Skip to main content

Virtana Launches Public Sector Division

Virtana launched a division of the company dedicated to delivering modern observability and AI solutions for federal, state, and local government agencies. 

Purpose-built for the public sector, the AI-powered Virtana Platform provides a unified view across applications, services, and infrastructure, correlating user impact, service dependencies, performance bottlenecks, and cost drivers in real time—whether in secure, on-premises facilities or multi-cloud environments. 

The Virtana Platform provides:

  • AI at Lower Risk & Cost – Optimized GPU utilization and proactive bottleneck prevention keep AI and data-intensive initiatives efficient and accountable, whether supporting public safety, education, or university research.
  • Faster MTTR & Higher Service Resilience – Correlated telemetry and dependency maps reduce time to isolate issues and restore services, improving reliability for everything from citizen-facing portals to research systems and transportation networks.
  • End-to-End Cost Optimization and Risk Mitigation – Holistic visibility into performance, capacity, and spend enables agencies to reallocate resources, prevent overruns, and reduce operational risk across programs and projects.
  • Operational Transparency Across Environments – A consistent view across multi-cloud, on-premises, edge, and dark data centers removes silos and blind spots, helping agencies, schools, and aerospace organizations maintain compliance and operational continuity.
  • Flexible, Future-Ready Platform – Modular observability across services, containers, infrastructure, and AI workloads allows organizations to adopt new capabilities incrementally, aligning modernization with evolving budgets, regulatory requirements, and strategic goals.

The public sector initiative will drive sector-specific solutions and services that support key public sector use cases, including:

Federal

  • Civilian Agencies - Cross-program transparency and cost control; accelerate ATO renewals with evidence-rich telemetry and change tracking.
  • Defense & Intelligence - Readiness for large-scale AI/ML and mission systems: GPU fleet health, edge observability, dependency mapping, and rapid fault isolation in disconnected ops.
  • Space & Research - HPC/AI pipeline visibility from ingest to inference; capacity planning to meet launch windows and research deadlines.

State & Local

  • Education – Optimize campus workloads, track cost and performance by department or grant, and protect sensitive data with scoped telemetry.
  • Emergency Management - Surge-ready capacity planning, situational observability during incidents, and post-event forensics with retained logs/metrics.
  • Smart Communities & Transportation - Real-time service health for IoT/SCADA, curb-to-core dependency mapping, and incident triage with automatic impact analysis.

Beyond these core capabilities, the Virtana Platform also delivers advanced Event Intelligence powered by high-fidelity data correlation across every layer of the stack. Unlike other tools that surface generic alerts or partial insights, Virtana provides the precision and context agencies need to understand true root cause and impact in real time. This differentiation is why federal, state, and local agencies rely on Virtana for decisions that demand accuracy, accountability, and resilience.

"The public sector is facing perhaps the greatest challenges in the endeavor to modernize systems and processes," said Paul Appleby, CEO of Virtana. "Virtana is already helping public sector agencies achieve their rigorous modernization goals and this has become a key pillar of our business. Unlike other providers that offer only surface-level alerts, Virtana delivers high-fidelity data and advanced Event Intelligence that provide the clarity agencies need to act with confidence. We are expanding our capabilities that enable the public sector to deliver secure AI solutions at scale, manage costs with capacity and governance insights, and ensure operational resilience."

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.

Virtana Launches Public Sector Division

Virtana launched a division of the company dedicated to delivering modern observability and AI solutions for federal, state, and local government agencies. 

Purpose-built for the public sector, the AI-powered Virtana Platform provides a unified view across applications, services, and infrastructure, correlating user impact, service dependencies, performance bottlenecks, and cost drivers in real time—whether in secure, on-premises facilities or multi-cloud environments. 

The Virtana Platform provides:

  • AI at Lower Risk & Cost – Optimized GPU utilization and proactive bottleneck prevention keep AI and data-intensive initiatives efficient and accountable, whether supporting public safety, education, or university research.
  • Faster MTTR & Higher Service Resilience – Correlated telemetry and dependency maps reduce time to isolate issues and restore services, improving reliability for everything from citizen-facing portals to research systems and transportation networks.
  • End-to-End Cost Optimization and Risk Mitigation – Holistic visibility into performance, capacity, and spend enables agencies to reallocate resources, prevent overruns, and reduce operational risk across programs and projects.
  • Operational Transparency Across Environments – A consistent view across multi-cloud, on-premises, edge, and dark data centers removes silos and blind spots, helping agencies, schools, and aerospace organizations maintain compliance and operational continuity.
  • Flexible, Future-Ready Platform – Modular observability across services, containers, infrastructure, and AI workloads allows organizations to adopt new capabilities incrementally, aligning modernization with evolving budgets, regulatory requirements, and strategic goals.

The public sector initiative will drive sector-specific solutions and services that support key public sector use cases, including:

Federal

  • Civilian Agencies - Cross-program transparency and cost control; accelerate ATO renewals with evidence-rich telemetry and change tracking.
  • Defense & Intelligence - Readiness for large-scale AI/ML and mission systems: GPU fleet health, edge observability, dependency mapping, and rapid fault isolation in disconnected ops.
  • Space & Research - HPC/AI pipeline visibility from ingest to inference; capacity planning to meet launch windows and research deadlines.

State & Local

  • Education – Optimize campus workloads, track cost and performance by department or grant, and protect sensitive data with scoped telemetry.
  • Emergency Management - Surge-ready capacity planning, situational observability during incidents, and post-event forensics with retained logs/metrics.
  • Smart Communities & Transportation - Real-time service health for IoT/SCADA, curb-to-core dependency mapping, and incident triage with automatic impact analysis.

Beyond these core capabilities, the Virtana Platform also delivers advanced Event Intelligence powered by high-fidelity data correlation across every layer of the stack. Unlike other tools that surface generic alerts or partial insights, Virtana provides the precision and context agencies need to understand true root cause and impact in real time. This differentiation is why federal, state, and local agencies rely on Virtana for decisions that demand accuracy, accountability, and resilience.

"The public sector is facing perhaps the greatest challenges in the endeavor to modernize systems and processes," said Paul Appleby, CEO of Virtana. "Virtana is already helping public sector agencies achieve their rigorous modernization goals and this has become a key pillar of our business. Unlike other providers that offer only surface-level alerts, Virtana delivers high-fidelity data and advanced Event Intelligence that provide the clarity agencies need to act with confidence. We are expanding our capabilities that enable the public sector to deliver secure AI solutions at scale, manage costs with capacity and governance insights, and ensure operational resilience."

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.