HPE has announced support for 3PAR storage with its HPE InfoSight cloud analytics product, acquired with Nimble, along with new updates to InfoSight focused on proactive recommendations. Even before the conference officially begins, HPE is releasing announcements that customers can dig into more during the Discover event in Madrid this week.
As promised earlier, the InfoSight support for 3PAR is coming to all existing customers with active support contracts on their 3PAR arrays. Since 3PAR already had a rich set of telemetry built into the platform, the main hurdle of integration was letting the InfoSight Data Scientists loose on the raw data to map and make sense of it. HPE leveraged existing code and analytical models against the 3PAR data to do this quickly [HPE completed the Nimble acquisition just 7 months ago].
The first iteration of InfoSight for 3PAR includes three feature sets:
- analytics between the storage and virtualization platform to find root cause of problems that existing between storage and virtual machines
- a unified cloud portal combining the HPE StoreFront Remote capabilities with InfoSight for trending, capacity predictions and health checks
- the foundations of predictive support, which in the future will eliminate most tier 1 and 2 support cases, instead routing cases directly to level 3 (aka. adoption of the Nimble Storage support model for 3PAR)
Not resting on past accomplishments, the InfoSight team also has a new set of capabilities it is unleashing to customers – Preemptive Recommendations. For these, HPE is drawing insights from the data it is getting from the storage and virtualization platform to make recommendations that prevent issues, improve performance and optimize the environment.
To a large degree, what HPE is talking about in preemptive analytics in InfoSight sounds a lot like the problems VMware is trying to solve in vSphere with proactive recommendations from vRealize Operations Manager (vROPS). Where these recommendations can potentially shine in InfoSight are in the deeper insights that correlate between the hardware and the software since InfoSight has deeper visibility into that platform. Clearly, all tech companies are realizing that there is tremendous value in machine learning applied to IT support.
HPE is using machine learning and expert defined conditions to generate preemptive recommendations. Since the learning engine is cloud based, the refinement and self-learning should power a number of wins for customers as the install-base widens and customers adopt this support tool, making it difficult to replicate for on-premises prediction engines.