Pepperdata and AWS Help Your Big Data Reach Peak Performance

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 175 fully-featured services from data centers around the world. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster. By running the Pepperdata solution on AWS, enterprises can automatically improve the performance of their big data systems. Pepperdata for Amazon EMR provides full-stack observability, automated tuning, and real-time insights across all EMR instances—all in one place. This joint partnership allows customers like Rubicon Project, a leading technology company, to increase throughput by 50%, slash troubleshooting time, and more.

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Why Pepperdata on AWS?

  • Improve performance to meet every SLA: The Pepperdata solution automatically tunes your big data environment to deliver the best application performance for even your most challenging workloads. 
  • Keep costs in line: Cut infrastructure costs by relying on Pepperdata to automatically optimize node performance and prevent application waste, enabling up to 50% more throughput.
  • Trusted by Fortune 500 enterprises: Fortune 500 enterprises rely on the Pepperdata solution to ensure the reliability and performance of over 50K+ nodes in production.

Take the Pepperdata Interactive Demo to See What Big Data Success Looks Like

Sign up to see how automatic optimization and full-stack observability can improve performance across your entire big data stack. No data or installation is required. Simply log in to start playing in the Pepperdata sandbox.

Take a free 15-day trial to see what Big Data success looks like

Pepperdata products provide complete visibility and automation for your big data environment. Get the observability, automated tuning, recommendations, and alerting you need to efficiently and autonomously optimize big data environments at scale.