Skip to main content

Renewing the Mainframe

April Hickel
BMC

Many have assumed that the mainframe is a dying entity, but instead, a mainframe renaissance is underway. Despite this notion, we are ushering in a future of more strategic investments, increased capacity, and leading innovations. Fast-growing organizations are meeting this progression with new approaches to improve their agility and speed while entirely integrating the mainframe within their enterprise systems and mechanisms.

According to the 2022 BMC Mainframe Survey, a study conducted of more than 1,000 mainframe and IT professionals globally, over 60% of respondents reported that their investment in the platform is increasing. These increases tie directly to changing workloads on the platform as transaction and data volumes and the number of databases increase more rapidly — and unpredictably — than ever before. This only further illustrates that capacity is growing across all sizes of mainframe shops.

To set the pace, strong organizations have strategically integrated their mainframe with their enterprise processes. Enterprises are prioritizing their efforts on developing software more quickly and more often. They are also achieving higher quality releases with DevOps and AIOps to improve performance, availability, security, and compliance to effectively secure mainframe environments. Mainframes play a valuable role in enterprise innovation to deliver real-world results. The survey shows that adopters of AIOps and DevOps are seeing clear value from their investments, and the adoption of new tools and processes in key areas like DevOps, DevSecOps, and AIOps all increased from the previous year.

Additional survey findings include:

■ 65% of respondents report the combined use of AIOps in their mainframe and distributed environments. With the increase in AIOps adoption, more enterprises include mainframes in their enterprise wide AIOps initiatives, reinforcing the mainframe as a valuable platform for innovation.

■ 70% of large organizations reported DevOps use within their mainframe environment.

■ For the third year, security and compliance lead the list of priorities for mainframe organizations, with 67% of respondents citing both as top issues, a 6% increase over last year.

In AIOps, adoption is growing as implementation barriers decline. The mainframe is moving firmly into enterprise AIOps, as witnessed by the decreased use in non-mainframe environments and increased use in combined environments. The adoption of DevOps on the mainframe also continues to be a trend, as DevOps and collaboration deliver real-world results.

Finally, there is a growing awareness of the need to effectively secure mainframe environments, especially as the mainframe becomes a more integral part of enterprise security initiatives.

A Familiar Interface for Mainframe Development

Timely responses are a must when meeting the expectations of large companies. The survey shows that four out of five organizations look to update applications more often, with 14% updating their mainframe applications each day. However, attracting, onboarding, and retaining talent can be a challenge. Older mainframe code can be complicated and a majority of colleges and universities have abandoned the "green screen" teaching method in modern integrated development environments (IDEs) like Visual Studio Code (VS Code). As a matter of fact, the 2022 Stack Overflow Developer Survey found that almost 75% of respondents said they used VS Code in the past year and plan on continuing to work with it in the future.

In order to meet expectations for faster software delivery life cycles and beat staffing challenges, companies are integrating tools that get rid of obstructions that prevent a wider array of developers from accessing the mainframe. It holds true that developers should be able to leverage interfaces that are easy to comprehend and utilize while having the ability to troubleshoot code on even the most advanced systems.

An improved developer experience not only helps attract new talent to the mainframe; it also gives both new and seasoned developers a familiar environment to work in, decreasing onboarding time and enabling them to be more productive, faster.

The Renaissance Prevails

The mainframe platform is evolving at a rapid pace as more organizations apply an open-borders approach that utilizes mainframe, distributed, and cloud systems across applications. It is essential to fully integrate the mainframe with enterprise development and operations practices to ensure agility, resilience, and security while making work on the mainframe seamless.

April Hickel is VP, Intelligent Z Optimization and Transformation, at BMC

Hot Topics

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 ...

Renewing the Mainframe

April Hickel
BMC

Many have assumed that the mainframe is a dying entity, but instead, a mainframe renaissance is underway. Despite this notion, we are ushering in a future of more strategic investments, increased capacity, and leading innovations. Fast-growing organizations are meeting this progression with new approaches to improve their agility and speed while entirely integrating the mainframe within their enterprise systems and mechanisms.

According to the 2022 BMC Mainframe Survey, a study conducted of more than 1,000 mainframe and IT professionals globally, over 60% of respondents reported that their investment in the platform is increasing. These increases tie directly to changing workloads on the platform as transaction and data volumes and the number of databases increase more rapidly — and unpredictably — than ever before. This only further illustrates that capacity is growing across all sizes of mainframe shops.

To set the pace, strong organizations have strategically integrated their mainframe with their enterprise processes. Enterprises are prioritizing their efforts on developing software more quickly and more often. They are also achieving higher quality releases with DevOps and AIOps to improve performance, availability, security, and compliance to effectively secure mainframe environments. Mainframes play a valuable role in enterprise innovation to deliver real-world results. The survey shows that adopters of AIOps and DevOps are seeing clear value from their investments, and the adoption of new tools and processes in key areas like DevOps, DevSecOps, and AIOps all increased from the previous year.

Additional survey findings include:

■ 65% of respondents report the combined use of AIOps in their mainframe and distributed environments. With the increase in AIOps adoption, more enterprises include mainframes in their enterprise wide AIOps initiatives, reinforcing the mainframe as a valuable platform for innovation.

■ 70% of large organizations reported DevOps use within their mainframe environment.

■ For the third year, security and compliance lead the list of priorities for mainframe organizations, with 67% of respondents citing both as top issues, a 6% increase over last year.

In AIOps, adoption is growing as implementation barriers decline. The mainframe is moving firmly into enterprise AIOps, as witnessed by the decreased use in non-mainframe environments and increased use in combined environments. The adoption of DevOps on the mainframe also continues to be a trend, as DevOps and collaboration deliver real-world results.

Finally, there is a growing awareness of the need to effectively secure mainframe environments, especially as the mainframe becomes a more integral part of enterprise security initiatives.

A Familiar Interface for Mainframe Development

Timely responses are a must when meeting the expectations of large companies. The survey shows that four out of five organizations look to update applications more often, with 14% updating their mainframe applications each day. However, attracting, onboarding, and retaining talent can be a challenge. Older mainframe code can be complicated and a majority of colleges and universities have abandoned the "green screen" teaching method in modern integrated development environments (IDEs) like Visual Studio Code (VS Code). As a matter of fact, the 2022 Stack Overflow Developer Survey found that almost 75% of respondents said they used VS Code in the past year and plan on continuing to work with it in the future.

In order to meet expectations for faster software delivery life cycles and beat staffing challenges, companies are integrating tools that get rid of obstructions that prevent a wider array of developers from accessing the mainframe. It holds true that developers should be able to leverage interfaces that are easy to comprehend and utilize while having the ability to troubleshoot code on even the most advanced systems.

An improved developer experience not only helps attract new talent to the mainframe; it also gives both new and seasoned developers a familiar environment to work in, decreasing onboarding time and enabling them to be more productive, faster.

The Renaissance Prevails

The mainframe platform is evolving at a rapid pace as more organizations apply an open-borders approach that utilizes mainframe, distributed, and cloud systems across applications. It is essential to fully integrate the mainframe with enterprise development and operations practices to ensure agility, resilience, and security while making work on the mainframe seamless.

April Hickel is VP, Intelligent Z Optimization and Transformation, at BMC

Hot Topics

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 ...