Best Application Performance Monitoring (APM) Software for Amazon EMR

Find and compare the best Application Performance Monitoring (APM) software for Amazon EMR in 2026

Use the comparison tool below to compare the top Application Performance Monitoring (APM) software for Amazon EMR on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    New Relic Reviews
    Top Pick
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    New Relic’s Application Performance Monitoring offers a streamlined solution for managing application performance through a cohesive platform that provides immediate insights into your complete technology infrastructure. Tailored for enterprise requirements, this tool enables decision-makers to oversee application performance, boost reliability, and improve user experience. With comprehensive features such as code-level visibility, AI-driven alerts, and Digital Experience Monitoring (DEM), along with recent advancements like AI Monitoring and Transaction 360, teams can quickly detect and address issues before they affect users. Enhance performance monitoring, unify your tools, and maximize resources to confidently drive digital transformation forward. Upgrade to New Relic APM now and stay ahead of application-related challenges.
  • 2
    Pepperdata Reviews

    Pepperdata

    Pepperdata, Inc.

    Pepperdata autonomous, application-level cost optimization delivers 30-47% greater cost savings for data-intensive workloads such as Apache Spark on Amazon EMR and Amazon EKS with no application changes. Using patented algorithms, Pepperdata Capacity Optimizer autonomously optimizes CPU and memory in real time with no application code changes. Pepperdata automatically analyzes resource usage in real time, identifying where more work can be done, enabling the scheduler to add tasks to nodes with available resources and spin up new nodes only when existing nodes are fully utilized. The result: CPU and memory are autonomously and continuously optimized, without delay and without the need for recommendations to be applied, and the need for ongoing manual tuning is safely eliminated. Pepperdata pays for itself, immediately decreasing instance hours/waste, increasing Spark utilization, and freeing developers from manual tuning to focus on innovation.
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