Virtana

10/16/2026

AI is only as powerful as the operational context behind it. Enterprise environments generate enormous amounts of telemetry across applications, infrastructure, cloud, Kubernetes, networks, storage, and AI workloads. But fragmented telemetry creates fragmented understanding.

The Virtana Agentic Observability Platform changes that by continuously building unified system understanding, giving agentic AI the context to:
- Observe: See what is happening across the entire ex*****on system.
- Reason: Connect dependencies, distinguish symptoms from root cause, and cut through alert noise.
- Act: Investigate in natural language and enable intelligent remediation.

This is more than adding AI to observability. It is Agentic Observability: turning telemetry into understanding, and understanding into action.

Read the white paper:
https://hubs.la/Q04BpKxK0

10/15/2026

Preparing for AI takes more than protecting jobs. It requires rethinking how we support the systems and people powering the AI revolution.

In this Fast Company article, Virtana President and CEO Paul Appleby explores three critical challenges organizations must address as AI adoption accelerates: workforce transformation, growing energy demands, and the resilience of essential services.

The stakes are high. Virtana's latest research reveals that 52% of IT practitioners report persistent visibility gaps across their AI infrastructure, raising concerns about operational readiness as AI scales.

At Virtana, we believe AI innovation must be matched by the visibility, intelligence, and operational resilience needed to make it sustainable and trustworthy. Because the future of AI isn't just about what we can build. It's about how reliably we can run it.

Read Paul's full perspective in Fast Company:

We also need to focus on energy demand and essential services using AI.

10/13/2026

AI is moving faster than organizations can govern it. So how do we close the gap?

In a recent CIO article, Virtana Chief Product Officer Amit Rathi shares why understanding how IT teams actually work—not just how processes are documented—is essential to building effective AI.

That insight is central to Virtana's approach to agentic AI. Our agentic observability capabilities are designed to bring deep infrastructure context, intelligent root-cause analysis, and actionable insights together, enabling AI agents to reason and act with greater precision and confidence.

Because the future of autonomous IT isn't just about moving faster. It's about making smarter, more informed decisions with the right guardrails in place.

Read Amit's insights: https://hubs.la/Q04B3fDk0

CIOs are discovering that the biggest barrier to scaling AI isn’t the technology itself, but the organization’s ability to understand its own processes.

10/09/2026

Nutanix environments move faster when workload placement decisions are not guesswork.

Without real-time visibility into capacity, teams often slow provisioning, overprovision resources, and drive up costs. Virtana gives teams a system wide view of capacity so they can make fast, consistent placement decisions across their environment.

As one customer put it: "What took us months took about twenty minutes with Virtana."

This white paper explores how system aware observability helps organizations connect infrastructure, applications, and AI workloads into a single intelligent view: https://hubs.la/Q04zMzB70

10/08/2026

The Definition of "Application" Has Changed.

Treating the application as a bounded artifact no longer makes sense. What we call “the application” now spans the entire system required to run it. Its behavior emerges from CPUs, GPUs, schedulers, networks, storage systems, Kubernetes, cloud services, AI workloads, and LLM-driven ex*****on paths operating together in real time.

Virtana's eBook explores why the traditional definition of “the application” no longer holds. If your teams are stuck defending code during infrastructure-driven incidents or preparing for agent-driven operations, this guide reframes the problem: https://hubs.la/Q04zD1ls0

10/06/2026

Agentic AI is moving fast. But before AI agents can act, they need to understand.

In a new VentureBeat interview, Virtana CEO Paul Appleby makes the case that the next phase of agentic AI depends on something fundamental: causality.

“Without that foundation, AI agents inherit the same blind spots that constrain human operators, and they amplify those failures at machine speed.”

The challenge is bigger than AI infrastructure. Modern enterprise systems are deeply interconnected. An agent can’t reliably resolve a problem if it sees the alert but doesn’t understand the dependencies, operational context, and chain of cause and effect behind it.

That’s where Agentic Observability changes the equation: giving people and AI agents the system understanding to move from detecting symptoms, to reasoning about root cause, to taking governed action. It’s also the foundation Virtana is building into the Virtana Agentic Observability Platform.

As Paul puts it: “Once you get to causality, you can remediate.”

Read Paul’s full perspective in VentureBeat:

Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact [email protected].

10/06/2026

Modern IT environments span applications, infrastructure, networks, containers, cloud services, and shared runtime environments. Yet operations teams still manage them through disconnected tools and fragmented telemetry.

Agentic AI changes the equation, but only when AI agents have the context to understand what is happening across the entire environment and act on it. That is where Model Context Protocol (MCP) comes in. By giving AI agents a standardized way to access structured, machine readable operational context, MCP helps connect AI to the systems it needs to understand.

In our latest white paper, we explore how MCP can help move enterprise operations from tool centric monitoring to system aware, agentic AI driven operations and what this means for the future of IT operations.

Learn more: https://hubs.la/Q04zdqc70

10/02/2026

Question: "Where do you see organizations hitting their limits—not because of effort or talent, but because of sheer system complexity?"

In this clip, Virtana Chief Product Officer, Amit Rathi explains why more data does not automatically lead to better operations.

As system complexity grows, organizations are collecting more telemetry than ever while struggling to turn it into actionable insights. At the same time, rising observability costs are forcing some teams to monitor only part of their environments.

Watch the video to learn why intelligence, not just visibility, is becoming essential for modern IT operations.

09/30/2026

AI is changing the way enterprises operate, but many teams are still relying on fragmented monitoring to understand increasingly complex environments.

In this new Hot Seat Live with The Register with Tim Phillips, Virtana CEO Paul Appleby discusses why that observability gap matters and how Agentic Observability can give both teams and AI agents real-time context across the full technology environment to accelerate root cause analysis and remediation.

From hybrid infrastructure and AI systems to governance and resilience, the conversation explores what it takes to move beyond monitoring individual components and toward understanding how the full system works together.

Watch the conversation:

How agentic AI, real-time visibility, and stronger governance can help enterprises protect critical services and manage increasingly complex IT environments.

09/29/2026

Your application might show you where a problem appears.

But what if the real constraint is somewhere else?

Storage. Network. Kubernetes. GPU infrastructure. An AI workload.

As enterprise technology estates expand, application-level visibility alone may not provide the context teams and AI agents need to understand the dependencies behind performance.

A new IDC Spotlight sponsored by Virtana explores what this changing environment means for observability architecture—and why AI infrastructure now needs to be part of the operational picture.

Read the Spotlight: https://hubs.la/Q04yB3LR0