Pepperdata Total Performance Management Solutions

Pepperdata Total Performance Management Solutions

Pepperdata solutions address the pain points of big data developers and operators and provide enterprise solutions to monitor, tune, troubleshoot, and automate cluster optimization. Pepperdata application performance management (APM) and operations performance management (OPM) solutions are presented cohesively in a single pane of glass so that both operators and developers are receiving the same information and it is interpreted in one way.

Enterprise customers use Pepperdata products and services to troubleshoot performance problems in production, increase cluster utilization, and help developers understand and improve application performance. Pepperdata products and services work with customer big data systems both on-premise and in the cloud. Pepperdata products improve collaboration between development and operations teams by providing both an application as well as cluster view of performance. Pepperdata products, are used to monitor and manage mixed workloads from frameworks such as Spark, MapReduce, Kafka, Tez, Solr, and Impala.

For Developers and Users

For Operators

Application Spotlight

Self-Service Application Performance Management (APM) Portal

Pepperdata® Application Spotlight is a self-service APM portal that enables big data application developers to generate application-specific recommendations to improve application performance, highlight applications that need attention, automatically identify bottlenecks, and alert on duration, failure conditions, and resource usage.

Cluster Analyzer

Operations Performance Management (OPM)

Pepperdata® Cluster Analyzer provides fine-grained visibility into workloads, down to the task level, to drastically decrease troubleshooting time via the use of the most comprehensive set of correlated big data metrics available.

Capacity Optimizer Add-on Module

Ops Performance Management

Pepperdata® Capacity Optimizer is an optional add-on module that leverages active resource management features to dynamically alleviate inefficiencies and bottlenecks without the need for manual job tuning or cluster tuning. Enterprise deployments typically achieve a 30-50% increase in throughput performance when Capacity Optimizer is enabled.