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Network Instruments Unveils Observer 15

Network Instruments, a provider of network and application performance monitoring, introduced the latest version of its Observer performance management platform, which significantly expands support for complex communications and multi-tiered application environments.

Developed in response to customer demand, Observer 15 focuses on critical application challenges IT teams face in validating video conferencing performance, gaining insight into the middleware layer of multi-tiered applications, and proactively tracking end-user experience without the burden of agents.

The redesigned platform also addresses the primary challenges IT managers face in deploying performance management systems in the data center: network overhead and scalability limitations.

Observer version 15 includes:

Video-Conference Monitoring: The Observer platform now provides comprehensive codec support and metrics to ensure video and audio quality are fully optimized. Version 15 allows engineers to view video performance alongside other applications that could adversely impact call quality.

Microsoft UC: Network Instruments has strengthened its unified communications analysis by adding in-depth support for the Microsoft UC platform. In addition to viewing UC/VoIP metrics on a summary or per-call basis, teams can utilize Observer Infrastructure to monitor the health of Microsoft Lync servers and related UC components.

IBM WebSphere MQ: Enterprise network teams can now use Observer to improve overall service health by understanding how WebSphere MQ runs within the application hierarchy. By analyzing MQ response times and payload, it’s possible to determine whether performance between tiers is degrading.

End-User Experience: As user expectations and dependence on the network increase, the Observer platform ensures IT stays a step ahead by providing new metrics and intelligence for measuring end-user experience. Relying upon probes and polling technologies accessing native agents, Observer delivers in-depth end-user experience metrics without burdensome proprietary agents or manipulating packets. To streamline the process of managing user experience, teams can drill from dashboard views using new out-of-the-box reports to specific conversations and event details for resolution.

Capture and Analysis Innovations: With Observer 15, Network Instruments introduces several significant hardware and software innovations and enhancements that mark architectural leaps forward in high-speed packet capture and analysis.

Financial Trading Analysis: Observer now includes robust multicast analysis and automated microburst detection to ensure IT teams know what is happening down to sub-second levels. Teams can verify multicast streams are properly sent and received, and analyze and summarize stream performance. Observer also allows teams to define microburst parameters and will automatically identify occurrences.

Integrated Third-Party Analysis: Observer 15 offers integrated support for third-party analysis capabilities by exporting captures from Observer and GigaStor to external analysis and security solutions. Users can utilize the integrated analysis feature to mine data and automatically launch analysis within third-party tools, including security, compliance, and forensic tools, alongside Observer 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 ...

Network Instruments Unveils Observer 15

Network Instruments, a provider of network and application performance monitoring, introduced the latest version of its Observer performance management platform, which significantly expands support for complex communications and multi-tiered application environments.

Developed in response to customer demand, Observer 15 focuses on critical application challenges IT teams face in validating video conferencing performance, gaining insight into the middleware layer of multi-tiered applications, and proactively tracking end-user experience without the burden of agents.

The redesigned platform also addresses the primary challenges IT managers face in deploying performance management systems in the data center: network overhead and scalability limitations.

Observer version 15 includes:

Video-Conference Monitoring: The Observer platform now provides comprehensive codec support and metrics to ensure video and audio quality are fully optimized. Version 15 allows engineers to view video performance alongside other applications that could adversely impact call quality.

Microsoft UC: Network Instruments has strengthened its unified communications analysis by adding in-depth support for the Microsoft UC platform. In addition to viewing UC/VoIP metrics on a summary or per-call basis, teams can utilize Observer Infrastructure to monitor the health of Microsoft Lync servers and related UC components.

IBM WebSphere MQ: Enterprise network teams can now use Observer to improve overall service health by understanding how WebSphere MQ runs within the application hierarchy. By analyzing MQ response times and payload, it’s possible to determine whether performance between tiers is degrading.

End-User Experience: As user expectations and dependence on the network increase, the Observer platform ensures IT stays a step ahead by providing new metrics and intelligence for measuring end-user experience. Relying upon probes and polling technologies accessing native agents, Observer delivers in-depth end-user experience metrics without burdensome proprietary agents or manipulating packets. To streamline the process of managing user experience, teams can drill from dashboard views using new out-of-the-box reports to specific conversations and event details for resolution.

Capture and Analysis Innovations: With Observer 15, Network Instruments introduces several significant hardware and software innovations and enhancements that mark architectural leaps forward in high-speed packet capture and analysis.

Financial Trading Analysis: Observer now includes robust multicast analysis and automated microburst detection to ensure IT teams know what is happening down to sub-second levels. Teams can verify multicast streams are properly sent and received, and analyze and summarize stream performance. Observer also allows teams to define microburst parameters and will automatically identify occurrences.

Integrated Third-Party Analysis: Observer 15 offers integrated support for third-party analysis capabilities by exporting captures from Observer and GigaStor to external analysis and security solutions. Users can utilize the integrated analysis feature to mine data and automatically launch analysis within third-party tools, including security, compliance, and forensic tools, alongside Observer 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 ...