CloudPhysics Adds Big Data Monitoring Features for VMware Data Centers

Big Data meets the software-defined data center in the latest offering from CloudPhysics, which has updated its SaaS benchmark and monitoring platform with new metric features for VMware (VMW) users.

The company announced the new features, called Global Metrics, at VMworld this week. The software works by continuously monitoring performance metrics of a particular data center and comparing them with global data from other server arrays, with the goal of allowing users "to instantly identify areas for improvement in their own environments as well as specific actions for achieving better data center health, performance and efficiency," according to CloudPhysics.

The functionality complements another CloudPhysics feature, Daily Insights, which collects information on data center performance from across the various nodes within a single data center.

The company is pitching the solution as a new way for enterprises to leverage Big Data in optimizing data center performance and preventing disasters. "Today's announcement delivers further on CloudPhysics' commitment to use Big Data to help IT teams make smarter operational decisions for better data centers," said John Blumenthal, CloudPhysics vice president of Product management. "We continue to formulate new ways to put data to work for our customers, yielding relevant insights at the right time, in the right context."

Alongside the Global Insights announcement, CloudPhysics also took advantage of VMworld to provide details on another new feature, Workload Shapes. That software, which provides visualizations to help administrators monitor the performance and efficiency of data storage, remains currently in technology-preview mode. When fully ready for production, however, a solution such as Workload Shapes stands to play an important role in data centers as software-defined storage increasingly becomes the norm, making traditional tools for monitoring and optimizing storage performance less useful.