Virtana
- , , San Jose, California,
- 2008
- 500
- Website
About
Virtana (formerly Virtual Instruments) provides AI-powered software observability solutions to simplify hybrid cloud complexity and accelerate digital transformation. Founded in 2008, more than 260 Global 2000 enterprise customers such as AstraZeneca, Dell, Apple, Paypal, Geico, Costco, Nasdaq, and Boeing, have long valued Virtana as a partner in monitoring and optimizing their on-premises and cloud infrastructure.
Our new Virtana Platform is the industry’s only unified observability platform for migrating, optimizing, and monitoring application workloads across public, private, hybrid, and multi-cloud environments. Virtana Platform collects high-fidelity data and then applies AIOps technologies, including machine learning and advanced data analytics, to give our customers data-driven observability.
The platform enables a “know before you go” approach by providing intelligent observability into which workloads to migrate to the public cloud. It also ensures that unexpected costs and performance degradation are avoided once workloads are operating in the cloud. With the Virtana Platform, enterprises can confidently speed cloud adoption and reduce cloud operating costs by simplifying their IT environments.
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Something About AI Still Doesn’t Feel Right
Something About AI Still Doesn’t Feel Right
This report brings the current AI conversation together and makes sense of the signals people are seeing in isolation.
- Why AI can look like it’s slowing down and accelerating at the same time
- How work is changing at the task level, rather than through sudden job replacement
- Why productivity gains often come with increased pressure and workload
- What changes when AI moves inside tools instead of sitting alongside them
- Why readiness, not capability, is now the biggest constraint for organisations
- How agentic AI shifts the conversation from output to action
This report brings the current AI conversation together and makes sense of the signals people are seeing in isolation.
- Why AI can look like it’s slowing down and accelerating at the same time
- How work is changing at the task level, rather than through sudden job replacement
- Why productivity gains often come with increased pressure and workload
- What changes when AI moves inside tools instead of sitting alongside them
- Why readiness, not capability, is now the biggest constraint for organisations
- How agentic AI shifts the conversation from output to action