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GigaVUE Cloud Suite for VMware Obtains VMware Ready Certification

Gigamon announced that the GigaVUE Cloud Suite for VMware has obtained VMware Ready certification.

This milestone demonstrates delivery of comprehensive application visibility across complex hybrid environments, including east-west traffic, at scale. GigaVUE efficiently collects, aggregates, processes and selectively filters traffic before forwarding to the proper security and analytics tools, enabling network optimization and security. GigaVUE is now interoperable with VMware’s NSX-T and vCenter Server through APIs for improved agility, reduced manual management tasks and enhanced return on investment (ROI).

IT and InfoSec teams can now fortify their security and optimize their operations by:

- Automating deployment of virtual TAPs using NSX Dynamic Service Insertion

- Monitoring micro-segmented, multi-tenant environments

- Discovering new workloads and those dynamically relocated via VMware vMotion

“We are pleased that Gigamon and GigaVUE Cloud Suite for VMware qualifies for the VMware Ready logo, signifying to customers that it has met specific VMware interoperability standards and works effectively with VMware technologies. This signifies to customers that GigaVUE Cloud Suite for VMware can be deployed in production environments with confidence and can speed time to value within customer environments,” said Kristen Edwards, Director, Technology Alliance Partner Program at VMware.

“We must work together on simplifying cloud visibility. Gigamon and VMware have created a solution that automates deployment and discovery of new and relocated workloads, enabling next-generation digital enterprises to run fast and stay more secure,” said Ananda Rajagopal, VP of Products and Solutions at Gigamon. “Certified ecosystem solutions expedite successful deployment and operations and this latest product certification serves as a strong validation of our combined solutions for customers.”

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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 ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

GigaVUE Cloud Suite for VMware Obtains VMware Ready Certification

Gigamon announced that the GigaVUE Cloud Suite for VMware has obtained VMware Ready certification.

This milestone demonstrates delivery of comprehensive application visibility across complex hybrid environments, including east-west traffic, at scale. GigaVUE efficiently collects, aggregates, processes and selectively filters traffic before forwarding to the proper security and analytics tools, enabling network optimization and security. GigaVUE is now interoperable with VMware’s NSX-T and vCenter Server through APIs for improved agility, reduced manual management tasks and enhanced return on investment (ROI).

IT and InfoSec teams can now fortify their security and optimize their operations by:

- Automating deployment of virtual TAPs using NSX Dynamic Service Insertion

- Monitoring micro-segmented, multi-tenant environments

- Discovering new workloads and those dynamically relocated via VMware vMotion

“We are pleased that Gigamon and GigaVUE Cloud Suite for VMware qualifies for the VMware Ready logo, signifying to customers that it has met specific VMware interoperability standards and works effectively with VMware technologies. This signifies to customers that GigaVUE Cloud Suite for VMware can be deployed in production environments with confidence and can speed time to value within customer environments,” said Kristen Edwards, Director, Technology Alliance Partner Program at VMware.

“We must work together on simplifying cloud visibility. Gigamon and VMware have created a solution that automates deployment and discovery of new and relocated workloads, enabling next-generation digital enterprises to run fast and stay more secure,” said Ananda Rajagopal, VP of Products and Solutions at Gigamon. “Certified ecosystem solutions expedite successful deployment and operations and this latest product certification serves as a strong validation of our combined solutions for customers.”

The Latest

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 ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...