There's a better way to resolve Big Data performance issues than spending hours sifting through monitoring graphs and logs
Managing big data operations in a multi-tenant cluster is complex. It's hard to diagnose problems, like rogue applications, missed SLAs, cascading cluster failures, application slowdowns, stuck jobs, and failed queries. Also, it’s becoming hard to track who is doing what, understand cluster usage and application performance, justify resource demands, and forecast capacity needs.
- Gain full visibility across the big data stack
- Understand, improve and control application performance in production across systems like Hadoop, Spark, Kafka, Impala, Amazon Web Services, etc.