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October 18, 2012

Compuware Announces Pricing for APM's dynaTrace Enterprise for Hadoop

Compuware Corporation recently announced that APM’s (News - Alert) dynaTrace Enterprise for Hadoop, delivering Hadoop performance optimization, 24/7 job visibility and automated hotspot analysis, will now be offered at a starting price of just $1,000 per Hadoop Java Virtual Machine (JVM).

Key benefits of the company's dynaTrace Enterprise include easy-to-deploy and -manage advanced dashboards, delivering 100 percent deep visibility into Hadoop MapReduce performance without the need for code changes; quick mean-time-to-resolve (MTTR) via one-click hotspot analysis of MapReduce jobs, which allows users to identify root cause in minutes instead of hours or days; and easy Hadoop environments optimization, ensuring savings in costs while providing benefits such as deep insight into how MapReduce jobs use resources, scaling across cluster and automated performance analytics.

"Hadoop is a critical part of our infrastructure and is used by multiple stakeholders to offer brand marketing insights to our customers,” said Amit Gupta, director of Systems Engineering at Media6Degrees (News - Alert) (m6d). “We were amazed by the deep visibility into MapReduce jobs that Compuware dynaTrace Enterprise provided out-of-the-box. With dynaTrace's automated hotspot analysis, we were able to pinpoint the root causes of MapReduce job issues within minutes instead of days. We were also able to quickly optimize our Hadoop environment, which has resulted in significant cost savings.”

“And being a high growth company, with little time to learn and manage new performance systems, we've been very pleased with the ease of use and myriad automatic capabilities," Gupta added.

The Compuware (News - Alert) dynaTrace Enterprise incorporating PurePath Technology has been developed to deliver never-before-seen visibility into Hadoop applications, while ensuring greater scalability and support for elastic environments.

Other benefits include easy monitoring of Hadoop cluster overall, spanning individual machines, monitor CPU, memory, disk I/O and garbage collection, allowing users to keep a track of system health and introducing fixes before they impact SLAs; and Automatic MapReduce Error Correlation With Job, Task and Method level Detail supporting quick MTTR.

Edited by Braden Becker

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