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Netuitive Studio Fueling Field Integrations of Business and IT Data

Netuitive announced details about new technology integrations resulting from the release of Netuitive 6.0, including Integration Studio, the industry’s first “open” API to a predictive analytics platform for IT allowing organizations to easily create custom integrations that apply Netuitive’s IT analytics to virtually any data source (announced April 30).

Since its release, Netuitive reports that it is developing 10 new custom integrations to industry-leading APM platforms such as Splunk, EMC Celera, Blue Stripe, Nastel, and others. This is in addition to Netuitive’s 30+ existing integrations with leading monitoring tools from leaders such as CA, BMC, HP, IBM, VMware, Microsoft, Compuware, EMC, NetApp, Oracle, and others.

The combination of these integrations allows large enterprises to apply Netuitive’s advanced IT analytics to achieve comprehensive visibility across those data sources.

This open approach to leveraging IT analytics across an entire organization is enabling them to go beyond monitoring silos to understand how IT performance is impacting the business in real-time.

Netuitive 6.0 enables large organizations to monitor and quickly correlate the vast and unmanageable amounts of APM-generated Big Data (e.g., business activity, customer experience, applications, and infrastructure) collected from a growing number of specialized monitoring tools. Leveraging advanced Behavior Learning technology applied to the data collected, it provides meaningful visibility into the health of applications, automatically isolates problems across silos and domains, and delivers proactive notifications of impending performance issues.

“Ultimately, data is the key to success of IT analytics solutions focused on improving visibility into performance of critical applications,” said Will Cappelli, senior analyst, Gartner. “The advent of open IT analytics platforms is well suited for large IT organizations that may be lagging on the IT maturity level but have revenue impacting critical applications demanding proactive management. Open IT analytics is the only way to get the data required to achieve true end-to-end visibility.”

“We are starting to see the power of an open IT analytics architecture applied to proactively managing the performance of critical business applications,” said Nicola Sanna, CEO of Netuitive. “The new, open nature of Netuitive capitalizes on years of experience and more than 30 standard integrations allowing customers to start creating new and customized IT analytics solutions tailored to their APM tools and solution needs.”

In addition to Integration Studio, Netuitive 6.0 features new models for complex, distributed Java applications providing much greater visibility into Java applications, and an improved user interface and new algorithms optimized for APM diagnostics.

www.netuitive.com

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 ...

Netuitive Studio Fueling Field Integrations of Business and IT Data

Netuitive announced details about new technology integrations resulting from the release of Netuitive 6.0, including Integration Studio, the industry’s first “open” API to a predictive analytics platform for IT allowing organizations to easily create custom integrations that apply Netuitive’s IT analytics to virtually any data source (announced April 30).

Since its release, Netuitive reports that it is developing 10 new custom integrations to industry-leading APM platforms such as Splunk, EMC Celera, Blue Stripe, Nastel, and others. This is in addition to Netuitive’s 30+ existing integrations with leading monitoring tools from leaders such as CA, BMC, HP, IBM, VMware, Microsoft, Compuware, EMC, NetApp, Oracle, and others.

The combination of these integrations allows large enterprises to apply Netuitive’s advanced IT analytics to achieve comprehensive visibility across those data sources.

This open approach to leveraging IT analytics across an entire organization is enabling them to go beyond monitoring silos to understand how IT performance is impacting the business in real-time.

Netuitive 6.0 enables large organizations to monitor and quickly correlate the vast and unmanageable amounts of APM-generated Big Data (e.g., business activity, customer experience, applications, and infrastructure) collected from a growing number of specialized monitoring tools. Leveraging advanced Behavior Learning technology applied to the data collected, it provides meaningful visibility into the health of applications, automatically isolates problems across silos and domains, and delivers proactive notifications of impending performance issues.

“Ultimately, data is the key to success of IT analytics solutions focused on improving visibility into performance of critical applications,” said Will Cappelli, senior analyst, Gartner. “The advent of open IT analytics platforms is well suited for large IT organizations that may be lagging on the IT maturity level but have revenue impacting critical applications demanding proactive management. Open IT analytics is the only way to get the data required to achieve true end-to-end visibility.”

“We are starting to see the power of an open IT analytics architecture applied to proactively managing the performance of critical business applications,” said Nicola Sanna, CEO of Netuitive. “The new, open nature of Netuitive capitalizes on years of experience and more than 30 standard integrations allowing customers to start creating new and customized IT analytics solutions tailored to their APM tools and solution needs.”

In addition to Integration Studio, Netuitive 6.0 features new models for complex, distributed Java applications providing much greater visibility into Java applications, and an improved user interface and new algorithms optimized for APM diagnostics.

www.netuitive.com

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 ...