By Udi Shagal, Analytics product manager, and Eran Samuni, Analytics R&D Manager — HP Performance Anywhere

Identifying anomalies and qualifying probable causes is an important process that leads to faster resolution and better performance. In this blog post, we explore how predictive analytics, machine learning and advanced correlation capabilities can work together to help automate anomaly isolation processes.

As companies seek to gain speed, agility, and cost savings out of their virtualization initiatives, trying to improve the utilization of their resources can be a difficult task.  IT organizations need analytic capabilities to help them optimize their virtualized environments and to help them make intelligence decisions when it comes to capacity planning for the future.  Guest blogger Shiva Prakash from HP’s Service Intelligence R&D team explains some of the tips and tricks for making optimization an easier task.

I’ve noticed an interesting trend happening lately.  It seems every few days, I see new reports predicting 2012 as the rise of analytics – especially around predictive analytics.  It seems to be “cool” to talk about data analytics.  And the discussions around the topic of analytics are everywhere, and impacting every industry.

What can HP offer in the way of data analytics to help with the issue of Big Data in IT Ops?

Vendors acknowledge that in any enterprise reporting tool, irrespective of how good the out of the box reports, it is impossible to consider every possible scenario found in the customer’s environment. A lot of effort in the development activities of reporting solutions goes into the ease of use, and ease of customization capabilities of the product. The lack of an easy customization capability leads to costs associated with ramp up on learning, training and maintenance of the customized reports.

To that end, HP Service Health Reporter (HP SHR), attempts to make the report customization easy for its users.

Krishna Mahadevan Ramakrishnan and Prapulla B, SHR R&D Engineers, explain...

Service Health Reporter (SHR) uses Sybase IQ, a Column based Database Management System (DBMS), to implement its Data Warehouse. The choice of DBMS technology in SHR proves to be an advantageous choice for data analytics, storage and aggregations.

Balasubramanya Ramananda of the SHR R&D team expains.

Last week at HP Discover in Vienna, we launched a new BSM predictive analytics tool called Service Health Analyzer.  Already, we have heard a lot of positive feedback.  Many have asked for a video demonstration of the tool at work. 

Ask and you shall receive.    This video shows you how SHA uses the Run-Time Service Model (RTSM)  to capture and correlate metric data with anomalies to help forecast issues.  Enjoy!

If you could forecast potential issues in your data center, what would it mean to you?  Would advance warning technology be useful?  If you could be notified early of an impending problem, would it benefit your business?

Announced this week at HP Discover Vienna, HP Service Health Analyzer is providing IT managers this exact capability -- to anticipate, prevent and remediate IT incidents before they impact the business. 

Service Health Analyzer (SHA) is a predictive analytics tool within HP’s Business Service Management Portfolio that will change the way IT manages data and operates the data center.  Much like weather forecasters are monitoring and predicting major hurricanes and cyclones, SHA is using advanced analytics to forecast IT storms, which can help you prevent problems from impacting your business.