Speedata announced the launch of Workload Analyzer.
The browser-based performance predictor tool analyzes Spark log files to help data engineers learn how to maximize workload performance, both in the cloud and on-prem.
Speedata's Workload Analyzer provides data engineers and platform administrators with valuable insights into the performance of their Spark queries. The tool demonstrates how an enterprise's workload would perform in different environments, assisting engineers in determining the impact of certain infrastructure decisions such as deploying a faster network or adding more servers.
"Our team is committed to providing enterprises with the tools needed to accelerate their big data analytics workloads," said Jonathan Friedmann, Co-Founder & CEO of Speedata. "The Workload Analyzer is one of those tools, helping businesses focus on what's working and how to improve what's not. It's designed to help data engineers optimize their analytics with available infrastructure, set realistic goals, maximize their data, and maintain their competitive edge."
The Workload Analyzer also demonstrates the performance improvement of an enterprise's data analytics workload when running on Speedata's APU. APU alleviates the main bottlenecks of data analytics, significantly improving workloads' speed and performance, dramatically reducing costs, and increasing efficiency.
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