Pepperdata Application Spotlight is a big data application profiler that automatically captures and analyzes performance metrics to provide observability across resource utilization and costs while also providing optimization tuning recommendations. Working with a variety of technologies, including Spark, Hadoop, Impala, Hive, and Kafka to name a few, Application Spotlight enables you to cut troubleshooting time, ensure optimal performance, and maintain SLAs.
Application Spotlight provides you with a comprehensive view of all your data in one place, empowering you to improve efficiency and deliver the best big data application performance. With our unified platform you can:
Improve the performance and efficiency of your applications to achieve optimal application performance on multi-tenant systems by configuring alerts and utilizing recommendations. Application Spotlight allows you to:
Query Spotlight provides insightful information on Hive query execution and database performance, so query workloads can be tuned, debugged, and optimized for better performance and reduced costs. Use Query Spotlight to:
Streaming Spotlight enables IT operations teams to get detailed, near real-time visibility into Kafka cluster metrics, broker health, topics, and partitions within the dashboard. With this data, you can reduce troubleshooting time, ensure optimal performance, and maintain SLAs. Use Streaming Spotlight to:
Automatically optimize your big data and deliver superior application performance in the cloud with Pepperdata for Amazon EMR. Application Spotlight is available on AWS Marketplace. In addition to optimizing application performance, get full-stack observability, automated tuning with managed autoscaling, and real-time insights across all of your EMR instances—all in one place. Automatically optimize your big data and deliver superior application performance. Application Spotlight allows you to:
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.