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BMC TrueSight Capacity Optimization Certified for Hadoop Big Data Environments

BMC TrueSight Capacity Optimization is certified for integration on both Cloudera Enterprise and Hortonworks Hadoop environments.

The integration enables digital enterprises to accurately plan for and maximize their investment in the Hadoop IT infrastructure resources they need to quickly deploy Big Data applications and ensure ongoing service delivery.

Digital enterprises are increasingly using Big Data to secure business insights that deliver a competitive advantage. According to a recent IDC forecast, the Big Data technology and services market will grow at a 26.4 percent compound annual growth rate to $41.5 billion through 2018, or about six times the growth rate of the overall information technology market.

BMC's TrueSight Capacity Optimization solution is available for Hadoop capacity management, enabling enterprises to automate the planning and management of the growth and use of their Hadoop compute, storage and network resources. With this knowledge, organizations can accurately plan capital expenditures and optimize their infrastructure investment for their Hadoop projects, as well as ensure that Hadoop clusters have the resources needed to support current and future application workloads and reduce the risk of application failure due to capacity shortfalls.

"Success in the digital economy demands that enterprises quickly and intelligently respond to customer, market and other business developments. To enable this agility and insight, many companies turn to Hadoop and Big Data applications," said Bill Berutti, President of the Cloud, Data Center and Performance Businesses at BMC. "BMC's TrueSight Capacity Optimization gives organizations the ability to plan, control and optimize their ongoing IT investment in their Hadoop environments. Ultimately, the TrueSight Capacity Optimization solution enables them to accelerate their transformation into digital enterprises that move at the speed of business."

"BMC's TrueSight Capacity Optimization integration with Cloudera Manager provides organizations with added visibility and analysis of their Cloudera cluster resources. This added insight allows organizations to better understand existing big data environments and plan for future business workloads," said Tim Stevens, VP of Business and Corporate Development at Cloudera.

"Hortonworks is dedicated to expanding and empowering the Apache Hadoop ecosystem, accelerating innovation and adoption of Open Enterprise Hadoop," said Matt Morgan, VP of Product and Alliance Marketing at Hortonworks. "We are pleased to welcome BMC's TrueSight Capacity Optimization solution to the Apache Hadoop community and look forward to working with them to help strengthen Hadoop's role as the foundation of the next-generation data architecture. The relationship will help accelerate successful implementations of TrueSight Capacity Optimization and the Hortonworks Data Platform to deliver data driven business transformations."

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.

BMC TrueSight Capacity Optimization Certified for Hadoop Big Data Environments

BMC TrueSight Capacity Optimization is certified for integration on both Cloudera Enterprise and Hortonworks Hadoop environments.

The integration enables digital enterprises to accurately plan for and maximize their investment in the Hadoop IT infrastructure resources they need to quickly deploy Big Data applications and ensure ongoing service delivery.

Digital enterprises are increasingly using Big Data to secure business insights that deliver a competitive advantage. According to a recent IDC forecast, the Big Data technology and services market will grow at a 26.4 percent compound annual growth rate to $41.5 billion through 2018, or about six times the growth rate of the overall information technology market.

BMC's TrueSight Capacity Optimization solution is available for Hadoop capacity management, enabling enterprises to automate the planning and management of the growth and use of their Hadoop compute, storage and network resources. With this knowledge, organizations can accurately plan capital expenditures and optimize their infrastructure investment for their Hadoop projects, as well as ensure that Hadoop clusters have the resources needed to support current and future application workloads and reduce the risk of application failure due to capacity shortfalls.

"Success in the digital economy demands that enterprises quickly and intelligently respond to customer, market and other business developments. To enable this agility and insight, many companies turn to Hadoop and Big Data applications," said Bill Berutti, President of the Cloud, Data Center and Performance Businesses at BMC. "BMC's TrueSight Capacity Optimization gives organizations the ability to plan, control and optimize their ongoing IT investment in their Hadoop environments. Ultimately, the TrueSight Capacity Optimization solution enables them to accelerate their transformation into digital enterprises that move at the speed of business."

"BMC's TrueSight Capacity Optimization integration with Cloudera Manager provides organizations with added visibility and analysis of their Cloudera cluster resources. This added insight allows organizations to better understand existing big data environments and plan for future business workloads," said Tim Stevens, VP of Business and Corporate Development at Cloudera.

"Hortonworks is dedicated to expanding and empowering the Apache Hadoop ecosystem, accelerating innovation and adoption of Open Enterprise Hadoop," said Matt Morgan, VP of Product and Alliance Marketing at Hortonworks. "We are pleased to welcome BMC's TrueSight Capacity Optimization solution to the Apache Hadoop community and look forward to working with them to help strengthen Hadoop's role as the foundation of the next-generation data architecture. The relationship will help accelerate successful implementations of TrueSight Capacity Optimization and the Hortonworks Data Platform to deliver data driven business transformations."

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.