Skip to main content

TeamQuest Integrates with BMC and Releases App for iOS Devices

TeamQuest is announcing two new features for their Vityl Adviser (Adviser ) platform. As well as a new app for all iOS devices, TeamQuest is announcing an integration with BMC’s TrueSight Capacity Optimization (BCO), meaning that customers can expect an even more streamlined health and risk platform.

The new integration will be between BCO and TeamQuest’s own Adviser, a platform that offers simplified infrastructure monitoring and capacity management by using advanced algorithms to translate data into health and risk scores. Adviser will now support BCO versions 10.5 and 10.3 in Linux and Windows environments, along with the BCO Oracle database server. With the latest Adviser release, the software will allow users to monitor and optimize their infrastructures faster and more efficiently.

“We understand that enterprises make large and significant investments in infrastructure monitoring,” says TeamQuest CEO Paul Hesser. “This is just the latest expansion of our efforts to ensure that all of our users’ existing data, regardless of platform or vendor, can be converted by TeamQuest’s advanced algorithm into simple health and risk scores.”

Complementing the new integration is the release of an iOS app. This new platform interfaces with Adviser to measure and report on the health and risk of deployed services and features intuitive controls that make it easy to cycle through different services. The app simplifies thousands of data points into a single indicator for each service, providing IT leaders with a comprehensive picture of their infrastructure’s risk and health when they’re ‘on-the-go’.

“Whether they are using an iPhone, iPad, or Apple Watch employees can now receive instant notifications when IT issues arise,” Hesser adds. “The app also provides insights as to how similar problems can be avoided later on. Even when they are away, employees will know exactly when things go wrong, so they don’t need to keep checking dashboards when they aren’t in the office.”

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.

TeamQuest Integrates with BMC and Releases App for iOS Devices

TeamQuest is announcing two new features for their Vityl Adviser (Adviser ) platform. As well as a new app for all iOS devices, TeamQuest is announcing an integration with BMC’s TrueSight Capacity Optimization (BCO), meaning that customers can expect an even more streamlined health and risk platform.

The new integration will be between BCO and TeamQuest’s own Adviser, a platform that offers simplified infrastructure monitoring and capacity management by using advanced algorithms to translate data into health and risk scores. Adviser will now support BCO versions 10.5 and 10.3 in Linux and Windows environments, along with the BCO Oracle database server. With the latest Adviser release, the software will allow users to monitor and optimize their infrastructures faster and more efficiently.

“We understand that enterprises make large and significant investments in infrastructure monitoring,” says TeamQuest CEO Paul Hesser. “This is just the latest expansion of our efforts to ensure that all of our users’ existing data, regardless of platform or vendor, can be converted by TeamQuest’s advanced algorithm into simple health and risk scores.”

Complementing the new integration is the release of an iOS app. This new platform interfaces with Adviser to measure and report on the health and risk of deployed services and features intuitive controls that make it easy to cycle through different services. The app simplifies thousands of data points into a single indicator for each service, providing IT leaders with a comprehensive picture of their infrastructure’s risk and health when they’re ‘on-the-go’.

“Whether they are using an iPhone, iPad, or Apple Watch employees can now receive instant notifications when IT issues arise,” Hesser adds. “The app also provides insights as to how similar problems can be avoided later on. Even when they are away, employees will know exactly when things go wrong, so they don’t need to keep checking dashboards when they aren’t in the office.”

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.