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Investing, Innovating, and Integrating the Mainframe: A Strategy for Success

April Hickel
BMC

Consumers are using more digital products every day, and in doing so, they have come to expect easy-to-use, always-available, bug-free digital experiences. As such, development teams are under pressure more than ever before to innovate at a rapid pace and produce high-quality services and applications. In our current environment, the mainframe cannot be a department of "no," or a department of "slow." Instead, organizations must evolve their processes, tools, and culture to respond quickly to market demands and new business needs if they are to be successful.

Key to this move toward faster, more responsive, and higher-quality development is the adoption of a "shift-left" attitude towards testing. Organizations can't afford to develop software, pass it along to operations for testing, and wait for bug reports to be able to resolve issues. By shifting testing closer to development and making it part of their automated continuous integration/continuous delivery (CI/CD) pipeline, they can rapidly test new code, and ultimately drive more agile release cycles with better overall quality.

The results of the 2021 BMC Mainframe Survey highlight the consistent positive growth outlook as seen in recent years, with 92 percent of respondents viewing the mainframe as a platform for long-term growth and new workloads, and 86 percent of extra-large shops expecting MIPS (millions of instructions per second) to grow in the coming year. This is not surprising, considering the disruptive nature of the modern digital economy.

Furthermore, the results of the survey show mainframe Champions — organizations that are increasing their mainframe investment or expect MIPS to grow — have incorporated the mainframe into their enterprise agile development and DevOps initiatives. In doing so, they have improved the stability of their IT infrastructure, the quality of their applications, and the efficiency of their development processes.

Mainframe Security Remains Critical for Enterprises

As organizations look to develop new services and open the mainframe to more, the security of the platform is of utmost concern. For the second consecutive year, according to our survey, security was cited as the top priority for respondents at 61%, with mainframe Champions focusing on proactive security, real-time visibility, and integration of the mainframe with enterprise security information event management (SIEM).

While the mainframe is inherently securable, last year's rapid shift to remote work only further proved that the traditional network perimeter is dead, and a proactive approach is essential to ensure mainframe protection. Based on our survey, 86% of respondents conducted an internal security audit in the last two years that revealed an unaddressed vulnerability. Furthermore, the most common vulnerability findings were related to the operating system (41%) and configuration (40%).

Champions are recognizing that with the breakdown of the enterprise perimeter, audits are no longer enough to guarantee protection from threats. The mainframe must also be proactively secured, with real-time visibility and SIEM integration to enable fast detection and response by security operations center (SOC) teams. This is also critical for the evolution to an autonomous digital enterprise (ADE). To continuously protect against vulnerabilities, malicious actions, and data theft businesses should consider:

■ Having the ability to halt suspicious and known malicious actions before systems are compromised. This can be accomplished through automated protection, detection, and response.

■ Ensuring real-time visibility for security responders and operations teams so that they can rapidly close the window of opportunity for attackers. This could be the difference between a secure platform and harmful attack.

■ Collecting actionable intelligence for incident response. To do this, it is important for data to be correlated across multiple systems and translated into common security terms for clarity and context.

Innovating to Meet Rising Digital Demands

Enterprises are moving quickly to keep pace with the rising demand for new applications and services and deliver a transcendent customer experience, which is a key tenet of the ADE, to both their employees and customers. According to our survey, champions update their mainframe applications more frequently — and want to further accelerate delivery. They've made Agile/DevOps a staple of development across the enterprise, including in mainframe-only environments, and it's paying off with rapid return on investment (ROI).

Champions are realizing the broad benefits that come from DevOps, which include:

■ Improving IT infrastructure stability and the quality of deployed applications.

■ Automating manual tasks to reduce errors and free development staff to work on high-value initiatives.

■ Leveraging modern development tools to attract new talent to create new innovations on the platform.

Overall, the results of the survey show that the platform will be an integral part of organizations' workload infrastructure for decades to come. In a year defined by sharp increases in digital activities from remote working to online banking, commerce, and entertainment, businesses counted on their mainframe to handle new levels of unpredictability. As enterprise evolution continues, the mainframe will help organizations evolve to ADEs, where competitive differentiation is enabled by agility, customer centricity, and actionable insights.

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

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In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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 ...

