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Self-driving IT specialist Virtual Instruments rebrands as Virtana
by Max Smolaks
Still believes data centers should be managed by algorithms
by Max Smolaks 22 October 2019
American software developer Virtual
Instruments, which makes tools for AI-assisted IT management, has changed its
name to Virtana.
The company has also launched CloudWisdom, a new hybrid IT management product delivered as a service.
Virtana is a trailblazer in the emerging
AIOps field, believing that server farms are best managed in partnership with
algorithms that can sift through reams of logs and metrics to find ways to
reduce IT infrastructure costs or identify issues that could cause downtime
down the line.
Its products use a combination of real-time monitoring, big data analytics, and increasingly,
artificial intelligence and machine learning technologies.
dots between the health and performance of individual data center and public
cloud resources with their exact impact on application SLAs and performance is
the holy grail for enterprises embarking on their digital transformation
journey,” explained Torsten Volk, senior analyst at Enterprise Management
combining its heritage of highly granular real-time application infrastructure
monitoring with advanced machine learning and analytics capabilities from the
Metricly (formerly Netuitive) acquisition, to ultimately offer comprehensive
monitoring and policy-driven capacity optimization and automated problem
In addition to changing its name, Virtana has advanced its business model to include
self-service SaaS and introduced downloadable 30-day trial versions of its software
CloudWisdom is one of the first products to get the SaaS treatment. The software performs both cloud monitoring and cost analysis – the latter is a complicated, contentious subject ignored by most infrastructure management providers.
CloudWisdom monitors middleware including databases, messaging platforms,
microservices, and containers, as well as dozens of leading cloud
One term – data analytics – having two meanings – AI and SSBI – this is the classic setup for misunderstandings, failing project pitches, and failed projects. But what exactly are the differences between AI and SSBI? And are they complementing or competing concepts?