CloudPhysics introduces Global and Daily Insights

CloudPhysics is also previewing its "workload shapes" technology, an industry-first that provides VMware administrators with a visual shorthand for quickly recognizing storage performance anomalies, and deep visibility for accelerating resolution.

"Today's announcement delivers further on CloudPhysics' commitment to use Big Data to help IT teams make smarter operational decisions for better datacenters," 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. From broad aggregation of operational metrics gathered across thousands of datacenters, to highly granular views into individual workload shapes, our data-driven insights give IT teams more power than ever before to understand, troubleshoot, and optimize their virtualized datacenters."

CloudPhysics' new features and technology preview will be unveiled at booth #640 at VMworld 2014, where the company is also sponsoring a contest to win Google Glass. In this show of skill, attendees can demonstrate their vSphere expertise by guessing the percentage change of key datacenter metrics over the past two years according to CloudPhysics' global data set.

CloudPhysics Product News Highlights
CloudPhysics' cloud-based platform collects and analyzes a daily stream of configuration, performance, failure and event data from a global user base, with a total of 50+ trillion samples collected to date. Combining this Big Data with unique patent-pending datacenter simulation and resource management techniques, CloudPhysics identifies global trends and patterns of behavior. This Collective Intelligence is passed on to customers through the algorithms that drive the new features and capabilities announced:
· Global Benchmarks and Daily Insights: A new interactive console provides Global and Daily Insights, both of which are continually refreshed. Global Insights compare a user's key datacenter metrics against those from CloudPhysics' unique global data set, providing useful benchmarks for evaluating relative performance, health and efficiency. Daily Insights aggregate alerts and recommendations generated by CloudPhysics across the datacenter and, with new hyperlinking capabilities, provide the ability to navigate and drill down contextually to gain deeper visibility, accelerate resolution and improve overall datacenter metrics.
· Enhanced Performance Troubleshooting: Building on the recently released Datastore Contention analytic, which provides insights into disk I/O contention at the datastore level, CloudPhysics' new VM Disk I/O Contention analytic focuses on VM-level performance. An interactive timeline visually correlates patterns among datastores/VMs, and dramatically simplifies the exploration of hotspots. The algorithm used to detect contention has been tuned and validated using CloudPhysics' Collective Intelligence.
· New Smart Alerts: "Guest Partition in VM Running Out of Space" and "Unused VMs" further expand CloudPhysics' set of SmartAlerts, first introduced in June. CloudPhysics evaluates all objects in the virtual datacenter against certain criteria (e.g., latency, duration, outstanding IOs, IOPS, etc.) and triggers Smart Alerts based on thresholds derived dynamically from patterns and trends observed across our global dataset. Users foresee when conditions are degrading and receive specific recommendations for preemptive measures.
· Workload Shapes (Technology Preview): CloudPhysics analyzes and characterizes storage workload spatial locality (sequentiality vs. randomness), dominant I/O block sizes, and the complete latency profile, then visualizes these into "workload shapes." Administrators quickly learn which shapes are "normal" for their environment and identify outliers that indicate performance troublespots, accelerating time to resolution. This deep visibility comes from unique underlying technology, in which every I/O is analyzed, ensuring anomalies don't get lost in the averages, which is what happens with most other tools.