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BMC Delivers Next Wave of New Digital Enterprise Management Solutions

BMC kicked off its second annual user conference by announcing the next wave of new and enhanced Digital Enterprise Management IT solutions, including offerings to discover valuable insights into digital service performance, improve employee productivity, reduce security vulnerabilities and decrease the costs associated with maintaining mainframe infrastructure.

“With Digital Enterprise Management, BMC is providing a clear path to successfully manage this digital transformation. Our six new innovative solutions enable companies to delight customers and empower employees with digital services that do not compromise data security or bust the IT budget,” said BMC CEO Bob Beauchamp. “From the mainframe to mobile to the cloud, our solutions allow companies to improve the speed and lower the cost of digital service development, deployment, operation and maintenance.”

The new and enhanced solutions include:

- TrueSight Intelligence: Improves business decision-making and innovation with high-volume IT operation, technical and business data analysis tools that deliver actionable real-time insights into digital service performance.

- MyIT Service Broker: Boosts employee productivity and reduces unauthorized IT activity with a digital service app store that aggregates, manages, delivers and analyzes hardware, software and services in a unified catalog.

- HR Case Management: Streamlines HR processes and improves employee satisfaction with a digital service that includes 350 prebuilt HR process templates, embedded HR best practices and intuitive HR self-service apps.

- BladeLogic 8.7 Intelligent Compliance: Strengthens digital service security with new features that decrease vulnerability response times, improve regulatory compliance and reduce security audit times.

- Mainframe MLC Cost Management: Reduces costs associated with maintaining mainframe infrastructure by lowering mainframe monthly licensing charge (MLC) software charges.

- Control M9: Lowers IT administration time, reduces the risk of business interruption and speeds digital service deployment with new application workflow automation features, including automated agent and client deployment for faster upgrades and maintenance, a global calendar and a 24/7 high availability fail over capability for better application reliability.

“Companies today realize they must adopt a digital-first business strategy, as they look to grow their business, seek new revenue streams and expand into new markets,” said BMC EVP Paul Appleby. “BMC’s solutions provide companies with the tools they need to execute their strategies, use the Internet of Things, big data and other technologies to digitally transform almost every aspect of their internal operations and strengthen their customer relationships.”

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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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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.

BMC Delivers Next Wave of New Digital Enterprise Management Solutions

BMC kicked off its second annual user conference by announcing the next wave of new and enhanced Digital Enterprise Management IT solutions, including offerings to discover valuable insights into digital service performance, improve employee productivity, reduce security vulnerabilities and decrease the costs associated with maintaining mainframe infrastructure.

“With Digital Enterprise Management, BMC is providing a clear path to successfully manage this digital transformation. Our six new innovative solutions enable companies to delight customers and empower employees with digital services that do not compromise data security or bust the IT budget,” said BMC CEO Bob Beauchamp. “From the mainframe to mobile to the cloud, our solutions allow companies to improve the speed and lower the cost of digital service development, deployment, operation and maintenance.”

The new and enhanced solutions include:

- TrueSight Intelligence: Improves business decision-making and innovation with high-volume IT operation, technical and business data analysis tools that deliver actionable real-time insights into digital service performance.

- MyIT Service Broker: Boosts employee productivity and reduces unauthorized IT activity with a digital service app store that aggregates, manages, delivers and analyzes hardware, software and services in a unified catalog.

- HR Case Management: Streamlines HR processes and improves employee satisfaction with a digital service that includes 350 prebuilt HR process templates, embedded HR best practices and intuitive HR self-service apps.

- BladeLogic 8.7 Intelligent Compliance: Strengthens digital service security with new features that decrease vulnerability response times, improve regulatory compliance and reduce security audit times.

- Mainframe MLC Cost Management: Reduces costs associated with maintaining mainframe infrastructure by lowering mainframe monthly licensing charge (MLC) software charges.

- Control M9: Lowers IT administration time, reduces the risk of business interruption and speeds digital service deployment with new application workflow automation features, including automated agent and client deployment for faster upgrades and maintenance, a global calendar and a 24/7 high availability fail over capability for better application reliability.

“Companies today realize they must adopt a digital-first business strategy, as they look to grow their business, seek new revenue streams and expand into new markets,” said BMC EVP Paul Appleby. “BMC’s solutions provide companies with the tools they need to execute their strategies, use the Internet of Things, big data and other technologies to digitally transform almost every aspect of their internal operations and strengthen their customer relationships.”

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.