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Apache Authors: Liz McMillan, Pat Romanski, Elizabeth White, Christopher Harrold, John Mertic

Related Topics: @BigDataExpo, Java IoT, Microservices Expo, Machine Learning , @CloudExpo, Apache

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Compuware APM Unveils Solution to Optimize Hadoop on Amazon Web Services

Insight into AWS Elastic MapReduce Provides Hotspot Analysis and One-Click to Root Cause Without Log Hassle

Compuware Corporation on Tuesday announced it has released an APM solution for Hadoop on Amazon Elastic MapReduce, (EMR) available now in the AWS Marketplace. This solution enables organizations to tame big data at scale, enabling customers to gain faster business value at lower cost, and furthers Compuware APM's ability to provide visibility and troubleshooting insight into big data workloads.

"Compuware APM combined with the AWS cloud provides customers with the technical capabilities they need to allow them to focus on their business," said Terry Hanold, Vice President, Cloud Commerce, AWS.

Powered by its patented PurePath Technology(R), Compuware APM profiles Amazon EMR jobs, providing drill-down dashboards that can pinpoint the root cause of failed jobs or performance hotspots with a single click.

Operation teams gain full visibility into cluster usage based on users or job types, enabling monitoring of service level agreements (SLAs) and charge-back models to consumers. By profiling Hadoop jobs in production, operations teams can quickly identify the issues, whether they are misconfigured or unbalanced clusters, poorly-coded workloads or unhealthy hosts. Developers, armed with exact detail shared by operations and QA, no longer have to guess at the performance of their code when running at massive scale.

Features and capabilities of Compuware APM solution with Amazon EMR include:

  • Profiling Hadoop jobs in production clusters to see which teams are utilizing the cluster and exactly why, to code level, a job takes minutes or hours to run.
  • Automatically identifying performance hotspots in Amazon EMR, such as whether the problem is due to a poor configuration, over-utilized or failed infrastructure, or inefficient code.
  • Eliminating the need to scour log files by identifying the root cause of a job failure in one click. Exceptions, stack traces and logged data are automatically identified by PurePath Technology, showing both where and why failures occur. Deep facts can be easily shared with development to quickly fix issues.

More Stories By Elizabeth White

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