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ExtraHop 6.2 Announced

ExtraHop announced several major platform enhancements as part of version 6.2.

These upgrades, supported by analytics and machine learning, provide IT teams situational insight and forensic capabilities required to make informed, data-driven decisions. The ExtraHop Platform's analytics-first workflow now scales to deliver 40Gbps line-rate continuous packet capture, while flexible licensing models for storage eliminate the data tax for extended lookback, saving up to 50 percent over traditional Network Performance Monitoring and Diagnostics (NPMD) tools.

With the latest updates, ExtraHop flips the traditional network analytics model on its head with an analytics-first approach that delivers real-time visibility into the performance, availability, and security of every IT system, from the edge to the cloud. Machine learning proactively surfaces anomalies, which can be easily and rapidly investigated from high-level performance metrics to individual transactions to packets in a matter of clicks rather than hours.

The following new capabilities are included in ExtraHop version 6.2:

- 40Gbps line-rate continuous packet capture provides visibility at scale for the digital enterprise.

- Extended storage model offers lookback at up to 50 percent less than competitive NPMD offerings, eliminating the data tax associated with the forensic investigation of performance and security issues. *New continuous packet capture for virtual environments extends visibility everywhere IT assets reside, providing a unified, all-up view of every transaction occurring within the organization.

- Audience-specific dashboards that surface analytics based on LDAP privileges, giving teams access to the data they need securely.

- The addition of nested queries to visual query language simplify transaction record search.

- Integration with ServiceNow further simplifies the process, automatically ticketing and triaging events to keep IT teams focused on the most critical issues.

"Process transformation cannot happen without tools to support it, and the traditional packets-first NPMD model has rendered proactive, strategic operations virtually impossible," said Jesse Rothstein, CTO and co-founder of ExtraHop. "At ExtraHop, we've recognized from the beginning that the scale, complexity, and dynamism of modern IT couldn't be addressed with post-hoc analysis of data. Modern IT demands analytics that are real-time, at scale, as well as intelligent, actionable, and predictive. We've put the NPMD market on notice: this is a new era for analytics, and we're already way out ahead."

ExtraHop 6.2 and ExtraHop Addy will be generally available on April 19, 2017.

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ExtraHop 6.2 Announced

ExtraHop announced several major platform enhancements as part of version 6.2.

These upgrades, supported by analytics and machine learning, provide IT teams situational insight and forensic capabilities required to make informed, data-driven decisions. The ExtraHop Platform's analytics-first workflow now scales to deliver 40Gbps line-rate continuous packet capture, while flexible licensing models for storage eliminate the data tax for extended lookback, saving up to 50 percent over traditional Network Performance Monitoring and Diagnostics (NPMD) tools.

With the latest updates, ExtraHop flips the traditional network analytics model on its head with an analytics-first approach that delivers real-time visibility into the performance, availability, and security of every IT system, from the edge to the cloud. Machine learning proactively surfaces anomalies, which can be easily and rapidly investigated from high-level performance metrics to individual transactions to packets in a matter of clicks rather than hours.

The following new capabilities are included in ExtraHop version 6.2:

- 40Gbps line-rate continuous packet capture provides visibility at scale for the digital enterprise.

- Extended storage model offers lookback at up to 50 percent less than competitive NPMD offerings, eliminating the data tax associated with the forensic investigation of performance and security issues. *New continuous packet capture for virtual environments extends visibility everywhere IT assets reside, providing a unified, all-up view of every transaction occurring within the organization.

- Audience-specific dashboards that surface analytics based on LDAP privileges, giving teams access to the data they need securely.

- The addition of nested queries to visual query language simplify transaction record search.

- Integration with ServiceNow further simplifies the process, automatically ticketing and triaging events to keep IT teams focused on the most critical issues.

"Process transformation cannot happen without tools to support it, and the traditional packets-first NPMD model has rendered proactive, strategic operations virtually impossible," said Jesse Rothstein, CTO and co-founder of ExtraHop. "At ExtraHop, we've recognized from the beginning that the scale, complexity, and dynamism of modern IT couldn't be addressed with post-hoc analysis of data. Modern IT demands analytics that are real-time, at scale, as well as intelligent, actionable, and predictive. We've put the NPMD market on notice: this is a new era for analytics, and we're already way out ahead."

ExtraHop 6.2 and ExtraHop Addy will be generally available on April 19, 2017.

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In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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 ...