Spark 2017-06-12T14:26:36+00:00

Application Performance Management for Spark

Optimize, troubleshoot and analyze all applications on the Spark Core

Manage all your applications on the Spark Core


  • SparkSQL
  • Streaming
  • MLlib
  • GraphX


  • Scala
  • Python
  • Java
  • R


  • Standalone
  • Mesos
  • Yarn

Data Stores

  • HDFS
  • Cassandra
  • Hbase
  • Kafka
  • Elasticsearch

Optimize applications and pipelines

  • Detect and fix inefficient and failed applications
  • Troubleshoot multi-system pipelines from a single location
  • Ensure compliance on reliability, throughput, and response-time SLAs

Get powerful insights into data usage and access

  • Ensure optimal use of in-memory data caching
  • Optimize HDFS, NoSQL, and Kafka usage for Spark
  • Detect and fix poor partitioning

Optimize your big data resources

  • Optimize container sizes for Spark on Mesos and YARN
  • Get instructions for tuning JVM for Spark drivers and executors
  • Minimize data shuffles

See how StitchFix solves problems with their Spark applications