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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.

Investing, Innovating, and Integrating the Mainframe: A Strategy for Success

April Hickel
BMC

Consumers are using more digital products every day, and in doing so, they have come to expect easy-to-use, always-available, bug-free digital experiences. As such, development teams are under pressure more than ever before to innovate at a rapid pace and produce high-quality services and applications. In our current environment, the mainframe cannot be a department of "no," or a department of "slow." Instead, organizations must evolve their processes, tools, and culture to respond quickly to market demands and new business needs if they are to be successful.

Key to this move toward faster, more responsive, and higher-quality development is the adoption of a "shift-left" attitude towards testing. Organizations can't afford to develop software, pass it along to operations for testing, and wait for bug reports to be able to resolve issues. By shifting testing closer to development and making it part of their automated continuous integration/continuous delivery (CI/CD) pipeline, they can rapidly test new code, and ultimately drive more agile release cycles with better overall quality.

The results of the 2021 BMC Mainframe Survey highlight the consistent positive growth outlook as seen in recent years, with 92 percent of respondents viewing the mainframe as a platform for long-term growth and new workloads, and 86 percent of extra-large shops expecting MIPS (millions of instructions per second) to grow in the coming year. This is not surprising, considering the disruptive nature of the modern digital economy.

Furthermore, the results of the survey show mainframe Champions — organizations that are increasing their mainframe investment or expect MIPS to grow — have incorporated the mainframe into their enterprise agile development and DevOps initiatives. In doing so, they have improved the stability of their IT infrastructure, the quality of their applications, and the efficiency of their development processes.

Mainframe Security Remains Critical for Enterprises

As organizations look to develop new services and open the mainframe to more, the security of the platform is of utmost concern. For the second consecutive year, according to our survey, security was cited as the top priority for respondents at 61%, with mainframe Champions focusing on proactive security, real-time visibility, and integration of the mainframe with enterprise security information event management (SIEM).

While the mainframe is inherently securable, last year's rapid shift to remote work only further proved that the traditional network perimeter is dead, and a proactive approach is essential to ensure mainframe protection. Based on our survey, 86% of respondents conducted an internal security audit in the last two years that revealed an unaddressed vulnerability. Furthermore, the most common vulnerability findings were related to the operating system (41%) and configuration (40%).

Champions are recognizing that with the breakdown of the enterprise perimeter, audits are no longer enough to guarantee protection from threats. The mainframe must also be proactively secured, with real-time visibility and SIEM integration to enable fast detection and response by security operations center (SOC) teams. This is also critical for the evolution to an autonomous digital enterprise (ADE). To continuously protect against vulnerabilities, malicious actions, and data theft businesses should consider:

■ Having the ability to halt suspicious and known malicious actions before systems are compromised. This can be accomplished through automated protection, detection, and response.

■ Ensuring real-time visibility for security responders and operations teams so that they can rapidly close the window of opportunity for attackers. This could be the difference between a secure platform and harmful attack.

■ Collecting actionable intelligence for incident response. To do this, it is important for data to be correlated across multiple systems and translated into common security terms for clarity and context.

Innovating to Meet Rising Digital Demands

Enterprises are moving quickly to keep pace with the rising demand for new applications and services and deliver a transcendent customer experience, which is a key tenet of the ADE, to both their employees and customers. According to our survey, champions update their mainframe applications more frequently — and want to further accelerate delivery. They've made Agile/DevOps a staple of development across the enterprise, including in mainframe-only environments, and it's paying off with rapid return on investment (ROI).

Champions are realizing the broad benefits that come from DevOps, which include:

■ Improving IT infrastructure stability and the quality of deployed applications.

■ Automating manual tasks to reduce errors and free development staff to work on high-value initiatives.

■ Leveraging modern development tools to attract new talent to create new innovations on the platform.

Overall, the results of the survey show that the platform will be an integral part of organizations' workload infrastructure for decades to come. In a year defined by sharp increases in digital activities from remote working to online banking, commerce, and entertainment, businesses counted on their mainframe to handle new levels of unpredictability. As enterprise evolution continues, the mainframe will help organizations evolve to ADEs, where competitive differentiation is enabled by agility, customer centricity, and actionable insights.

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

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.