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Compuware APM Offers Hadoop Performance Optimization

Compuware Corporation announced pricing for its deep transaction management solution for optimizing performance of Apache Hadoop applications - Compuware APM’s dynaTrace Enterprise for Hadoop will be offered starting at just $1,000 per Hadoop Java Virtual Machine (JVM).

Applications using Hadoop MapReduce suffer from many of the performance challenges and bottlenecks that plague current distributed applications, though the volume of performance data can be much larger. Optimizing compute and data distribution across nodes, assuring job execution efficiency, identifying I/O bottlenecks, tuning CPU and memory consumption amongst thousands of nodes requires deep insight into the Hadoop environment.

With its patented PurePath Technology, Compuware dynaTrace Enterprise provides visibility into Hadoop applications and supports these highly scalable, elastic environments in several unique ways:

- Zero-Configuration Instrumentation: Out-of-the-box dashboards for 100 percent deep visibility into Hadoop MapReduce performance, with no code changes required and easy to deploy and manage.

- One-Click Hotspot Analysis: Faster mean-time-to-resolve (MTTR) with one-click hotspot analysis of MapReduce jobs, including long-running and highly distributed jobs. See root cause in minutes instead of hours or days.

- Automated Performance Analytics: Optimize Hadoop environments and save costs with deep insight into how MapReduce jobs consume resources, scale across cluster and automated performance analytics from the task-level down to individual method execution times.

- Correlated Cluster Health Monitoring: Monitor Hadoop cluster overall and down to individual machines as well as monitor CPU, memory, disk, I/O and garbage collection to detect and correlate system health to job performance. Proactively fix issues before they impact SLAs.

- Automatic MapReduce Error Correlation With Job, Task and Method level Detail: For faster MTTR than any other approach in the market.

“The market for Hadoop applications is exploding,” said John Van Siclen, General Manager of Compuware’s APM business unit. “Our Hadoop customers seek a new generation APM approach that goes beyond log-file analysis and point tools. They expect an APM system that’s built for the Hadoop architecture, supports dynamic, elastic environments out-of-the-box, and is easy to deploy and use. Additionally, customers need this APM system to be affordable for the highly scalable Hadoop environments they run. We believe dynaTrace Enterprise, coupled with our pricing model, will accelerate the growth of the Hadoop market – making highly optimized, highly tuned Hadoop implementations much easier to achieve.”

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Compuware APM Offers Hadoop Performance Optimization

Compuware Corporation announced pricing for its deep transaction management solution for optimizing performance of Apache Hadoop applications - Compuware APM’s dynaTrace Enterprise for Hadoop will be offered starting at just $1,000 per Hadoop Java Virtual Machine (JVM).

Applications using Hadoop MapReduce suffer from many of the performance challenges and bottlenecks that plague current distributed applications, though the volume of performance data can be much larger. Optimizing compute and data distribution across nodes, assuring job execution efficiency, identifying I/O bottlenecks, tuning CPU and memory consumption amongst thousands of nodes requires deep insight into the Hadoop environment.

With its patented PurePath Technology, Compuware dynaTrace Enterprise provides visibility into Hadoop applications and supports these highly scalable, elastic environments in several unique ways:

- Zero-Configuration Instrumentation: Out-of-the-box dashboards for 100 percent deep visibility into Hadoop MapReduce performance, with no code changes required and easy to deploy and manage.

- One-Click Hotspot Analysis: Faster mean-time-to-resolve (MTTR) with one-click hotspot analysis of MapReduce jobs, including long-running and highly distributed jobs. See root cause in minutes instead of hours or days.

- Automated Performance Analytics: Optimize Hadoop environments and save costs with deep insight into how MapReduce jobs consume resources, scale across cluster and automated performance analytics from the task-level down to individual method execution times.

- Correlated Cluster Health Monitoring: Monitor Hadoop cluster overall and down to individual machines as well as monitor CPU, memory, disk, I/O and garbage collection to detect and correlate system health to job performance. Proactively fix issues before they impact SLAs.

- Automatic MapReduce Error Correlation With Job, Task and Method level Detail: For faster MTTR than any other approach in the market.

“The market for Hadoop applications is exploding,” said John Van Siclen, General Manager of Compuware’s APM business unit. “Our Hadoop customers seek a new generation APM approach that goes beyond log-file analysis and point tools. They expect an APM system that’s built for the Hadoop architecture, supports dynamic, elastic environments out-of-the-box, and is easy to deploy and use. Additionally, customers need this APM system to be affordable for the highly scalable Hadoop environments they run. We believe dynaTrace Enterprise, coupled with our pricing model, will accelerate the growth of the Hadoop market – making highly optimized, highly tuned Hadoop implementations much easier to achieve.”

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E-commerce is set to skyrocket with a 9% rise over the next few years ... To thrive in this competitive environment, retailers must identify digital resilience as their top priority. In a world where savvy shoppers expect 24/7 access to online deals and experiences, any unexpected downtime to digital services can lead to significant financial losses, damage to brand reputation, abandoned carts with designer shoes, and additional issues ...

Efficiency is a highly-desirable objective in business ... We're seeing this scenario play out in enterprises around the world as they continue to struggle with infrastructures and remote work models with an eye toward operational efficiencies. In contrast to that goal, a recent Broadcom survey of global IT and network professionals found widespread adoption of these strategies is making the network more complex and hampering observability, leading to uptime, performance and security issues. Let's look more closely at these challenges ...

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The 2025 Catchpoint SRE Report dives into the forces transforming the SRE landscape, exploring both the challenges and opportunities ahead. Let's break down the key findings and what they mean for SRE professionals and the businesses relying on them ...

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The pressure on IT teams has never been greater. As data environments grow increasingly complex, resource shortages are emerging as a major obstacle for IT leaders striving to meet the demands of modern infrastructure management ... According to DataStrike's newly released 2025 Data Infrastructure Survey Report, more than half (54%) of IT leaders cite resource limitations as a top challenge, highlighting a growing trend toward outsourcing as a solution ...

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Gartner revealed its top strategic predictions for 2025 and beyond. Gartner's top predictions explore how generative AI (GenAI) is affecting areas where most would assume only humans can have lasting impact ...

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AWS is a cloud-based computing platform known for its reliability, scalability, and flexibility. However, as helpful as its comprehensive infrastructure is, disparate elements and numerous siloed components make it difficult for admins to visualize the cloud performance in detail. It requires meticulous monitoring techniques and deep visibility to understand cloud performance and analyze operational efficiency in detail to ensure seamless cloud operations ...

Imagine a future where software, once a complex obstacle, becomes a natural extension of daily workflow — an intuitive, seamless experience that maximizes productivity and efficiency. This future is no longer a distant vision but a reality being crafted by the transformative power of Artificial Intelligence ...

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