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Dynatrace Application Monitoring 6 and Dynatrace User Experience Management 6 Released

Dynatrace (formerly Compuware APM) announced the release of Dynatrace Application Monitoring 6 and Dynatrace User Experience Management 6.

As today's user interactions increasingly happen over mobile and digital channels, businesses need to understand their users' behavior and perception, in order to maximize usage, customer satisfaction and conversion. Gaining those insights demands more than the evolution of existing sample-based APM solutions, which were architected to capture data related to poorly performing transactions only. Understanding the experience and behavior of digital users, requires the capture and analysis of customer visits without gaps, regardless of device, location and time. Dynatrace 6 brings a new architecture that enables businesses to capture and analyze each user visit and actions, and understand how conversion, satisfaction, user behavior and performance correlate.

"Many APM solutions claiming to address user experience management today are in fact repurposed from traditional sampling-based techniques and focused on monitoring application health, not users' experience," said Steve Tack, VP of Product Management at Dynatrace. "This new architecture enables anyone to capture not just slow transaction data, but any data that pertains to customers' visits. This data provides tremendous insights into user behaviors across channels, and how conversion and user experience correlate."

This release also greatly simplifies the deployment, management and monitoring of APM through set-up wizards, auto-instrumentation of Apple iOS and Swift-based apps, and simple business transaction definition.

Dynatrace 6 capabilities include:

- New architecture for gap-free data capture, reducing agent communication by 90% increasing interactive analysis by 10x, and providing high availability support with automatic failover of agents and collectors.

- New Agent set-up wizards, enabling installation of an agent in minutes.

- New Business Transaction Configurator to create web-based business transactions in seconds.

- New Auto-Instrumentation for iOS: you can go from an iOS app to an instrumented iOS app in less than 15 minutes -capturing user actions, network requests, crashes- without changing a line of code.

- Support for Swift and Apple new programming language.

- Out-of-the-box detection of swipes, taps, clicks, and remote calls for AngularJS, MooTools, and Prototype.

- New Dynatrace Agent for NGINX.

- First transactional APM solution for IBM IMS.

- In-Flight: a new, real-time user visibility dashboard for peak events.

- Thread Analysis for .NET, business dashboards and PHP & web server Improvements.

- New and improved agents for TIBCO ActiveMatrix, TIBCO EMS, Java 8, iOS 8, NGINX, HBase, Cassandra, MongoDB and iPlanet.

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 ...

Dynatrace Application Monitoring 6 and Dynatrace User Experience Management 6 Released

Dynatrace (formerly Compuware APM) announced the release of Dynatrace Application Monitoring 6 and Dynatrace User Experience Management 6.

As today's user interactions increasingly happen over mobile and digital channels, businesses need to understand their users' behavior and perception, in order to maximize usage, customer satisfaction and conversion. Gaining those insights demands more than the evolution of existing sample-based APM solutions, which were architected to capture data related to poorly performing transactions only. Understanding the experience and behavior of digital users, requires the capture and analysis of customer visits without gaps, regardless of device, location and time. Dynatrace 6 brings a new architecture that enables businesses to capture and analyze each user visit and actions, and understand how conversion, satisfaction, user behavior and performance correlate.

"Many APM solutions claiming to address user experience management today are in fact repurposed from traditional sampling-based techniques and focused on monitoring application health, not users' experience," said Steve Tack, VP of Product Management at Dynatrace. "This new architecture enables anyone to capture not just slow transaction data, but any data that pertains to customers' visits. This data provides tremendous insights into user behaviors across channels, and how conversion and user experience correlate."

This release also greatly simplifies the deployment, management and monitoring of APM through set-up wizards, auto-instrumentation of Apple iOS and Swift-based apps, and simple business transaction definition.

Dynatrace 6 capabilities include:

- New architecture for gap-free data capture, reducing agent communication by 90% increasing interactive analysis by 10x, and providing high availability support with automatic failover of agents and collectors.

- New Agent set-up wizards, enabling installation of an agent in minutes.

- New Business Transaction Configurator to create web-based business transactions in seconds.

- New Auto-Instrumentation for iOS: you can go from an iOS app to an instrumented iOS app in less than 15 minutes -capturing user actions, network requests, crashes- without changing a line of code.

- Support for Swift and Apple new programming language.

- Out-of-the-box detection of swipes, taps, clicks, and remote calls for AngularJS, MooTools, and Prototype.

- New Dynatrace Agent for NGINX.

- First transactional APM solution for IBM IMS.

- In-Flight: a new, real-time user visibility dashboard for peak events.

- Thread Analysis for .NET, business dashboards and PHP & web server Improvements.

- New and improved agents for TIBCO ActiveMatrix, TIBCO EMS, Java 8, iOS 8, NGINX, HBase, Cassandra, MongoDB and iPlanet.

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 ...