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Compuware APM Introduces Smart Network Packet Capture and Analysis With Enhanced Availability Analytics

New Version Simplifies Fault Domain Isolation Enabling Rapid Collaboration Between Network and Application Teams

Compuware Corporation announced a major new release of its Data Center Real User Monitoring solution (DC RUM).

Enhanced analytics and new network packet capture and analysis capabilities simplify identification and triage of performance issues across applications, infrastructure and network. Now application operators can monitor and understand the network impact on application performance down to the transaction and user level at packet-level depth.

The new availability analytics span all layers of a business transaction, from the network TCP session all the way up to the application logic.

"This new version of DC RUM will change the way we triage performance issues across the network and application layers. Instead of manually correlating across different network and application tools, Compuware APM provides a single solution and workflow," said Doug Botimer, Technology Solutions Manager, at Marketing Associates. "Not only does Compuware DC RUM automatically identify the bottleneck, it provides the user and transaction context required to solve the problem with packet-level visibility."

DC RUM's end-to-end view encompasses detailed network, client and server fault-domain analysis, and streamlines the identification and isolation of a problem's root cause. This unique fault-domain isolation value is now supplemented by the ability to initiate, collect and analyze packet-level data in the context of DC RUM reports. This allows operations and performance teams to ascertain root causes of network issues by viewing the packet-level data collected in the context of the application, transaction and user analysis.

Additionally, by leveraging domain experience built from thousands of customers and hundreds of man-years invested in performance analytics, Compuware APM customers now benefit from enhanced analytics that embed these best practices into the product itself.

Enhancements to Compuware APM's DC RUM solution include:

- Smarter triage and delivery of actionable root-cause information to network performance teams including packet-level visibility. When performance problems are triaged to the network, Compuware APM provides analysis of transactions at packet-level depth. Unlike competitor offerings that simply capture raw network data, DC RUM provides application, transaction and user context for enhanced analysis.

- Quantifies the business impact of availability issues with smart availability analytics. Operations and performance teams can now automatically understand when application and network faults impact user experiences. Instead of pouring over potentially innocuous issues or missing errors that affect users, immediate notification of user-impacting problems is provided. DC RUM measures and automatically baselines all layers supporting a business transaction - from network TCP sessions to application logic - and shows at a glance the source of the problem with a single application health index.

- The ability to initiate packet captures, using the context of transactions, applications, users and other criteriato set the boundaries for packet-level collection and analysis. DC RUM combined with transaction trace analysis, Compuware APM's protocol analyzer with expert application insight, delivers the facts through the industry's broadest set of application decodes.

"As modern network and application architectures continue to increase in complexity, so do challenges around performance visibility and control," said Steve Tack, Vice President of Product Management for Compuware's APM business unit. "With this new release of our DC RUM solution, we deliver powerful new performance analytics that solve these challenges and support a smarter triage process to rapidly resolve issues. Customers can improve user experience through network packet-level capture and analysis with business context, and enhanced availability analytics."

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Compuware APM Introduces Smart Network Packet Capture and Analysis With Enhanced Availability Analytics

New Version Simplifies Fault Domain Isolation Enabling Rapid Collaboration Between Network and Application Teams

Compuware Corporation announced a major new release of its Data Center Real User Monitoring solution (DC RUM).

Enhanced analytics and new network packet capture and analysis capabilities simplify identification and triage of performance issues across applications, infrastructure and network. Now application operators can monitor and understand the network impact on application performance down to the transaction and user level at packet-level depth.

The new availability analytics span all layers of a business transaction, from the network TCP session all the way up to the application logic.

"This new version of DC RUM will change the way we triage performance issues across the network and application layers. Instead of manually correlating across different network and application tools, Compuware APM provides a single solution and workflow," said Doug Botimer, Technology Solutions Manager, at Marketing Associates. "Not only does Compuware DC RUM automatically identify the bottleneck, it provides the user and transaction context required to solve the problem with packet-level visibility."

DC RUM's end-to-end view encompasses detailed network, client and server fault-domain analysis, and streamlines the identification and isolation of a problem's root cause. This unique fault-domain isolation value is now supplemented by the ability to initiate, collect and analyze packet-level data in the context of DC RUM reports. This allows operations and performance teams to ascertain root causes of network issues by viewing the packet-level data collected in the context of the application, transaction and user analysis.

Additionally, by leveraging domain experience built from thousands of customers and hundreds of man-years invested in performance analytics, Compuware APM customers now benefit from enhanced analytics that embed these best practices into the product itself.

Enhancements to Compuware APM's DC RUM solution include:

- Smarter triage and delivery of actionable root-cause information to network performance teams including packet-level visibility. When performance problems are triaged to the network, Compuware APM provides analysis of transactions at packet-level depth. Unlike competitor offerings that simply capture raw network data, DC RUM provides application, transaction and user context for enhanced analysis.

- Quantifies the business impact of availability issues with smart availability analytics. Operations and performance teams can now automatically understand when application and network faults impact user experiences. Instead of pouring over potentially innocuous issues or missing errors that affect users, immediate notification of user-impacting problems is provided. DC RUM measures and automatically baselines all layers supporting a business transaction - from network TCP sessions to application logic - and shows at a glance the source of the problem with a single application health index.

- The ability to initiate packet captures, using the context of transactions, applications, users and other criteriato set the boundaries for packet-level collection and analysis. DC RUM combined with transaction trace analysis, Compuware APM's protocol analyzer with expert application insight, delivers the facts through the industry's broadest set of application decodes.

"As modern network and application architectures continue to increase in complexity, so do challenges around performance visibility and control," said Steve Tack, Vice President of Product Management for Compuware's APM business unit. "With this new release of our DC RUM solution, we deliver powerful new performance analytics that solve these challenges and support a smarter triage process to rapidly resolve issues. Customers can improve user experience through network packet-level capture and analysis with business context, and enhanced availability analytics."

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 ...