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WildPackets Announces WatchPoint 3.0

WildPackets announced WatchPoint 3.0, a distributed network monitoring solution that uses big data technology to capture all network flow and packet analysis data with one-minute granularity for up to one year.

This provides the most comprehensive details and reports for service-level agreement analysis and reporting.

WatchPoint 3.0 provides up to one year of network analysis data, without sampling or averaging data, giving IT administrators, IT managers, and line-of-business managers the most comprehensive and detailed view of network performance available. Instead of cobbling together multiple short-term reports to understand long-term network performance, stakeholders can view reports that accurately represent long-term trends and baselines.

To support this detailed, scalable repository of network data, WatchPoint 3.0 uses a new big data architecture with a vast, flexible, and highly responsive data store that supports rich analysis of historical network activity and, through integration with WildPackets OmniPeek network analyzer, instant drill-down capabilities to the packet level. Businesses can use WatchPoint to monitor network health across data centers and branches.

Businesses can also use WatchPoint to examine current or previous network activity in close detail. For example, WatchPoint enables a leading financial services firm to verify, analyze, and troubleshoot financial data feeds.

"The challenge for distributed network monitoring solutions is to scale high-level network performance monitoring with its huge amount of associated network data down to the most pertinent network details," explained Tim McCreery, President and CEO of WildPackets. "With WatchPoint 3.0, we’ve re-architected our analysis platform to use big data architecture for data storage and analysis. The result is a solution that provides both long-term analytics and instant drill-down capabilities, delivering the essential facts needed for expert analysis. It’s like giving the NOC team a finely tuned microscope instead of a free plastic magnifier."

"TRAC's research shows that organizations are losing, on average, $72,000 per minute of unplanned network downtime," stated Bojan Simic, TRAC Research. "Having a network monitoring solution that can capture all of your data without sampling or averaging over a year is essential in understanding how you can make your network perform better, discovering security risks and finding intermittent problems before they snowball into network downtime."

Key Capabilities of WatchPoint 3.0

- Broad Network Coverage in a Single Pane: WatchPoint aggregates data from up to 20 network segments into a single view of network health, application trends, and business activity. The product summarizes data from OmniFlow-supported devices, NetFlow-supported devices, and sFlow-supported devices.

- Extensive Data Monitoring: WatchPoint monitors all data from all network flows and reports popular analytics like network utilization, top applications, top nodes, top flows, and VoIP analytics.

- Critical Business Application Monitoring: WatchPoint can track important business applications such as Oracle Financials, SAP or NetSuite. Customers can see at a glance whether specific applications are performing in compliance with SLAs and meeting end user needs.

- VoIP Analytics: WatchPoint provides a comprehensive Call Detail Record (CDR) for up to one year.

- Flexible Reporting: WatchPoint supports both ad hoc and scheduled PDF reports.

- Customization to Fit Businesses’ and Users’ Needs: WatchPoint allows users to create custom alerts and alarms based on monitored data. Additionally, it provides customizable displays for users, which can be accessed anywhere, anytime.

- Seamless Integration with other WildPackets Analysis and Troubleshooting Solutions: WatchPoint integrates with OmniPeek network analyzers, Omnipliance network appliances, and other WildPackets’ products.

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 ...

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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 ...

WildPackets Announces WatchPoint 3.0

WildPackets announced WatchPoint 3.0, a distributed network monitoring solution that uses big data technology to capture all network flow and packet analysis data with one-minute granularity for up to one year.

This provides the most comprehensive details and reports for service-level agreement analysis and reporting.

WatchPoint 3.0 provides up to one year of network analysis data, without sampling or averaging data, giving IT administrators, IT managers, and line-of-business managers the most comprehensive and detailed view of network performance available. Instead of cobbling together multiple short-term reports to understand long-term network performance, stakeholders can view reports that accurately represent long-term trends and baselines.

To support this detailed, scalable repository of network data, WatchPoint 3.0 uses a new big data architecture with a vast, flexible, and highly responsive data store that supports rich analysis of historical network activity and, through integration with WildPackets OmniPeek network analyzer, instant drill-down capabilities to the packet level. Businesses can use WatchPoint to monitor network health across data centers and branches.

Businesses can also use WatchPoint to examine current or previous network activity in close detail. For example, WatchPoint enables a leading financial services firm to verify, analyze, and troubleshoot financial data feeds.

"The challenge for distributed network monitoring solutions is to scale high-level network performance monitoring with its huge amount of associated network data down to the most pertinent network details," explained Tim McCreery, President and CEO of WildPackets. "With WatchPoint 3.0, we’ve re-architected our analysis platform to use big data architecture for data storage and analysis. The result is a solution that provides both long-term analytics and instant drill-down capabilities, delivering the essential facts needed for expert analysis. It’s like giving the NOC team a finely tuned microscope instead of a free plastic magnifier."

"TRAC's research shows that organizations are losing, on average, $72,000 per minute of unplanned network downtime," stated Bojan Simic, TRAC Research. "Having a network monitoring solution that can capture all of your data without sampling or averaging over a year is essential in understanding how you can make your network perform better, discovering security risks and finding intermittent problems before they snowball into network downtime."

Key Capabilities of WatchPoint 3.0

- Broad Network Coverage in a Single Pane: WatchPoint aggregates data from up to 20 network segments into a single view of network health, application trends, and business activity. The product summarizes data from OmniFlow-supported devices, NetFlow-supported devices, and sFlow-supported devices.

- Extensive Data Monitoring: WatchPoint monitors all data from all network flows and reports popular analytics like network utilization, top applications, top nodes, top flows, and VoIP analytics.

- Critical Business Application Monitoring: WatchPoint can track important business applications such as Oracle Financials, SAP or NetSuite. Customers can see at a glance whether specific applications are performing in compliance with SLAs and meeting end user needs.

- VoIP Analytics: WatchPoint provides a comprehensive Call Detail Record (CDR) for up to one year.

- Flexible Reporting: WatchPoint supports both ad hoc and scheduled PDF reports.

- Customization to Fit Businesses’ and Users’ Needs: WatchPoint allows users to create custom alerts and alarms based on monitored data. Additionally, it provides customizable displays for users, which can be accessed anywhere, anytime.

- Seamless Integration with other WildPackets Analysis and Troubleshooting Solutions: WatchPoint integrates with OmniPeek network analyzers, Omnipliance network appliances, and other WildPackets’ products.

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 ...