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Virtana and Carahsoft Partner on Agentic Observability

Virtana and Carahsoft Technology Corp. announced a partnership. 

Under the agreement, Carahsoft will serve as Virtana’s Public Sector distributor, making the Virtana Agentic Observability Platform available to the Public Sector through Carahsoft’s reseller partners and NASA Solutions for Enterprise-Wide Procurement (SEWP) V, Information Technology Enterprise Solutions – Software 2 (ITES-SW2), The Interlocal Purchasing System (TIPS), OMNIA Partners, E&I Cooperative Services Contract, and The Quilt contracts.

This partnership makes it easier for Federal, State, Local, education, defense, and intelligence organizations to procure and deploy Virtana’s platform, accelerating IT modernization and laying the foundation for Agentic AI and autonomous IT operations.

“Government organizations are rapidly modernizing hybrid, multicloud, AI-enabled, and air-gapped environments,” said Paul Appleby, Chief Executive Officer of Virtana. “As applications, infrastructure, services, and AI systems become increasingly interconnected, operations teams need a unified understanding of how their entire environment operates. Together with Carahsoft, we are making it easier for agencies to adopt the Virtana Agentic Observability Platform, giving them the unified system understanding needed to enable Agentic AI, accelerate autonomous IT operations, and maximize the value of every technology investment.”

Through Carahsoft’s reseller ecosystem, agencies now have streamlined access to the Virtana Agentic Observability Platform, enabling them to modernize and automate operations across applications, infrastructure, and AI systems in complex hybrid, multicloud, and air-gapped environments, all while building the trusted operational foundation for Agentic AI and autonomous IT operations.

“Carahsoft is committed to providing Government agencies with innovative technologies that accelerate digital transformation and AI adoption," said Michael Adams, Program Executive for AI Solutions at Carahsoft. “By adding the Virtana Agentic Observability Platform to our portfolio, Carahsoft and our reseller partners are expanding access to advanced observability capabilities that help agencies simplify IT operations, improving visibility across complex environments and supporting the next generation of AI-driven initiatives. Together with Virtana, we are helping Public Sector agencies build a more resilient and intelligent foundation.”

The Virtana Agentic Observability Platform goes beyond fragmented legacy monitoring tools by delivering system-aware observability across applications, infrastructure, services, and AI systems. By ingesting high-fidelity telemetry from across the enterprise, Virtana creates a unified source of truth, continuously maps system topology and dependencies, builds real-time operational context, and applies agentic AI to reason across the entire execution stack. Diagnostic and remediation agents identify system constraints, determine root cause, recommend corrective actions, and automate operational workflows.

These capabilities are applied across four domains:

  • AI Factory Observability for AI applications, models, inference pipelines, GPUs, and supporting infrastructure.
  • Application Observability for application execution across services, Kubernetes, and the underlying infrastructure.
  • Infrastructure Observability for compute, virtualization, storage, networking and cloud, on-premise, hybrid, and air-gapped environments.
  • Service Observability for business services, dependencies, and end-to-end service health.

The result is faster root cause analysis, reduced operational risk, optimized infrastructure and AI operations, improved resilience, and greater mission readiness.

The Virtana Agentic Observability Platform is available now through Carahsoft and its reseller partners.

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Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

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Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...

Virtana and Carahsoft Partner on Agentic Observability

Virtana and Carahsoft Technology Corp. announced a partnership. 

Under the agreement, Carahsoft will serve as Virtana’s Public Sector distributor, making the Virtana Agentic Observability Platform available to the Public Sector through Carahsoft’s reseller partners and NASA Solutions for Enterprise-Wide Procurement (SEWP) V, Information Technology Enterprise Solutions – Software 2 (ITES-SW2), The Interlocal Purchasing System (TIPS), OMNIA Partners, E&I Cooperative Services Contract, and The Quilt contracts.

This partnership makes it easier for Federal, State, Local, education, defense, and intelligence organizations to procure and deploy Virtana’s platform, accelerating IT modernization and laying the foundation for Agentic AI and autonomous IT operations.

“Government organizations are rapidly modernizing hybrid, multicloud, AI-enabled, and air-gapped environments,” said Paul Appleby, Chief Executive Officer of Virtana. “As applications, infrastructure, services, and AI systems become increasingly interconnected, operations teams need a unified understanding of how their entire environment operates. Together with Carahsoft, we are making it easier for agencies to adopt the Virtana Agentic Observability Platform, giving them the unified system understanding needed to enable Agentic AI, accelerate autonomous IT operations, and maximize the value of every technology investment.”

Through Carahsoft’s reseller ecosystem, agencies now have streamlined access to the Virtana Agentic Observability Platform, enabling them to modernize and automate operations across applications, infrastructure, and AI systems in complex hybrid, multicloud, and air-gapped environments, all while building the trusted operational foundation for Agentic AI and autonomous IT operations.

“Carahsoft is committed to providing Government agencies with innovative technologies that accelerate digital transformation and AI adoption," said Michael Adams, Program Executive for AI Solutions at Carahsoft. “By adding the Virtana Agentic Observability Platform to our portfolio, Carahsoft and our reseller partners are expanding access to advanced observability capabilities that help agencies simplify IT operations, improving visibility across complex environments and supporting the next generation of AI-driven initiatives. Together with Virtana, we are helping Public Sector agencies build a more resilient and intelligent foundation.”

The Virtana Agentic Observability Platform goes beyond fragmented legacy monitoring tools by delivering system-aware observability across applications, infrastructure, services, and AI systems. By ingesting high-fidelity telemetry from across the enterprise, Virtana creates a unified source of truth, continuously maps system topology and dependencies, builds real-time operational context, and applies agentic AI to reason across the entire execution stack. Diagnostic and remediation agents identify system constraints, determine root cause, recommend corrective actions, and automate operational workflows.

These capabilities are applied across four domains:

  • AI Factory Observability for AI applications, models, inference pipelines, GPUs, and supporting infrastructure.
  • Application Observability for application execution across services, Kubernetes, and the underlying infrastructure.
  • Infrastructure Observability for compute, virtualization, storage, networking and cloud, on-premise, hybrid, and air-gapped environments.
  • Service Observability for business services, dependencies, and end-to-end service health.

The result is faster root cause analysis, reduced operational risk, optimized infrastructure and AI operations, improved resilience, and greater mission readiness.

The Virtana Agentic Observability Platform is available now through Carahsoft and its reseller partners.

The Latest

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...