Developing distributed big data applications is complex. Developing fast and efficient Spark applications requires an thorough understanding of big data performance metrics and tuning parameters. Pepperdata automatically delivers job-specific application recommendations based on industry best practices and in-depth knowledge of big data performance metrics and performance tuning.
Change configuration parameters to optimize performance
Get self-service recommendations on data partitioning and serialization.
Tune CPU and memory reservations based on actual consumption
Get self-service recommendations on container sizes and heap reservations.
Change queue selection or launch time based on cluster activity
Identify the best queue and launch time for applications based on current workloads.
Key Performance Indicators
- Improves application efficiency and performance.
- Increases productivity.
Rubicon Project Improves Big Data Performance and
Streamlines Automated Advertising Solution
Rubicon Project automates the process of buying and selling of advertising for advertisers, publishers, and ad agencies. Platform Spotlight gave Rubicon Project the granular visibility they needed to quickly pinpoint, troubleshoot, and resolve problems in their multi-tenancy Hadoop cluster.
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.