Platform Spotlight
Pepperdata Platform Spotlight continuously monitors and collects unique data that is not available anywhere else — about your hosts, queues, users, applications and all relevant resources, and provides you a 360° cluster view that enables you to quickly diagnose performance issues and make resource decisions about your big data platform based on user priorities and needs. Platform Spotlight leverages AI-driven resource management to automatically tune Hadoop and Spark clusters and recapture wasted capacity. Create alerts to identify root causes, and receive recommendations to rightsize containers, queues and other resources.
360° Platform View
Create a Holistic Source of Performance Truth Across Your Big Data Clusters.
A Single Source of Operational and Performance Truth
Complete Instrumentation of Your
Big Data Ecosystem
Quantify the Impact Apps
have on the Cluster and the Impact
the Cluster has on Apps
Attribute Accurate Costs to Users
and Business Units
Real-time Platform Tuning
Automatically Recover Wasted Cluster Resources.
Maximize Your Existing Infrastructure Investment
Autoscale Big Data Cluster Resources for Peak Efficiency
Platform Recommendations
Create a holistic source of application performance truth across your big data clusters.
Size Queues Appropriately Based on Criticality
Size Containers for Optimal Resource Consumption
Accurately Forecast Resource Needs
Platform Alerting
Create and Receive Alerts that Identify Root Causes.
Identify Who is Blowing Up Your Big Data Cluster
Identify Which Hadoop and Spark Applications Will Miss Their SLAs
Identify Resource Contention on Your Multi-tenant Big Data Platform
Identify Underperforming or Failing Hardware
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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.
Ian O’Connell, Software Engineer at Stripe and Pepperdata Technology Advisory Board Member -
Chartboost is the world’s largest mobile games-only advertising platform, reaching one billion active players around 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..
Michael McGowan, Manager of Data Engineering at Chartboost
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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.