develop more effective strategies and make the most of their available resources and technological advancements.

Alisha Marfatia is a Product Strategist at EvolveWare

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The State of Application Modernization

Alisha Marfatia
EvolveWare

As businesses continue to rely heavily on technology to drive growth and innovation, the importance of modernizing outdated applications has become a top priority for CIOs and IT teams. With this in mind, EvolveWare commissioned an independent survey to gain current insights into IT teams' strategies and preparedness for modernization initiatives, revealing some surprising contradictions to common assumptions around modernization priorities and goals. It has also highlighted a curious disconnect between IT leaders' perception and the reality of their overall readiness, their ability to secure legacy talent, and the availability of the much-sought-after technology capabilities.

Jump to infographic below

Key findings include:

Confidence in understanding of applications wanes as projects progress

A comparison of the confidence in knowledge of applications being modernized between those who have not yet begun their modernization projects (41% very confident) to those who have already begun projects (28% very confident) reveals a notable drop. This is likely an indication that organizations only start to realize the level of knowledge needed for these efforts after they execute on the project plans.

Many respondents also base their confidence on having personnel with knowledge of these legacy systems. This is a clear blindspot for IT leaders, as a full 81% of respondents say they currently have — or anticipate — challenges hiring and/or retaining legacy programming talent. This shortage of specialized IT talent will only continue to grow as employees retire and expertise in legacy systems continues to decline.

IT Teams and the rest of the C-Suite may not be aligned on modernization goals

The number one modernization motivation for IT team respondents is boosting employee productivity (40%). This is opposed to commonly cited rationales such as improving customer experience (29%) and migrating to the cloud (22%). However when looking at success measures, increasing business efficiency is in the bottom two chosen, which boosting employee productivity would typically be related to. This discrepancy seems to imply that while IT teams are looking to address challenges they face with maintaining legacy applications, possibly due to lack of documentation and/or lack of qualified personnel, they must also justify these projects in terms that are important to business leadership.

Reasons most often cited by the C-Suite for modernization are directly related to increasing revenue and profits, such as moving to the cloud to improve customer experience and reduce costs. The disconnect indicates that IT teams, who have their own modernization motivations, must find ways to align with the C-Suite who are defining tangible measures of success, prior to executing on these projects.

IT teams lack of awareness and access to modern tools

Most respondents don't believe they have access to the capabilities they want. For example, more than half would like to automate code transformation and business rules extraction (BRE) to a large degree, and 40% want to automate application documentation creation. Similarly, 64% believe freezing code during the modernization process will have significant business and financial consequences, and a full 59% say the ability to modernize without freezing code is on their technology wish list, making it the top most requested modernization capability. Yet while these, and other technologies on their wish lists, are available in the current modernization market, no more than 31% of IT leaders say they have access to them.

The ability to successfully modernize will be a key differentiator for businesses as they navigate the ever-evolving digital landscape. While the process can be complex and challenging, insights into potential blind spots and disconnects can help IT leaders develop more effective strategies and make the most of their available resources and technological advancements.

Alisha Marfatia is a Product Strategist at EvolveWare

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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 ...

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 ...