Maximize Your Existing Big Data Infrastructure Investment

Pepperdata helps you increase hardware utilization and eliminate or reduce millions of dollars in hardware costs.

Understand Application Performance and APM

Configure and tune Hadoop and Spark applications to maximize resource allocation with insights from Pepperdata’s proven experience on hundreds of  big data clusters at Fortune 1000 companies.

Chartboost Realizes Significant Performance Boost and Cost Savings on their Hadoop AWS Cluster

On deployment, Pepperdata Platform Spotlight enabled Chartboost the deep visibility to pinpoint and troubleshoot critical issues in their Hadoop cluster and enable them to reduce their total AWS node count by 30 percent.

Before Pepperdata, we experimented with various approaches to solve our performance issues, but we couldn’t see deep enough into the cluster. Pepperdata shined a bright light into our Hadoop environment and provided the detailed data that helped us isolate and resolve the problem.- Software Architect at Philips Wellcentive
At Rubicon Project, having the appropriate visibility and insight into our Big Data applications is extremely important when delivering detailed reports to our clients and meeting our SLA. We challenged Pepperdata to find a solution to profile our applications before going to production that would help us maintain our customer SLA as we introduce new applications. Pepperdata listened to us and quickly understood the problem we were trying to address.- Senior Systems Engineer at Rubicon Project

Request a trial to see firsthand how Pepperdata big data solutions can help you achieve big data performance success. Pepperdata’s proven APM solutions provide a 360° degree view of both your platform and applications, with realtime tuning, recommendations, and alerting. See and understand how Pepperdata big data performance solutions helps you to quickly pinpoint and resolve big data performance bottlenecks. See for yourself why Pepperdata’s big data APM solutions are used to manage performance on over 30K Hadoop production clusters.

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