A new partnership between LiveAction and Corvil provides businesses with increased visibility into their IT networks, along with deeper analytic insights and stronger cybersecurity.
Together, the complementary network performance management platforms deliver increased productivity and efficiency for operations teams as well as improved digital experiences through faster detection and resolution of cyber threats and performance issues – oftentimes before they impact the end user.
Businesses that have high security and network performance demands, such as financial services, government, and others will realize even greater benefits from the combination of LiveAction’s flow-based network performance management, visualization, and analytics platform and Corvil’s packet-based network data analytics platform for streaming machine-time intelligence.
Together, the platforms deliver insights from multiple network flow sources and packet-level data. This provides customers with complete visibility and enhanced device management capabilities across global networks as well as a deeper view into the detailed communications, indicators of compromise, users, devices, services, and application details necessary to effectively drive today’s businesses.
“Optimizing the delivery of business services across large, complex infrastructures requires rich insights across multiple data sets,” said Dennis Drogseth, VP, Enterprise Management Associates. “Corvil’s partnership with LiveAction is a perfect example of what’s needed to provide yet more robust depth and insight to this very multi-dimensional challenge—from capturing transactional behaviors across the network, to in-depth views of volumes flows and impacts, to integrated awareness of security-sensitive activities, to hooks into change and capacity management and optimization—and doing this with the breadth of understanding to support the growing world of cloud and hybrid infrastructure interdependencies.”
“From transacting billions of dollars to delivering life-saving messages, to enabling voice and video collaboration, networks are the lifeblood of every business today,” said David Murray, Chief Business Development Officer, Corvil. “Corvil enriches LiveAction’s flow data and visualization with our own granular visibility into networks, applications, and user activity, to assure overall business performance, enable faster diagnosis of problems, and improve cybersecurity posture. As our joint customers are challenged to do more with less budget and time, we believe this collaboration allows us to bolster their productivity through streamlined workflows by joining an expanded set of network-based machine data sources, insights, and capabilities across our two products.”
LiveAction boosts network performance by proactively spotting potential issues, providing analytics into network traffic flow and offering historical playback of network activities to reenact a point of failure from any time. Corvil complements LiveAction’s LiveNX platform by further diagnosing the source of complex infrastructure and application problems through continuous packet capture, micro-level network visibility and forensics, operations analytics, and cyber surveillance of users, infrastructure, applications, and services.
“Partnering with Corvil brings together two powerful, complementary network performance management platforms,” said Christian Barr, VP of Marketing, LiveAction. “Our integrated solution will provide customers with granular network data analytics and forensics and the much-needed insight across their network to deliver powerful digital experiences and meet compliance requirements.”
The Latest
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 ...
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.