Application Tuning

You need faster, more efficient applications in order to meet your SLAs. Pepperdata provides you with all the necessary data from the application as well as the cluster enabling you to make quick decisions. Additionally, Pepperdata automatically tunes applications that are repetitive for either resource efficiency or runtime.

A single source for application performance data in the context of the cluster

Self-service access to all of the data on your applications in one place. The ability to distinguish whether performance issues were caused by your application or other applications on the cluster.

AI-driven optimization of recurring applications

Recurring applications account for a substantial portion of workload. These applications frequently need to meet constantly changing SLAs. Pepperdata auto-tunes configurations to optimize resource utilization or runtime.

Key Performance Indicators

  • Improves runtime of applications.
  • Improves resource utilization.

Rubicon Project Improves Performance and
Streamlines Automated Advertising Solution

Pepperdata Platform Spotlight gave Rubicon Project, a leading technology company that automates the process of buying and selling of advertising for advertisers, publishers, and ad agencies, the granular visibility they needed to quickly pinpoint, troubleshoot, and resolve problems in their cluster.

I develop a lot of complex Spark code to perform ETL on Hadoop clusters. In these complex, large-scale systems, you must be able to understand where the performance bottlenecks are. Pepperdata Application Spotlight gives developers detailed time-series performance data for things like CPU, JVM memory, and I/O usage overlaid against Spark job stages. I’m excited about the direction Pepperdata is moving — letting developers quickly see problems in time-series views and tie them back to their actual Spark application code will be a very useful tool for developers working on production Spark applications.- Software Engineer at Stripe and Pepperdata Technology Advisory Board Member
the world every month. Chartboost utilizes Apache Spark on large Amazon EC2 Hadoop clusters for machine learning and ETL workflows. Understanding Spark application performance in these complex environments is always a challenge. As a current user of Pepperdata Platform Spotlight, it has been great to work with Pepperdata on the development of the Application Spotlight self-service portal software. It will give us a comprehensive insight into Spark jobs.”- Manager of Data Engineering at Chartboost

See firsthand how Pepperdata solutions bring APM to every phase of the big data DevOps cycle with solutions for monitoring, tuning, troubleshooting, and improving collaboration between teams.

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